Search Results (4,173)

Due to human activities and the invasion of Spartina alterniflora, the population of Scirpus mariqueter (S. mariqueter) in the Yangtze River Estuary has gradually declined. To address this issue, numerous restoration efforts have been undertaken. To investigate the changes and influencing factors of soil bacterial communities during the restoration of S. mariqueter wetlands, we selected S. mariqueter populations as the research focus and divided the samples into two years, S1 and S2. High-throughput sequencing technology was employed for observation and analysis. The results revealed that from S1 to S2, soil bacterial diversity in the S. mariqueter wetland increased significantly and displayed clear seasonal patterns. The dominant bacterial phyla included Proteobacteria, Bacteroidota, Firmicutes, and Acidobacteriota. Among these, Proteobacteria had the highest relative abundance, while Acidobacteriota showed the most pronounced increase, surpassing Bacteroidota and Firmicutes to become the second most abundant group. Redundancy analysis (RDA) indicated that soil organic matter and electrical conductivity were the key factors influencing the composition and diversity of the soil bacterial community, with Acidobacteriota playing a dominant role during wetland restoration. In conclusion, during the ecological restoration of the S. mariqueter wetlands, attention should be given to environmental factors such as soil organic matter and electrical conductivity, while the regulatory role of Acidobacteriota in wetland soils should not be overlooked. This study provides a microscopic perspective on the interactions between microbial diversity and ecosystem functions in coastal wetlands, offering valuable guidance for the ecological restoration of degraded wetlands. Full article

The evolutionary loss of ednrb2 in specific vertebrate lineages, such as mammals and cypriniform fish, raises fundamental questions about its functional necessity and potential redundancy or synergy with paralogous endothelin receptors in pigment cell development. In teleosts possessing both ednrb1a and ednrb2 (e.g., Nile tilapia), their respective and combined roles in regulating neural crest-derived pigment cell precursors remains unresolved. Using CRISPR/Cas9, we generated single and double ednrb mutants to dissect their functions. We demonstrated that ednrb1a and ednrb2 synergistically govern the differentiation and migration of iridophore precursors. While ednrb1a is broadly essential for iridophore development, ednrb2 plays a unique and indispensable role in the colonization of iridophores in the dorsal iris. Double mutants exhibit near-complete iridophore loss; severe depletion of melanophores, xanthophores, and erythrophores; and a striking, fertile, transparent phenotype. Crucially, this iridophore deficiency does not impair systemic guanine synthesis pathways. mRNA rescue experiments confirmed mitfa as a key downstream effector within the Ednrb signaling cascade. This work resolves the synergistic regulation of pigment cell fates by Ednrb receptors and establishes a mechanism for generating transparent ermplasm. Full article

Injecting industrial high-temperature flue gas into hydrocarbon reservoirs has emerged as a novel approach for carbon sequestration. However, the complex high-temperature phase behavior between flue gas (CO₂, N₂) and reservoir fluids challenges this technology’s development, as traditional experimental methods and theoretical models often fall short in capturing it accurately. To address this, molecular dynamics simulations were employed in this study to investigate the phase behavior of single-component alkanes, multicomponent alkane mixtures, and multicomponent alkane–flue gas systems under high-temperature conditions. The results reveal that CO₂ can become miscible with alkanes, while N₂ diffuses into the system, causing volumetric expansion and a reduction in density. The initially distinct phase interface between the multicomponent alkanes and the flue gas becomes progressively blurred and eventually disappears, indicating the formation of a fully miscible phase. Comparative simulations revealed that the diffusion coefficients of N₂ and CO₂ increased by up to 20% with rising temperature and pressure, while variations in flue gas composition had negligible effects, indicating that high-temperature and high-pressure conditions significantly enhance flue gas–alkane miscibility. Full article

