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Abstract Coronary microvascular dysfunction serves as one of the etiological factors for ischemic heart disease and represents a novel therapeutic direction for coronary artery diseases; however, the research on its pathogenesis remains inconsistent. This study aims to explore the single-cell gene expression profiles in rats with coronary microvascular dysfunction using single-cell RNA sequencing, with a particular focus on the in-depth analysis of endothelial cell gene expression characteristics. By establishing a rat model of coronary microvascular dysfunction, we collected cardiac apical tissue to prepare single-cell suspensions and further analyzed them using bioinformatics methods. From a total of 55,419 cells, we identified 28 distinct cell clusters, with endothelial cells and fibroblasts being the predominant cell types. Compared to the NC group, the proportion of endothelial cells in the CMD group was significantly reduced, while the number of fibroblasts was significantly increased. Through further analysis of the endothelial cells, we classified them into normal phenotype endothelial cells, mesenchymal phenotype endothelial cells, proliferative phenotype endothelial cells, and lymphatic endothelial cells, with mesenchymal and proliferative endothelial cells originating from normal phenotype endothelial cells. Additionally, the CMD group exhibited an increase in immune cells, enhanced inflammatory response, and increased oxidative stress. These findings may provide novel potential therapeutic targets for the treatment of Coronary microvascular dysfunction.

Abstract Depression, a prevalent psychiatric disorder of ambiguous etiology and high heterogeneity, has been recently linked to the primary visual cortex (V1). However, the precise circuits mediating the impact of V1 on depressive-like behaviors are poorly understood. Here, we demonstrate that the V1, specifically the lateral posterior nucleus of the thalamus (LP)-projecting V1 glutamatergic subpopulation (GluV1→LP neurons), shows reduced activity after chronic restraint stress (CRS) in male mice, leading to depressive-like behaviors. Optogenetic or chemogenetic activation of these neurons ameliorated depressive-like behaviors in CRS-depressed mice, whereas reducing activity exacerbated these behaviors. This reduction in GluV1→LP neurons activity was predominantly due to a decrease in the guanine nucleotide-binding protein subunit gamma-4 (Gγ4). Overexpression of Gγ4 in the GluV1→LP neurons produced antidepressant-like effects, suggesting that Gγ4 is a crucial regulator of mood. Collectively, these results reveal a V1→LP circuit that modulates depressive-like behaviors, suggesting potential targets for therapeutic interventions.

Solid–liquid separation is a critical component in treating mineral processing wastewater. Its effectiveness primarily hinges on the disruption of colloidal stability in the wastewater. Flocculants play a key role in destabilizing and dehydrating these colloids. Polyacrylamide is widely utilized as a flocculant in mineral processing plants. However, it requires large dosages and contains residual toxic monomers. Developing green, efficient flocculants with multiple active sites is vital for creating an efficient solid–liquid separation process with a low dosage of flocculants, enabling efficient treatment and recycling of mineral processing wastewater. In this work, acrylamide (AM) and dimethyl diallyl ammonium chloride (DMDAAC) are grafted onto the chitosan molecular chain through UV-initiated polymerization, obtaining chitosan-grafted-cationic polyacrylamide (Chi-g-CPAM) with varying molecular structures by modifying the mass fraction of initiator. The chemical structure and crystallinity of the grafted copolymer are characterized using Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance spectroscopy (1H NMR), and X-ray diffraction. Chi-g-CPAM’s flocculation performance on kaolinite suspensions is evaluated through settling tests. The adsorption behavior of Chi-g-CPAM on silica surfaces and the flocculation kinetics of kaolinite are investigated using quartz crystal microbalance with dissipation. The adsorption morphology of Chi-g-CPAM on the SiO2 chip surface, floc structure, and flocculation mechanism are analyzed. The analysis reveals that long branched chains enhance Chi-g-CPAM’s bridging effect on kaolinite, accelerating settling. The abundant branched chains provide substantial positive sites, reducing supernatant turbidity, while short-branched chains result in a “train-like” adsorption conformation of flocculants on kaolinite surfaces, weakening the bridging effect. The grafting ratio of Chi-g-CPAM reaches 580.0% at an initiator mass fraction of 0.10%, with numerous long-branched chains. QCM-D measurements indicate that Chi-g-CPAM with these chains exhibits the maximum equilibrium adsorption capacity of (−11.68±0.40) Hz. Initially, a smaller fitting slope of 0.1814 increases to 0.5054 after 509 s, indicating an outward extending adsorption conformation. The flocculation of kaolinite by Chi-g-CPAM is minimal, forming relatively loose flocs. Under the action of Chi-g-CPAM with numerous and long branched chains, the flocculation process is more complicated, as evidenced by the high degree of fit observed in the pseudo-first-order, pseudo-second-order, and Elovich equations. The settling test results reveal that kaolinite suspensions treated by the above flocculant achieve a settling rate of 12.18 m·h–1, the highest among all tested flocculants. Additionally, the turbidity of the supernatant measures just 13 nephelometric turbidity units, indicating excellent flocculation performance. This is attributed to the synergistic interactions of charge neutralization, bridging, and net-trapping. At initiator mass fraction of 0.15% and 0.05%, the synthesized Chi-g-CPAM with short branched chains exhibits a planar "train-like" adsorption conformation on the SiO2 surface, which reduces bridging and net-trapping capacity, leading to poor flocculation performance. The molecular structure of multi-active functional flocculants affects their adsorption conformation on mineral surfaces, a critical factor in determining their flocculation performance. The findings of this study offer valuable insights into the molecular structure design of macromolecular agents for mineral processing.

The crosstalk between immune cells and the neurovascular unit plays a pivotal role in neural regeneration following central nervous system (CNS) injury. Maintaining brain immune homeostasis is crucial for restoring neurovascular function. In this study, an interactive bridge was developed via an immunomodulatory hydrogel microsphere to link the interaction network between microglia and the neurovascular unit, thereby precisely regulating immune-neurovascular crosstalk and achieving neural function recovery. This immunomodulatory crosstalk microsphere (MP/RIL4) was composed of microglia-targeted RAP12 peptide-modified interleukin-4 (IL-4) nanoparticles and boronic ester-functionalized hydrogel using biotin-avidin reaction and air-microfluidic techniques. We confirmed that the immunomodulatory microspheres reduced the expression of pro-inflammatory factors including IL-1β, iNOS, and CD86, while upregulating levels of anti-inflammatory factors such as IL-10, Arg-1, and CD206 in microglia. In addition, injection of the MP/RIL4 significantly mitigated brain atrophy volume in a mouse model of ischemic stroke, promoted neurobehavioral recovery, and enhanced the crosstalk between immune cells and the neurovascular unit, thus increasing angiogenesis and neurogenesis of stroke mice. In summary, the immunomodulatory microspheres, capable of orchestrating the interaction between immune cells and neurovascular unit, hold considerable therapeutic potential for ischemic stroke and other CNS diseases.

Abstract We conducted two experiments to examine the lexical and sub-lexical processing of Chinese two-character words in reading. We used a co-registration electroencephalogram (EEG) for the first fixation on target words. In Experiment 1, whole-word occurrence frequency and initial constituent character frequency were orthogonally manipulated, while in Experiment 2, whole-word occurrence frequency and end constituent character frequency were orthogonally manipulated. Results showed that word frequency facilitated eye-tracking measures, while initial and end character frequencies inhibited them. Classical word frequency effects on N170 and N400 in the posterior region and reversed word frequency effects over the anterior region were consistently observed in both experiments. Experiment 1 revealed an inhibiting effect of initial character frequency on anterior N170. In Experiment 2, interaction between end-character frequency and word frequency showed reliable effects on anterior N170 and N400. These results demonstrate both facilitating and inhibiting word frequency effects, along with inhibiting effects of character frequency and that word frequency moderates the inhibiting effects of end constituent character frequency during natural silent Chinese reading.

This study presents a deep learning model that integrates Vision Transformers (ViT) with Fourier spectral filtering for remote sensing lithology classification. The model automates the process of identifying and classifying various rock types in remote sensing images, addressing a multi-class classification challenge. It utilizes ViT for feature extraction, enhanced by pretrained weights for improved efficiency and accuracy in recognizing geographical features. Fourier spectral filtering further augments the model by leveraging frequency domain information for accurate classification. The model preprocesses images, extracts spatial features, applies spectral filtering, and employs a classification head to predict rock types. Optimization of parameters through backpropagation and gradient descent methods, coupled with regularization strategies, aims to prevent overfitting and ensure generalizability. This approach combines deep learning’s capability for feature extraction with the analytical power of signal processing, offering a significant advancement for automatic rock type classification in remote sensing.

Abstract Cysteine-rich polycomb-like proteins (CPPs), pivotal transcription factors crucial for evolution of plants from germination to maturity, and adaptation to environmental stresses, have not yet been characterized within the context of Moso bamboo. The CPP gene family of Moso bamboo was identified through bioinformatics, and the structural and functional attributes of the gene, including its physicochemical properties, evolutionary relationships, and gene-protein structures, were revealed. Additionally, the current study also offers valuable information on the patterns of gene expression in bamboo shoots during the period of accelerated development. The results show that the Moso bamboo genome contains 17 CPP members. Molecular phylogenetic relationships indicated that CPPs could be divided into three subfamilies and that CPP members of the same subfamily shared similar gene structures, motifs and conserved structural domains. The covariance analysis showed that the covariance between CPP and Oryza sativa was higher than that between Arabidopsis. Protein homology modeling showed that CPP proteins contain the DNA-binding domain of typical transcription factors. Transcriptomic data analysis revealed that CPP gene expression differs between tissues and organs. CPP could be regulated in response to exogenous gibberellin (GA) and naphthalene acetic acid (NAA). The qRT-PCR experiments demonstrated that CPP was crucial in the initial and fast expansion of bamboo shoots. Additionally, gene ontology (GO), KEGG enrichment and CPP regulatory network map analyses revealed multiple functional annotations of PeCPP-regulated downstream target genes. The results of this study will not only lay the foundation for further exploration of the detailed biological functions of CPP genes in the growth and development of Moso bamboo, but also establish the groundwork for future genetic enhancement of fast-growing forest trees.

Abstract With the rapid development of renewable energy, microgrid cluster systems are gradually being applied. To promote the development of microgrid cluster scheduling technology, maximize economic benefits while reducing the operating cost required for microgrid scheduling, an optimized scheduling scheme is proposed by constructing a function to minimize the operating cost of microgrids. Then, chaos mutation and Gaussian mutation are applied to improve the moth-flame algorithm that easily falling into local optima. A microgrid cluster optimization scheduling model on the basis of the improved moth-flame algorithm is constructed. The experimental results showed that the operating cost in islanding mode was 4286.21 yuan after 160 iterations. After optimizing the scheduling, the operating cost was 3912.3 yuan, with a decrease of 8.7%. The improved moth-flame algorithm had a stable average loss value of 20% and an operating efficiency of 97.19% after 10–50 iterations, which was significantly higher than other intelligent algorithms. This indicates that the improved moth-flame algorithm has high reliability and effectiveness in microgrid cluster optimization scheduling. Therefore, the proposed model effectively optimizes the scheduling scheme of microgrid cluster, providing new solutions for the efficient utilization of smart grids and renewable energy in the future.

Abstract Road damage detection (RDD) is critical to society's safety and the efficient allocation of resources. Most road damage detection methods which directly adopt various object detection models face some significant challenges due to the characteristics of the RDD task. First, the damaged objects in the road images are highly diverse in scales and difficult to differentiate, making it more challenging than other tasks. Second, existing methods neglect the relationship between the feature distribution and model structure, which makes it difficult for optimization. To address these challenges, this study proposes an efficient dense attention fusion network with channel correlation loss for road damage detection. First, the K‐Means++ algorithm is applied for data preprocessing to optimize the initial cluster centers and improve the model detection accuracy. Second, a dense attention fusion module is proposed to learn spatial‐spectral attention to enhance multi‐scale fusion features and improve the ability of the model to detect damage areas at different scales. Third, the channel correlation loss is adopted in the class prediction process to maintain the separability of intra and inter‐class. The experimental results on the collected RDDA dataset and RDD2022 dataset show that the proposed method achieves state‐of‐the‐art performance.

Effectively capturing carbon dioxide (CO2) is crucial for environmental protection. In this research, we synthesized a composite aerogel (CSA-n) by integrating a bimetallic metal-organic framework (Mg/Co-MOF-74) with biomass materials (cellulose/chitosan) using an in situ mineralization approach. This composite aerogel exhibited enhanced CO2 adsorption capabilities than pure biomass aerogel. At 298 K and 100 KPa, the CO2 adsorption capacity of CSA-3 reached 6.4 mmol/g, an increase of 16.4 % compared to pure MOF. The significant improvement of CO2 uptakes could be attributed to the more complex pore structure of the composite aerogel compared to pure MOF. Additionally, simulations based on the ideal adsorption solution theory (IAST) showed that the separation factors of CSA-3 for CO2/N2 and CO2/CH4 gas mixtures were 594.3 and 43.4, respectively. Furthermore, the composite aerogel exhibited excellent cyclic stability. After 10 cycles, the CO2 adsorption capacity of CSA-3 remained at 96.8 %. The results suggest that this bimetallic metal-organic framework @biomass hybrid aerogel holds great potential for CO2 adsorption and separation applications.

Dirigent (DIR) proteins are key regulators of lignin and lignan biosynthesis and play critical roles in plant hormone responses, abiotic stress tolerance, and growth and development. This study identified and characterized 47 PeDIR genes in Moso bamboo, classifying them into three groups. Phylogenetic and comparative analyses revealed strong evolutionary conservation, with the Moso bamboo PeDIR genes being most closely related to those in rice and maize. DIR proteins within each subfamily exhibited high conservation in motif composition, domain structure, and 3D configuration. Subcellular localization and protein interaction studies further elucidated PeDIR gene functions. Specifically, PeDIR02 primarily localized to the cell membrane and was shown to be unable to form homodimers in yeast two-hybrid (Y2H) assays. Transcriptome and expression analyses revealed the involvement of PeDIR genes in rapid shoot growth, indicating roles in lignin biosynthesis and cell wall modification. Transcriptome and qRT-PCR data also demonstrated the responsiveness of these genes to hormones and abiotic stresses, such as drought and salinity. This study constructed the first comprehensive regulatory network between transcription factors (TFs) and PeDIR genes, identifying ERF, DOF, and MYB TFs as key synergistic regulators of PeDIR gene expression.