Emotion analysis based on electroencephalogram (EEG) sensors is pivotal for human–machine interaction yet faces key challenges in spatio-temporal feature fusion and cross-band and brain-region integration from multi-channel sensor-derived signals. This paper proposes MB-MSTFNet, a novel framework for EEG emotion recognition. The model constructs a 3D tensor to encode band–space–time correlations of sensor data, explicitly modeling frequency-domain dynamics and spatial distributions of EEG sensors across brain regions. A multi-scale CNN-Inception module extracts hierarchical spatial features via diverse convolutional kernels and pooling operations, capturing localized sensor activations and global brain network interactions. Bi-directional GRUs (BiGRUs) model temporal dependencies in sensor time-series, adept at capturing long-range dynamic patterns. Multi-head self-attention highlights critical time windows and brain regions by assigning adaptive weights to relevant sensor channels, suppressing noise from non-contributory electrodes. Experiments on the DEAP dataset, containing multi-channel EEG sensor recordings, show that MB-MSTFNet achieves 96.80 ± 0.92% valence accuracy, 98.02 ± 0.76% arousal accuracy for binary classification tasks, and 92.85 ± 1.45% accuracy for four-class classification. Ablation studies validate that feature fusion, bidirectional temporal modeling, and multi-scale mechanisms significantly enhance performance by improving feature complementarity. This sensor-driven framework advances affective computing by integrating spatio-temporal dynamics and multi-band interactions of EEG sensor signals, enabling efficient real-time emotion recognition. Full article

Ischemic stroke is a serious disease that frequently occurs in the elderly and is characterized by a complex pathophysiology and a limited number of effective therapeutic agents. Salvianolic acid A (SAL-A) is a natural product derived from the rhizome of Salvia miltiorrhiza, which possesses diverse pharmacological activities. This study aims to investigate the effect and mechanisms of SAL-A in inhibiting ferroptosis to improve ischemic stroke. Brain injury, oxidative stress and ferroptosis-related analysis were performed to evaluate the effect of SAL-A on ischemic stroke in photochemical induction of stroke (PTS) in mice. Lipid peroxidation levels, antioxidant protein levels, tissue iron content, nuclear factor erythroid 2-related factor 2 (Nrf2), and mitochondrial morphology changes were detected to explore its mechanism. SAL-A significantly attenuated brain injury, reduced malondialdehyde (MDA) and long-chain acyl-CoA synthase 4 (ACSL4) levels. In addition, SAL-A also amplified the antioxidative properties of glutathione (GSH) when under glutathione peroxidase 4 (GPX4), and the reduction in ferrous ion levels. In vitro, brain microvascular endothelial cells (b.End.3) exposed to oxygen-glucose deprivation/reoxygenation (OGD/R) were used to investigate whether the anti-stroke mechanism of SAL-A is related to Nrf2. Following OGD/R, ML385 (Nrf2 inhibitor) prevents SAL-A from inhibiting oxidative stress, ferroptosis, and mitochondrial dysfunction in b.End.3 cells. In conclusion, SAL-A inhibits ferroptosis to ameliorate ischemic brain injury, and this effect is mediated through Nrf2. Full article

In this paper, a novel 4H-SiC LDMOS structure with a trench heterojunction in the source (referred as to THD-LDMOS) is proposed and investigated for the first time, to enhance the reverse recovery performance of its parasitic diode. Compared with 4H-SiC, silicon has a smaller band energy, which results in a lower built-in potential for the junction formed by P+ polysilicon and a 4N-SiC N-drift region. A trench P+ polysilicon is introduced in the source side, forming a heterojunction with the N-drift region, and this heterojunction is unipolar and connected in parallel with the body PiN diode. When the LDMOS operates as a freewheeling diode, the trench heterojunction conducts first, preventing the parasitic PiN from turning on and thereby significantly reducing the number of carriers in the N-drift region. Consequently, THD-LDMOS exhibits superior reverse recovery characteristics. The simulation results indicate that the reverse recovery peak current and reverse recovery charge of THD-LDMOS are reduced by 55.5% and 77.6%, respectively, while the other basic electrical characteristics remains unaffected. Full article