The circadian clock, an innate timing mechanism, governs a variety of physiological activities by producing near-24-h cycles in gene expression. These cycles are reflected in patterns of metabolism and behavior. This system consists of two parts: one is the central clock located in the suprachiasmatic nucleus of the hypothalamus, and the other is the peripheral clock located in tissues throughout the body. Glucokinase, also termed hexokinase 4, is a member of the hexokinase family. It acts as a glucose sensor, plays a pivotal role in glucose homeostasis. Here, we review the role of circadian rhythm in glucose metabolism across various tissues, look into the molecular mechanism of circadian disruption involvement in glucose metabolism and diabetic complications, with a particular focus on the role of glucokinase. Finally, we propose potential strategies for effectively treating metabolic disorders and diabetic complications by modulating circadian rhythm glucokinase.

ObjectiveThe study focuses on comparing the efficacy of a low-dose combination of febuxostat and benzbromarone versus each drug used alone for the treatment of gout.MethodsA prospective, randomized, open-labeled trial of men with gout and renal uric acid underexcretion was conducted. We randomly assigned 100 patients to either low-dose febuxostat or low-dose benzbromarone for initial treatment. 43 patients with complete data were analyzed in this study. The analysis of medication Treatment effects, Period effects and Patient-Within-Sequence effects for different treatment options was performed by cross-test ANOVA.ResultThe cross-trial analysis revealed no significant differences in the magnitude of uric acid decline among the three groups after treatment. Similarly, there were no statistically significant differences in blood lipid levels, CRP, CA724, eGFR, and ALT among the three groups post-treatment. The null model without participant-specific benefits was a linear mixed model for ALT, AST, eGFR, TC, TG, LDL, UA, CRP, CA724, and 24-h uric acid with age, BMI, treatment period and treatment as fixed factors, and the intercept as a random factor by participant. The results indicated no significant differences on relevant indicators among the three treatment regimens.ConclusionOur study did not identify a difference in the efficacy of reducing uric acid excretion in gout patients when comparing conventional dose febuxostat and benzbromarone monotherapy versus low-dose combination therapy.

Abstract Extracellular vesicles (EVs) have shown great potential for treating various diseases. Translating EVs‐based therapy from bench to bedside remains challenging due to inefficient delivery of EVs to the injured area and lack of techniques to visualize the entire targeting process. Here we developed a dopamine surface functionalization platform that facilitates easy and simultaneous conjugation of targeting peptide and multi‐mode imaging probes to the surface of EVs. Utilizing this platform we concurrently modified M2 microglia‐derived EVs (M2‐EVs) with neuronal targeting peptide rabies virus glycoprotein peptide 29 (RVG29) and multi‐modal imaging tracers, resulting in the targeted delivery of M2‐EVs to stroke mice brain and enabled the dynamic visualization of the targeting process from whole‐body to cellular levels. We determined that intra‐arterial injection achieved the highest efficiency of targeted delivery of engineered EVs to the stroke mice brain, improved therapeutic efficacy by reducing neuronal apoptosis. Mechanistically, EVs miRNA array revealed that a number of anti‐apoptosis related miRNAs were significantly up‐regulated, including miR‐221‐3p and miR‐423‐3p, both exerted anti‐apoptotic effects through p38/ERK signalling pathways in stroke. Overall, this platform provides a facile and powerful tool for multifunctional engineering of EVs for multiscale therapeutic evaluation and enhancement of EV‐based therapy, with valuable prospects for clinical translation.

Crop residues have shown promise as non-conventional feed sources to enhance animal health and growth. This study evaluated the effects of chili straw (CS) on rumen fermentation, meat quality, amino and fatty acid composition, and rumen microbial diversity in sheep. Fifty F1 Dorper×Hu lambs (29.58 ± 2.06 kg) were randomly assigned to five groups, fed pelleted feed with 0%, 5%, 10%, 15%, or 20% CS over a 63-day period, including a 7-day pre-test. Post-trial, rumen fluid was sampled to assess fermentation and microbial profiles, and slaughter performance and meat quality were evaluated. Key findings include: (1) No significant differences were observed in rumen pH, NH3-N, or acetic acid-to-propionic acid ratio across groups (P > 0.05). (2) Rumen microbial diversity indices did not vary significantly between groups (P > 0.05), though the relative abundance of Firmicutes and Proteobacteria increased, and Bacteroidota decreased in CS-fed groups, with specific genus-level changes. (3) Carcass weight decreased in the CS20% group (P < 0.01). (4) Cooking loss decreased in CS10%, 15%, and 20% groups (P < 0.05), and meat redness increased in CS15% and 20% groups (P < 0.01). (5) Saturated fatty acids decreased, while the PUFA/SFA ratio and amino acid profiles, including sulfur-containing amino acids (SAA), dibasic amino acids (DAA), essential amino acids (EAA), and total amino acids (TAA), increased with CS, with a significant rise in Gly content in the CS15% group (P < 0.05). In conclusion, incorporating CS into lamb diets can enhance meat quality without adversely affecting rumen fermentation, with recommended levels between 10% and 15%.

Summary: Humans are widely exposed to phthalates, a common chemical plasticizer. Previous cohort studies have revealed that maternal exposure to monobutyl phthalate (MBP), a key metabolite of phthalates, is associated with neurodevelopmental defects. However, the molecular mechanism remains unclear. Here, we demonstrate that maternal exposure to MBP enhances neural stem cell (NSC) differentiation into astrocytes with highly expressed C3 and LCN2 in mouse offspring, resulting in increased synapse phagocytosis and cognitive dysfunction. Mechanistically, we find that MBP exposure activates the IRE1α/XBP1s (spliced XBP1) stress response pathway, which regulates key genes involved in astrocyte differentiation (SOX9 and ATF3) and reactivity (C3 and LCN2). Conditional knockout or pharmacological inhibition of IRE1α markedly inhibits NSC differentiation into astrocytes and astrocyte reactivity, attenuates synapse phagocytosis, and improves cognitive function. This phenotype is further recapitulated in a human brain organoid model. Together, these findings unveil the molecular mechanism underlying the neurodevelopmental deficits caused by a widespread environmental pollutant.

Abstract Aims Atrial fibrillation (AF) is the most common arrhythmia. Heart failure (HF) is a disease caused by heart dysfunction. The prevalence of AF and HF were progressively increasing over time. The co‐existence of AF and HF presents a significant therapeutic challenge. In order to provide new ideas for the diagnosis of AF and HF, it is necessary to carry out biomarker related studies. Methods and results The training set and validation set data of AF and HF patient samples were downloaded from the GEO database, ‘limma’ was used to compare the differences in gene expression levels between the disease group and the normal group to screen for differentially expressed genes (DEGs). Weighted correlation network analysis (WGCNA) identified the modules with the highest positive correlation with AF and HF. Functional enrichment and PPI network construction of key genes were carried out. Biomarkers were screened by machine learning. The infiltration of immune cells in AF and HF groups was evaluated by R‐packet ‘CIBERSORT’. The miRNA network was constructed and potential therapeutic agents for biomarker genes were predicted through the drugbank database. Through WGCNA analysis, it was found that the modules most positively correlated with AF and HF were MEturquoise (r = 0.21, P value = 0.09) and MEbrown (r = 0.62, P value = 8e‐12), respectively. We screened 25 genes that were highly correlated with both AF and HF. Lasso regression analysis results showed 7 and 20 core genes in AF and HF groups, respectively. The top 20 important genes in AF and HF groups were obtained as core genes by RF model analysis. Four biomarkers were obtained after the intersection of core genes in four groups, namely, GLUL, NCF2, S100A12, and SRGN. The diagnostic efficacy of four genes in AF validation sets was good (AUC: GLUL 0.76, NCF2 0.64, S100A12 0.68, and SRGN 0.76), as well as in the HF validation set (AUC: GLUL 0.76, NCF2 0.84, S100A12 0.92, and SRGN 0.68). The highest correlation with neutrophils was observed for GLUL, NCF2, and S100A12, while SRGN exhibited the strongest correlation with T cells CD4 memory resting in the AF group. GLUL, NCF2, S100A12, and SRGN were most associated with neutrophils in the HF group. A total of 101 miRNAs were predicted by four genes, and GLUL, NCF2, and S100A12 predicted a total of 10 potential therapeutic agents. Conclusions We identified four biological markers that are highly correlated with AF and HF, namely, GLUL, NCF2, S100A12, and SRGN. Our findings provide theoretical basis for the clinical diagnosis and treatment of AF and HF.

To address the shortcomings of traditional intumescent flame retardants (IFRs), a novel four-in-one IFR (M [APP/NiCo2O4]) was constructed for the first time. It integrates acid source, gas source, carbon source (crosslinking β-CD), and synergistic agent (NiCo2O4 nanoparticles) into a single entity by a co-encapsulation technology. Under the loading of 20 wt%, its flame retardant performance was significantly better than that of simple mixed flame retardants, and it could increase the limiting oxygen index of polypropylene (PP) from 18 to 30.2 and pass the UL-94 V-0 rating. At the same time, it could reduce the peak of heat release rate, total heat release, and peak of CO production of PP by 77%, 22%, and 80%, respectively, showing excellent flame retardant performance. The excellent flame retardant performance is mainly because the synergist NiCo2O4 nanoparticles in the four-in-one flame retardant can easily combine and efficiently interact with the acid source, carbon source, and gas source in the intumescent flame retardant to form a more stable protective char residue. In addition, the crosslinking β-CD shell enhances both the water resistance and initial thermal decomposition temperature of PP containing the four-in-one IFR compared to PP with simple mixed control samples. After 72 h of water resistance test, it can still maintain the UL-94 V-0 rating. The presence of the crosslinking β-CD shell also improves the compatibility of the four-in-one flame retardant in PP, and its adverse effects on the mechanical properties of PP are also significantly smaller than those of the mixed control sample.

Virtual power plants (VPPs) have recently become a prospective paradigm to support frequency control of main grid by harnessing the aggregation and regulation potential of end-side power load resources. However, in the VPPs participation in the frequency control process, the imperfect communication environment poses significant challenges for power regulation dispatch and dynamic control. This motivates us to propose a novel joint design method for frequency control and transmission communication of VPPs. First of all, a cloud-edge-end collaboration based control architecture is established. Based on this, we develop a joint design strategy for VPPs power dispatch and wired routing optimization under cloud-edge collaboration. That is, the effect of cloud-edge communication network uncertainty on VPPs power dispatch is considered, which can be overcome by using the devised routing optimization policy. Furthermore, we propose an integrated design approach for VPPs dynamic power control and wireless network performance under edge-end collaboration. Specifically, the impact of edge-end wireless network performance on VPPs dynamic power control is considered, which is able to be eliminated utilizing the developed dynamic power control strategy for VPPs cyber-physical collaborative “collection, transmission, decision and control” generalized closed-loop. Finally, simulation results validate the feasibility and efficacy of our proposed joint design method.

In this study, we examined the effects of different residual feed intakes (RFIs) on nutrient digestibility and the microbiota of the digestive tract of Dexin fine-wool sheep. Fifty 70-day-old Dexin fine-wool meat lambs were selected as the experimental group and fed in a single pen for 100 days. Based on their mid-term metabolic weight, 100-day average daily weight gain and daily feed intake, the male Dexin lambs were divided into a low-RFI group (13), a mid-RFI group (18), and a high-RFI group (11). Six male Dexin lambs were selected from each group to collect feces, rumen digesta and solid digesta. Rectal feces were collected from three lambs in each group. The results showed that the digestibility of dry matter and crude protein by sheep in the L-RFI group was than that in the H-RFI group (P < 0.05). Within the microbial population, f_Anaerovoracaceae, g_Christensenellaceae_R_7_group, p_Proteobacteria, and g_Roseburia were significantly correlated with RFI. Energy metabolism, metabolism of amino acids and carbohydrates, transport and catabolism, and cell migration pathways were upregulated in the L-RFI group. The differences in the microbiota of the digestive tract of sheep with different RFIs were reflected in the presence of some key bacterial genera rather than changes in the overall microbial diversity.

BackgroundCholesterol metabolism plays a crucial role in tumor progression and immune response modulation. However, the precise connection between cholesterol metabolism-related genes (CMRGs) and their implications for clinical prognosis, the tumor microenvironment (TME), and the outcomes of immunotherapy in gastric cancer remains to be fully elucidated.MethodsTranscriptome data and related clinical information from 675 gastric cancer patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A total of 50 cholesterol metabolism-related genes (CMRGs) were identified from the Kyoto Encyclopedia of Genes and Genomes (KEGG, hsa04979). Consensus clustering analysis was used to classify patients into distinct molecular subgroups, while principal component analysis (PCA) was applied to develop a prognostic scoring system for predicting survival and immunotherapy response. The scoring system was validated using three independent cohorts of gastric cancer patients.ResultsBased on 49 CMRGs, 675 gastric cancer patients were categorized into three distinct subgroups with varying prognoses, tumor microenvironment features, and clinical characteristics. Further differential gene analysis and consensus clustering identified two additional subgroups. The prognostic scoring system developed through PCA demonstrated that the high-score subgroup had significantly improved survival, higher tumor mutational burden (TMB), and microsatellite instability (MSI), as well as a greater number of mutated genes, indicating greater sensitivity to immunotherapy. This system was validated in a real-world cohort undergoing immunotherapy. Additionally, the correlation between GPC3 expression and cholesterol levels was confirmed, highlighting GPC3’s potential biological role.ConclusionThis study highlights the importance of CMRGs in gastric cancer, deepens our understanding of the tumor immune microenvironment, and guides individualized immunotherapy.