Browning significantly impacts the commercial value of luffa (luffa cylindrica) and is primarily driven by the metabolic processes of phenolic acids. Investigating changes in phenolic acids during browning aids in understanding the physiological mechanisms underlying this process and provides a basis for improving storage, processing, variety breeding, and utilization of germplasm resources. This study compared browning-resistant (‘30’) and browning-sensitive (‘256’) luffa varieties using high-throughput sequencing and metabolomics techniques. The results revealed 55 genes involved in the phenylpropanoid biosynthesis pathway, including 8 phenylalanine ammonia-lyase (PAL) genes, 20 peroxidase (POD) genes, 2 polyphenol oxidase (PPO) genes associated with tyrosine metabolism, and 37 peroxisome-related genes. Real-time quantitative (qPCR) was employed to validate 15 browning-related genes, revealing that the expression levels of LcPOD21 and LcPOD6 were 12.5-fold and 25-fold higher in ‘30’ compared to ‘256’, while LcPAL5 and LcPAL4 were upregulated in ‘30’. Enzyme analysis showed that catalase (CAT) and phenylalanine ammonia-lyase (PAL) activities were higher in ‘30’ than in ‘256’. Conversely, superoxide dismutase (SOD) and polyphenol oxidase (PPO) activities were reduced in ‘30’, whereas CAT activity was upregulated. The concentrations of cinnamic acid, p-coumaric acid, trans-5-O-(4-coumaroyl)mangiferic acid, and caffealdehyde were lower in browning-resistant luffa ‘30’ than in browning-sensitive luffa ‘256’, suggesting that their levels influence browning in luffa. These findings elucidate the mechanisms underlying browning and inform strategies for the storage, processing, and genetic improvement of luffa. Full article

Knowledge-graph-based recommendation aims to provide personalized recommendation services to users based on their historical interaction information, which is of great significance for shopping transaction rates and other aspects. With the rapid growth of online shopping, the knowledge graph constructed from users’ historical interaction data now incorporates multiattribute information, including timestamps, images, and textual content. The information of multiple modalities is difficult to effectively utilize due to their different representation structures and spaces. The existing methods attempt to utilize the above information through simple embedding representation and aggregation, but ignore targeted representation learning for information with different attributes and learning effective weights for aggregation. In addition, existing methods are not sufficient for effectively modeling temporal information. In this article, we propose MTR, a knowledge graph recommendation framework based on mixture of experts network. To achieve this goal, we use a mixture-of-experts network to learn targeted representations and weights of different product attributes for effective modeling and utilization. In addition, we effectively model the temporal information during the user shopping process. A thorough experimental study on popular benchmarks validates that MTR can achieve competitive results. Full article

The advancement of Artificial Intelligence (AI) has significantly accelerated progress across various research domains, with growing interest in plant science due to its substantial economic potential. However, the integration of AI with digital vegetation analysis remains underexplored, largely due to the absence of large-scale, real-world plant datasets, which are crucial for advancing this field. To address this gap, we introduce the PP3D dataset—a meticulously labeled collection of about 500 potted plants represented as 3D point clouds, featuring fine-grained annotations for approximately 20 species. The PP3D dataset provides 3D phenotypic data for about 20 plant species spanning model organisms (e.g., Arabidopsis thaliana), potted plants (e.g., Foliage plants, Flowering plants), and horticultural plants (e.g., Solanum lycopersicum), covering most of the common important plant species. Leveraging this dataset, we propose the panoptic plant recognition task, which combines semantic segmentation (stems and leaves) with leaf instance segmentation. To tackle this challenge, we present SCNet, a novel dual-representation learning network designed specifically for plant point cloud segmentation. SCNet integrates two key branches: a cylindrical feature extraction branch for robust spatial encoding and a sequential slice feature extraction branch for detailed structural analysis. By efficiently propagating features between these representations, SCNet achieves superior flexibility and computational efficiency, establishing a new baseline for panoptic plant recognition and paving the way for future AI-driven research in plant science. Full article

Water science has always been a central part of modern scientific research. In this study, the viscosity and hydrogen bond structures of methanol aqueous solutions with different molar ratios were investigated via confocal microscopic Raman spectroscopy. The Raman spectra of methanol in the CH and CO stretching regions were measured in order to investigate the structure of water/methanol molecules. The points of transition were identified by observing changes in viscosity following changes in concentration, and the bands were assigned to the C-H bond vibration shifts where the molar ratios of methanol and water were 1:3 and 3:1. Furthermore, the large band shift of 19 cm⁻¹ between the methanol solutions with the lowest and highest concentrations contained three hydrogen bond network modes, affecting the viscosity of the solution. This study provides an explanation for the relationship between the microstructures and macroscopic properties of aqueous solutions. Full article