The study comprehensively investigated the therapeutic potential of Gymnema sylvestre triterpenoid saponin extract (GST), encompassing its hepatoprotective, immunomodulatory, and anticancer activities. The study employed a Prednisolone (PRD)-induced immunosuppressed rat model to assess the hepatoprotective and immunomodulatory effects of GST. Using this model, GST was found to modulate haematopoiesis, improving RBC, platelet, and WBC counts, underscoring its potential in hematopoietic homeostasis. Organ atrophy, a hallmark of immunosuppression in spleen, thymus, liver, and kidneys, was reversed with GST treatment, reinforcing its hepatotrophic and organotropic capabilities. Elevated hepatic biomarkers, including alanine transaminase (ALT), aspartate transaminase (AST), alkaline phosphatase (ALP), and lipid peroxidase (LPO), indicative of hepatocellular injury and oxidative stress, were reduced with GST, underscoring its hepatoprotective and antioxidative effects. Additionally, GST restored depleted antioxidants glutathione (GSH) and superoxide dismutase (SOD), highlighting its strong antioxidative capabilities. Molecular insights revealed a downregulation of interleukin-2 (IL-2) and interleukin-4 (IL-4) mRNA in the spleen of immunosuppressed rats, while GST treatment significantly upregulated IL-2 and IL-4 mRNA expression, showcasing its immunomodulatory potential. Increased levels of tumor necrosis factor-α (TNF-α) associated with immune dysregulation were effectively decreased by GST, underscoring its role in modulating inflammatory responses and restoring immune balance. Molecular docking studies indicated strong inhibition of TNF-α by GST compounds. In terms of anticancer activity, GST demonstrated significant cytotoxicity against MCF-7, and MDA-MB-231 (breast cancer cell lines). Notably, GST demonstrated biocompatibility with normal CHO (Chinese hamster ovary cell line) and HUVEC (Human umbilical vein endothelial cells) cell lines. Molecular docking studies indicated strong inhibition of breast cancer proteins HER1 and HER2 (human epidermal growth factor receptors) by GST compounds. Additionally, pharmacokinetics, bioavailability, drug-likeness, and toxicity risk predictions suggest that GST compounds are pharmacologically favourable with no adverse effects.

Mixed-matrix membranes (MMMs) leverage the processability of polymers and selectivity of Metal-Organic Frameworks (MOFs). However, they still suffer from poor interfacial compatibility and limited scalability in preparation. In certain polymers, MOFs can bridge the pores within the polymer membrane, enhancing the CO2 adsorption and solubility properties, thus selectively boosting the CO2 permeability. In this study, high-performance MMMs were prepared using scalable CALF-20 in combination with PIM-1. MMMs with a 5% doping level achieved CO2 permeability up to 8003 barrer with 25% improvement in CO2/N2 selectivity. This enhancement was attributed to well-designed MMMs, where MOFs matched the abundant non-interconnecting pores in the PIM-1 membrane. This study represents a significant advancement towards scaling up the preparation of high-performance MOF-based MMMs for carbon capture applications.

BackgroundColorectal cancer (CRC) is a leading cause of morbidity and mortality, and timely diagnosis and intervention are crucial for cancer patients. Transfer RNA-derived fragments (tRFs) play a noncoding regulatory role in organisms. Serum EV(extracellular vesicles), as an integral mediator of intercellular transmission of genetic information vesicles in Transfer RNA-derived fragment (tRF RNA), are expected to be minimally invasive diagnostic and predictive biologic factors of CRC.MethodsCollect serum samples from 205 CRC patients, and then isolate extracellular vesicles from the serum. Captured the physical morphology of EV through transmission electron microscopy. The particle size was detected by particle size assay, and protein expression on the surface of EV was verified by Western blot. Gene microarrays were screened for differentially expressed tRF-RNA. TRF RNAs were verified by qPCR for differential expression in 205 CRC patients and 201 healthy donors, assessing the CRC diagnostic efficiency by area under the curve (AUC).ResultsCompared with 201 healthy donors, CRC patients experienced significantly down-regulated serum EV 3’tRF-ThrCGT while significantly up-regulated 3’tRF-mtlleGAT. Serum EV 3’tRF-ThrCGT and 3’tRF-mtlleGAT predictive diagnostic efficiency: 0.669 and 0.656, and the combination of CEA and CA724 predictive diagnostic efficiency was 0.938.ConclusionThe study data showed that 3’tRF-ThrCGT and 3’tRF-mtlelGAT can be minimally invasive diagnostic CRC indicators. The combination of tumor markers CEA and CA724 has important diagnostic significance.

Abstract As a new avenue for cancer research, phototheranostics has shown inexhaustible and vigorous vitality as it permits real‐time diagnosis and concurrent in situ therapy upon non‐invasive light‐initiation. However, construction of an advanced material, allowing prominent phototheranostic outputs and synchronously surmounting the inherent deficiency of phototheranostics, would be an appealing yet significantly challenging task. Herein, an aggregation‐induced emission (AIE)‐active luminogen (namely DBD‐TM) featured by intensive electron donor‐acceptor strength and twisted architecture with finely modulated intramolecular motion, is tactfully designed and prepared. DBD‐TM simultaneously possessed fluorescence emission in the second near‐infrared (NIR‐II) region and high‐efficiency photothermal conversion. By integrating DBD‐TM with anti‐angiogenic agent sorafenib, a versatile nanomaterial is smoothly fabricated and utilized for trimodal imaging‐navigated synergistic therapy involving photothermal therapy and anti‐angiogenesis toward cancer. This advanced approach is capable of affording accurate tumor diagnosis, complete tumor elimination, and largely restrained tumor recurrence, evidently denoting a prominent theranostic formula beyond phototheranostics. This study will offer a blueprint for exploiting a new generation of cancer theranostics.

Abstract Heart disease is the world’s leading cause of death. Diagnostic models based on electrocardiograms (ECGs) are often limited by the scarcity of high-quality data and issues of data imbalance. To address these challenges, we propose a conditional generative adversarial network (CECG-GAN). This strategy enables the generation of samples that closely approximate the distribution of ECG data. Additionally, CECG-GAN addresses waveform jitter, slow processing speeds, and dataset imbalance issues through the integration of a transformer architecture. We evaluated this approach using two datasets: MIT-BIH and CSPC2020. The experimental results demonstrate that CECG-GAN achieves outstanding performance metrics. Notably, the percentage root mean square difference (PRD) reached 55.048, indicating a high degree of similarity between generated and actual ECG waveforms. Additionally, the Fréchet distance (FD) was approximately 1.139, the root mean square error (RMSE) registered at 0.232, and the mean absolute error (MAE) was recorded at 0.166.

Due to limited antenna space, high communication requirements, and strict regulatory constraints, the design of antennas for modern mobile phones has become an exceedingly challenging task. In recent years, numerous studies have been conducted in this area, leading to significant advancements. This review paper comprehensively summarizes recent progress made in antenna design for modern mobile phones. Firstly, the challenges faced in antenna design for modern mobile phones are described, including bandwidth enhancement, integration and decoupling techniques, mm-wave array antennas, satellite communication antennas, as well as interactions between mobile antennas and the human body. Secondly, the basic antenna types (such as inverted-F, slot, loop, and planar inverted-F antennas) commonly used in modern metal-bezel mobile phones along with their key characteristics are briefly summarized. Thirdly, the commonly exployed methods used in practical applications for designing wideband antennas within compact sizes and achieving decoupling among multiple antennas with wide bandwidths are collected. Fourthly, recent advances in the design of compact, wideband, and wide-angle scanning mm-wave arrays for modern mobile phones are summarized. Fifthly, recent progress made in satellite communication antenna designs for modern mobile phones, including broadside and end-fire radiation patterns, is presented. Sixthly, recent studies on the interaction between mobile antennas and the human body are briefly concluded. Finally, the future challenge of antenna design for mobile phones is briefly discussed. It is our hope that this comprehensive review will provide readers with a systematic understanding of antenna design principles applicable to modern mobile phones.

The study of the attachment process between particles and bubbles in a turbulent environment is essential for understanding the microscopic process of flotation. The interaction force model between particles and bubbles is developed based on the API (Application Programming Interface) secondary development module of EDEM. The model establishes a three-dimensional discrete element method (DEM) to simulate the interaction process between particles and bubbles. Isotropic turbulence is generated by constructing regular grids in the Fluent software. The turbulent environment is then incorporated into the EDEM software using the computational fluid dynamics discrete element (CFD-DEM). The simulation consists of regular particles with sizes ranging from 0.10 to 0.30 mm and densities of 1500, 2000 and 2500 kg/m3. Additionally, the irregular particles with sphericity values ranging from 0.746 to 0.854 are included. Bubble sizes are set at 1.00, 1.20, 1.60, and 2.00 mm. To study the attachment process between particles and bubbles, the distance between the grid and the bubble in the turbulent environment are set as 1.00, 1.50, 2.00, and 3.00 mm. The results demonstrate the existence of a critical detachment flow rate (the minimum turbulent flow velocity where particles and bubbles cannot achieve a stable attachment state) for both regular and irregular particles adhering to bubbles in a turbulent environment. It is found that the particles with larger density and diameter exhibit a smaller critical detachment flow velocity when adhering to bubbles, indicating that particles with larger diameter and density have difficulty in achieving stable attachment with bubbles. As the bubble diameter increases, the critical detachment flow velocity required for stable particle-bubble attachment decreases, making it more difficult for particles to achieve stable attachment. At the same flow velocity, a smaller distance between the bubbles and the grid results in a higher turbulent flow intensity, leading to a smaller critical detachment flow velocity for stable particle-bubble attachment, suggesting that an increase in turbulent intensity is detrimental to the stable attachment of particles and bubbles. Furthermore, the particles with lower sphericity also exhibit a smaller critical detachment flow velocity for stable attachment to bubbles, indicating that the particles with lower sphericity have difficulty in achieving stable attachment with bubbles.

As a key element of spatial governance, marine protected areas (MPAs) have been increasingly established in various countries, with lessons learned from terrestrial environmental protection. Nevertheless, the development of MPAs in China continues to trail behind that of their land-based counterparts. Here, following the leverage points perspective of sustainability interventions, this article presents a systematic analysis of the governance and evolution of China’s MPAs, identifying key areas for improvement. The analysis encompasses the number, effectiveness, legal framework, governance structure, value, and paradigm of MPAs, and highlights the associated governance challenges facing China. Drawing on relevant experiences from the United States, Australia, and the European Union, the article offers valuable insights for informing China’s future MPA strategies. The study concludes that while China has made significant progress in the development of MPAs, further efforts are needed, including paradigm shifts, refinement of the legal system, optimization of governance structures, and enhancement of MPA effectiveness.

The South American tomato pinworm, Tuta absoluta (Meyrick), is one of the major invasive pests that causes severe economic damage to several hosts, especially tomato plants, globally. Spinosad, a biopesticide widely used against several insect pests, also shows promising results against T. absoluta. Here, we investigated the evolution of spinosad resistance and its effects on biological traits and related gene effects to fully understand the relationship between resistance degree and associated fitness costs. The spinosad-resistant strain (SpRS) with a moderate level of resistance (14.40-fold) was developed following continuous selection of the susceptible strain (SS) against spinosad for eight generations. Fitness analysis showed that the larval and pupal developmental durations were significantly increased, while the adult emergence was substantially reduced in the SpRS compared to SS. Adult longevity (male and female), fecundity, and hatching rates significantly decreased in the SpRS T. absoluta compared to SS. Additionally, the gene expression analyses indicated the down-regulation of development and reproduction-related genes (Vg, VgR, JHBP, JHAMT, JHE, and JHDK) in the SpRS population. Further, the mRNA expression level of the resistance-related cytochrome P450 gene CYP321C40, followed by CYP4M116, CYP6AW1, CYP339A1, and CYP6AB327, were significantly increased in the SpRS T. absoluta. Taken together, these results indicated that although T. absoluta developed a moderate level of spinosad resistance accompanied by fitness costs, continuous and indiscriminate use might elevate the resistance level. Overall, these findings provide important information about the trade-off between resistance degree and fitness cost that might be crucial to designing resistance management strategies against this key invasive herbivore.

Chalcone synthase (CHS), the first key structural enzyme in the flavonoid biosynthesis pathway, plays a crucial role in regulating plant responses to abiotic stresses and hormone signaling. However, its molecular functions remain largely unknown in Phyllostachys edulis, which is one of the most economically and ecologically important bamboo species and the most widely distributed one in China. This study identified 17 CHS genes in Phyllostachys edulis and classified them into seven subgroups, showing a closer evolutionary relationship to CHS genes from rice. Further analysis of PeCHS genes across nine scaffolds revealed that most expansion occurred through tandem duplications. Collinearity analysis indicated strong evolutionary conservation among CHS genes. Motif and gene structure analyses confirmed high structural similarity, suggesting shared functional characteristics. Additionally, cis-acting element analysis demonstrated that PeCHS genes are involved in hormonal regulation and abiotic stress responses. RNA-Seq expression profiles in different bamboo shoot tissues and heights, under various hormone treatments (gibberellin (GA), naphthaleneacetic acid (NAA), abscisic acid (ABA), and salicylic acid (SA)), as well as salinity and drought stress, revealed diverse response patterns among PeCHS genes, with significant differential expression, particularly under hormone treatments. Notably, PeCHS14 consistently maintained high expression levels, suggesting its key role in stress response mechanisms. qRT-PCR analysis further validated the expression differences in five PeCHS genes under GA and ABA treatments. Subcellular localization analysis demonstrated that PeCHS14 and PeCHS15 proteins are localized in the nucleus. This study provides a foundation for investigating the potential functions of PeCHS genes and identifies candidate genes for future research on the responses of Phyllostachys edulis to abiotic stresses and hormone signaling.

Vitamin D binding protein (VDBP) serves as a key transporter protein responsible for binding and delivering vitamin D and its metabolites to target organs. VDBP plays a crucial part in the inflammatory reaction following tissue damage and is engaged in actin degradation. Recent research has shed light on its potential role in various diseases, leading to a growing interest in understanding the implications of VDBP in psychiatric and neurological disorders. The purpose of this review was to provide a summary of the existing understanding regarding the involvement of VDBP in neurological and psychiatric disorders. By examining the intricate interplay between VDBP and these disorders, this review contributes to a deeper understanding of underlying mechanisms and potential therapeutic avenues. Insights gained from the study of VDBP could pave the way for novel strategies in the diagnosis, prognosis, and treatment of psychiatric and neurological disorders.