The significant energy intensity of high-speed railway necessitates integrating renewable technologies to enhance grid resilience and decarbonize transport. This study establishes a coordinated carbon–green certificate market mechanism for railway power systems and develops a tri-source planning model (grid/solar/energy storage) that comprehensively considers the full lifecycle carbon emissions of these assets while minimizing lifecycle costs and CO₂ emissions. The proposed EDMOA algorithm optimizes storage configurations across multiple operational climatic regimes. Benchmark analysis demonstrates superior economic–environmental synergy, achieving a 23.90% cost reduction (USD 923,152 annual savings) and 24.02% lower emissions (693,452.5 kg CO₂ reduction) versus conventional systems. These results validate the synergistic integration of hybrid power systems with the carbon–green certificate market mechanism as a quantifiable pathway towards decarbonization in rail infrastructure. Full article

The thalamus is an important sensory relay station. It integrates all somatic sensory pathways (excluding olfaction) and transmits information through thalamic relay neurons before projecting to the cerebral cortex via thalamocortical axons (TCAs). Emerging evidence has shown that FGF3, a member of the morphogen family, is an axon guidance molecule that repels TCAs away from the hypothalamus and into the internal capsule so that they subsequently reach different regions of the cortex. However, current studies on FGF-mediated axon guidance predominantly focus on phenomenological observations, with limited exploration of the underlying molecular mechanisms. To address this gap, we investigated both direct and indirect downstream signaling pathways mediating FGF3-dependent chemorepulsion of TCAs at later developmental stages. Firstly, we used pharmacological inhibitors to identify the signaling cascade(s) responsible for FGF3-triggered direct chemorepulsion of TCAs, in vitro and in vivo. Our results demonstrate that the PC-PLC pathway is required for FGF3 to directly stimulate the asymmetrical repellent growth of developing TCAs. Then, we found the FGF3-mediated repulsion can be indirectly induced by Slit1 because the addition of FGF3 in the culture media induced an increase in Slit1 expression in the diencephalon. Furthermore, by using downstream inhibitors, we found that the indirect repulsive effect of FGF3 is mediated through the PI3K downstream pathway of FGFR1. Full article

Driven by industry–education integration and digital technology, higher vocational education textbooks are transitioning from traditional formats to an integrated “loose-leaf + digital” model. Combining the flexibility of loose-leaf textbooks with digital technology, these new materials enable real-time updates and align closely with industry practices. We explored the era connotations of integrated textbooks and proposed a development process based on cognitive psychology, interdisciplinary integration, and synergy theory. Continuous optimization through robust evaluation systems and digital platforms is required to provide modernized and informatized vocational education. Full article