The effects of global climate change have accelerated the melting of glaciers and the decline of sea ice coverage in the Arctic. In tandem with advancements in icebreaker and other shipping technologies, the navigability of Arctic shipping routes has dramatically improved. Given the geographical advantages of the Arctic region in terms of shipping routes and resource potential, various countries have implemented initiatives to secure a foothold in the Arctic shipping industry. However, the current shipping industry has not yet achieved the ideal state of net-zero emissions, and the rapid increase in Arctic shipping has brought serious and even irreversible negative impacts on the Arctic environment. The study employs document and policy analyses to conduct an in-depth examination of legal and policy documents related to Arctic shipping, especially those from the past 5 years, systematically outlining the relevant legal and policy frameworks, as well as their historical context. At the same time, interdisciplinary research methods are utilized to comprehensively assess the new challenges. It is concluded that against the backdrop of the Arctic region’s unique and fragile environment, the International Maritime Organization (IMO) and the Arctic Council are introducing increasingly stringent regulations for Arctic shipping, posing a complex array of challenges for the industry. Not only must it navigate the mounting pressure of emission reduction policies and intensifying public scrutiny but it must also overcome a multitude of complex technical and operational hurdles. Consequently, the joint efforts of the international community are essential to promote the sustainable development and emission reduction goals of the Arctic shipping industry.

Background: Although limited in predictive accuracy, polygenic scores (PGS) for educational outcomes are currently available to the public via direct-to-consumer genetic testing companies. Further, there is a growing movement to apply PGS in educational settings via ‘precision education.’ Prior scholarship highlights the potentially negative impacts of such applications, as disappointing results may give rise a “polygenic Pygmalion effect.” In this paper two studies were conducted to identify factors that may mitigate or exacerbate negative impacts of PGS. Methods: Two studies were conducted. In each, 1188 students were randomized to one of four conditions: Low-percentile polygenic score for educational attainment (EA-PGS), Low EA-PGS + Mitigating information, Low EA-PGS + Exacerbating information, or Control. Regression analyses were used to examine differences between conditions. Results: In Study 1, participants randomized to Control reported significantly higher on the Rosenberg Self-Esteem Scale (RSES), Competence Scale (CS), Academic Efficacy Scale (AES) and Educational Potential Scale (EPS). CS was significantly higher in the Low EA-PGS + Mitigating information condition. CS and AES were significantly lower in the Low EA-PGS + Exacerbating information condition compared to the Low EA-PGS + Mitigating information condition. In Study 2, participants randomized to Control reported significantly higher CS and AES. Pairwise comparisons did not show significant differences in CS and AES. Follow-up pairwise comparisons using Tukey P-value correction did not find significant associations between non-control conditions. Conclusion: These studies replicated the polygenic Pygmalion effect yet were insufficiently powered to detect significant effects of mitigating contextual information. Regardless of contextual information, disappointing EA-PGS results were significantly associated with lower assessments of self-esteem, competence, academic efficacy, and educational potential.

Mesenchymal stem cells (MSCs) have emerged as promising candidates for idiopathic pulmonary fibrosis (IPF) therapy. Increasing the MSC survival rate and deepening the understanding of the behavior of transplanted MSCs are of great significance for improving the efficacy of MSC-based IPF treatment. Therefore, dual-functional Au-based nanoparticles (Au@PEG@PEI@TAT NPs, AuPPT) were fabricated by sequential modification of cationic polymer polyetherimide (PEI), polyethylene glycol (PEG), and transactivator of transcription (TAT) penetration peptide on AuNPs, to co-deliver retinoic acid (RA) and microRNA (miRNA) for simultaneously enhancing MSC survive and real-time imaging tracking of MSCs during IPF treatment. AuPPT NPs, with good drug loading and cellular uptake abilities, could efficiently deliver miRNA and RA to protect MSCs from reactive oxygen species and reduce their expression of apoptosis executive protein Caspase 3, thus prolonging the survival time of MSC after transplantation. In the meantime, the intracellular accumulation of AuPPT NPs enhanced the computed tomography imaging contrast of transplanted MSCs, allowing them to be visually tracked in vivo. This study establishes an Au-based dual-functional platform for drug delivery and cell imaging tracking, which provides a new strategy for MSC-related IPF therapy.

Perilla frutescens L. essential oil (PLEO) has antibacterial and antioxidant properties, which can effectively maintain the quality of fruits and extend their shelf life. In this study, sodium alginate and chitosan were used as wall materials, and PLEO microcapsule powder was used as the core materials to prepare PLEO hydrogel beads. The best results were obtained by using 2%w/v sodium alginate and 1.5%w/v chitosan as wall materials, with a core-to-wall ratio of 2:1 and homogenized for 15 min producing PLEO hydrogel beads with encapsulation efficiency of 82.61 %. For strawberries preservation, PLEO hydrogel beads preservation group had a better effect after 5 d of storage, showing a lower decay rate (15.71 %), better maintaining the hardness of 1.75 kg/cm2, and a weight loss of 3.29 %. Furthermore, organic acids and total phenols were retained more in this group, the number of microorganisms was significantly reduced, and sensory qualities were improved, especially taste and color. This study provides important insights into the application of natural preservatives in the food industry and promotes sustainable practices in food preservation.

In order to further improve the utilization value of Perilla resources, this study used Perilla seed shell extract (PSHE) as raw material, through single factor experiments, the effects of silver nitrate concentration, extract concentration, ultrasonic power, ultrasonic temperature and ultrasonic time on the silver ion reduction rate of Perilla seed shell extract silver nanoparticles (PSHE@AgNPs) were investigated, response surface methodology (RSM) was used to optimize the ultrasonic-assisted preparation of PSHE@AgNPs, the structure and properties of PSHE@AgNPs were characterized by X-ray diffraction, fourier transform infrared spectroscopy, thermogravimetric analysis and transmission electron microscope. The results showed that the optimal PSHE@AgNPs preparation process involved a silver nitrate concentration 15 mmol/L, extract concentration 0.4 g/mL, ultrasonic power 480 W, ultrasonic temperature 80 ℃, and ultrasonic time 7 hours. Under these conditions, the silver ion reduction rate of PSHE@AgNPs reached an impressive 92.37%. X-ray diffraction analysis confirmed the presence of a face-centered cubic structure in PSHE@AgNPs. Fourier-transform infrared spectroscopy showed that there were plant chemical substances on the surface of PSHE@AgNPs，and phenolic compounds were involved in the synthesis of nano-silver. Thermal gravimetric analysis demonstrated the exceptional thermal stability of PSHE@AgNPs，with a major mass loss of 46.74% in the range of 276.7~420.3 ℃. Transmission electron microscopy displayed PSHE@AgNPs as highly dispersed near-spherical particles with an average particle size of 27.97 nm. These research findings would provide valuable theoretical guidance for the ultrasound-assisted green synthesis of PSHE@AgNPs with small particle size, superior dispersion, and remarkable thermal stability in a face-centered cubic structure. Furthermore, these results contribute to advancing the application of PSHE@AgNPs in the fields of biomaterials and medicine.