Background: BDE-47, a pervasive environmental pollutant detected in >90% of human serum samples, is increasingly linked to metabolic disorders. This study investigates the specific impact of BDE-47 exposure on the gut microbiota in prediabetic mice and evaluates the efficacy of therapeutic interventions in mitigating these effects. Objectives: To determine whether BDE-47 exposure induces diabetogenic dysbiosis in prediabetic mice and to assess whether dietary interventions, such as grape exosomes and an antioxidant cocktail, can restore a healthy microbiota composition and mitigate diabetes risk. Methods: In this study, a prediabetic mouse model was established in 54 male SPF-grade C57BL/6J mice through a combination of high-sugar and high-fat diet feeding with streptozotocin injection. Oral glucose tolerance tests (OGTT) were conducted on day 7 and day 21 post-modeling to assess the establishment of the model. The criteria for successful model induction were defined as fasting blood glucose levels below 7.8 mmol/L and 2 h postprandial glucose levels between 7.8 and 11.1 mmol/L. Following confirmation of model success, a 3 × 3 factorial design was applied to allocate the experimental animals into groups based on two independent factors: BDE-47 exposure and exosome intervention. The BDE-47 exposure factor consisted of three dose levels—none, high-dose, and medium-dose—while the exosome intervention factor included three modalities—none, Antioxidant Nutrients Intervention, and Grape Exosomes Intervention. Fresh fecal samples were collected from mice two days prior to sacrifice. Cecal contents and segments of the small intestine were collected and transferred into 1.5 mL cryotubes. All sequences were clustered into operational taxonomic units (OTUs) based on defined similarity thresholds. To compare means across multiple groups, a two-way analysis of variance (ANOVA) was employed. The significance level was predefined at α = 0.05, and p-values < 0.05 were considered statistically significant. Bar charts and line graphs were generated using GraphPad Prism version 9.0 software, while statistical analyses were performed using SPSS version 20.0 software. Results: The results of 16S rDNA sequencing analysis of the microbiome showed that there was no difference in the α diversity of the intestinal microbiota in each group of mice (p > 0.05), but there was a difference in the Beta diversity (p < 0.05). At the gate level, the abundances of Proteobacteria, Campylobacterota, Desulfobacterota, and Fusobacteriota in the medium-dose BDE-7 group were higher than those in the model control group (p < 0.05). The abundance of Patellar bacteria was lower than that of the model control group (p < 0.05). The abundances of Proteobacteria and Campylobacterota in the high-dose BDE-7 group were higher than those in the model control group (p < 0.05). The abundance of Planctomycetota and Patescibacteria was lower than that of the model control group (p < 0.05), while the abundance of Campylobacterota in the grape exosome group was higher than that of the model control group (p < 0.05). The abundance of Patescibacteria was lower than that of the model control group (p < 0.05), while the abundance of Firmicutes and Fusobacteriota in the antioxidant nutrient group was higher than that of the model control group (p < 0.05). However, the abundance of Verrucomicrobiota and Patescibacteria was lower than that of the model control group (p < 0.05). At the genus level, the abundances of Bacteroides and unclassified Lachnospiraceae in the high-dose BDE-7 group were higher than those in the model control group (p < 0.05). The abundance of Lachnospiraceae NK4A136_group and Lactobacillus was lower than that of the model control group (p < 0.05). The abundance of Veillonella and Helicobacter in the medium-dose BDE-7 group was higher than that in the model control group (p < 0.05), while the abundance of Lactobacillus was lower (p < 0.05). The abundance of genera such as Lentilactobacillus and Faecalibacterium in the grape exosome group was higher than that in the model control group (p < 0.05). The abundance of Alloprevotella and Bacteroides was lower than that of the model control group (p < 0.05). In the antioxidant nutrient group, the abundance of Lachnospiraceae and Hydrogenophaga was higher than that in the model control group (p < 0.05). However, the abundance of Akkermansia and Coriobacteriaceae UCG-002 was significantly lower than that of the model control group (p < 0.05). Conclusions: BDE-47 induces diabetogenic dysbiosis in prediabetic mice, which is reversible by dietary interventions. These findings suggest that microbiota-targeted strategies may effectively mitigate the diabetes risk associated with environmental pollutant exposure. Future studies should further explore the mechanisms underlying these microbiota changes and the long-term health benefits of such interventions. Full article

Cell proliferation plays a pivotal role in multiple physiological processes, including osteoporosis alleviation, wound healing, and immune enhancement. Numerous novel peptides with cell proliferation-promoting activity have been identified. These peptides exert their functions by modulating key cellular signaling pathways, thereby regulating diverse biological processes related to cell proliferation. This work summarizes peptides derived from animals and plants that stimulate cell proliferation, focusing on their amino acid composition, physicochemical properties, and preparation techniques. Furthermore, we highlight the major signaling pathways—such as the PI3K/Akt, MAPK/ERK, and Wnt/β-catenin pathways—that have been implicated in the mechanistic studies of food-derived peptides. Through the analysis and summary of previous studies, we observe a notable lack of in vivo animal models and clinical trials, indicating that these may represent promising directions for future research on food-derived bioactive peptides. Meanwhile, the potential safety concerns of proliferation-enhancing peptides—such as immunogenicity, appropriate dosage, and gastrointestinal stability—warrant greater attention. In summary, this review provides a comprehensive overview of the sources and mechanisms of cell proliferation-promoting peptides and addresses the challenges in industrializing bioactive peptide-based functional foods; therefore, further research in this area is encouraged. Full article