Abstract Background Acute ischemic stroke is a common neurological disease with a significant financial burden but lacks effective drugs. Hypoxia-inducible factor (HIF) and prolyl hydroxylases (PHDs) participate in the pathophysiological process of ischemia. However, whether FG4592, the first clinically approved PHDs inhibitor, can alleviate ischemic brain injury remains unclear. Methods The infarct volumes and behaviour tests were first analyzed in mice after ischemic stroke with systemic administration of FG4592. The knockdown of HIF-1α and pretreatments of HIF-1/2α inhibitors were then used to verify whether the neuroprotection of FG4592 is HIF-dependent. The targets predicting and molecular docking methods were applied to find other targets of FG4592. Molecular, cell biological and gene knockdown methods were finally conducted to explore the potential neuroprotective mechanisms of FG4592. Results We found that the systemic administration of FG4592 decreased infarct volume and improved neurological defects of mice after transient or permanent ischemia. Meanwhile, FG4592 also activated autophagy and inhibited apoptosis in peri-infarct tissue of mice brains. However, in vitro and in vivo results suggested that the neuroprotection of FG4592 was not classical HIF-dependent. 2-oxoglutarate and iron-dependent oxygenase domain-containing protein 1 (OGFOD1) was found to be a novel target of FG4592 and regulated the Pro-62 hydroxylation in the small ribosomal protein s23 (Rps23) with the help of target predicting and molecular docking methods. Subsequently, the knockdown of OGFOD1 protected the cell against ischemia/reperfusion injury and activated unfolded protein response (UPR) and autophagy. Moreover, FG4592 was also found to activate UPR and autophagic flux in HIF-1α independent manner. Blocking UPR attenuated the neuroprotection, pro-autophagy effect and anti-apoptosis ability of FG4592. Conclusion This study demonstrated that FG4592 could be a candidate drug for treating ischemic stroke. The neuroprotection of FG4592 might be mediated by inhibiting alternative target OGFOD1, which activated the UPR and autophagy and inhibited apoptosis after ischemic injury. The inhibition of OGFOD1 is a novel therapy for ischemic stroke.

Abstract Background KNOTTED1-like homeobox (KNOX) genes, plant-specific homologous box transcription factors (TFs), play a central role in regulating plant growth, development, organ formation, and response to biotic and abiotic stresses. However, a comprehensive genome-wide identification of the KNOX genes in Moso bamboo (Phyllostachys edulis), the fastest growing plant, has not yet been conducted, and the specific biological functions of this family remain unknown. Results The expression profiles of 24 KNOX genes, divided into two subfamilies, were determined by integrating Moso bamboo genome and its transcriptional data. The KNOX gene promoters were found to contain several light and stress-related cis-acting elements. Synteny analysis revealed stronger similarity with rice KNOX genes than with Arabidopsis KNOX genes. Additionally, several conserved structural domains and motifs were identified in the KNOX proteins. The expansion of the KNOX gene family was primarily regulated by tandem duplications. Furthermore, the KNOX genes were responsive to naphthaleneacetic acid (NAA) and gibberellin (GA) hormones, exhibiting distinct temporal expression patterns in four different organs of Moso bamboo. Short Time-series Expression Miner (STEM) analysis and quantitative real-time PCR (qRT-PCR) assays demonstrated that PeKNOX genes may play a role in promoting rapid shoot growth. Additionally, Gene Ontology (GO) and Protein–Protein Interaction (PPI) network enrichment analyses revealed several functional annotations for PeKNOXs. By regulating downstream target genes, PeKNOXs are involved in the synthesis of AUX /IAA, ultimately affecting cell division and elongation. Conclusions In the present study, we identified and characterized a total of 24 KNOX genes in Moso bamboo and investigated their physiological properties and conserved structural domains. To understand their functional roles, we conducted an analysis of gene expression profiles using STEM and RNA-seq data. This analysis successfully revealed regulatory networks of the KNOX genes, involving both upstream and downstream genes. Furthermore, the KNOX genes are involved in the AUX/IAA metabolic pathway, which accelerates shoot growth by influencing downstream target genes. These results provide a theoretical foundation for studying the molecular mechanisms underlying the rapid growth and establish the groundwork for future research into the functions and transcriptional regulatory networks of the KNOX gene family.

No well-established biomarkers are available for the clinical diagnosis of major depressive disorder (MDD). Vitamin D-binding protein (VDBP) is altered in plasma and postmortem dorsolateral prefrontal cortex (DLPFC) tissues of MDD patients. Thereby, the role of VDBP as a potential biomarker of MDD diagnosis was further assessed. Total extracellular vesicles (EVs) and brain cell-derived EVs (BCDEVs) were isolated from the plasma of first-episode drug-naïve or drug-free MDD patients and well-matched healthy controls (HCs) in discovery (20 MDD patients and 20 HCs) and validation cohorts (88 MDD patients and 38 HCs). VDBP level in the cerebrospinal fluid (CSF) from chronic glucocorticoid-induced depressed rhesus macaques or prelimbic cortex from lipopolysaccharide (LPS)-induced depressed mice and wild control groups was measured to evaluate its relationship with VDBP in plasma microglia-derived extracellular vesicles (MDEVs). VDBP was significantly decreased in MDD plasma MDEVs compared to HCs, and negatively correlated with HAMD-24 score with the highest diagnostic accuracy among BCDEVs. VDBP in plasma MDEVs was decreased both in depressed rhesus macaques and mice. A positive correlation of VDBP in MDEVs with that in CSF was detected in depressed rhesus macaques. VDBP levels in prelimbic cortex microglia were negatively correlated with those in plasma MDEVs in depressed mice. The main results suggested that VDBP in plasma MDEVs might serve as a prospective candidate biomarker for MDD diagnosis.

Abstract Background: Epilepsy is a common neurological disorder that affects approximately 60 million people worldwide. Characterized by unpredictable neural electrical activity abnormalities, it results in seizures with varying intensity levels. Electroencephalography (EEG), as a crucial technology for monitoring and predicting epileptic seizures, plays an essential role in improving the quality of life for people with epilepsy. Method: This study introduces an innovative deep learning model, a lightweight triscale yielding convolutional neural network” (LTY-CNN), that is specifically designed for EEG signal analysis. The model integrates a parallel convolutional structure with a multihead attention mechanism to capture complex EEG signal features across multiple scales and enhance the efficiency achieved when processing time series data. The lightweight design of the LTY-CNN enables it to maintain high performance in environments with limited computational resources while preserving the interpretability and maintainability of the model. Results: In tests conducted on the SWEC-ETHZ and CHB-MIT datasets, the LTY-CNN demonstrated outstanding performance. On the SWEC-ETHZ dataset, the LTY-CNN achieved an accuracy of 99.9%, an area under the receiver operating characteristic curve (AUROC) of 0.99, a sensitivity of 99.9%, and a specificity of 98.8%. Furthermore, on the CHB-MIT dataset, it recorded an accuracy of 99%, an AUROC of 0.932, a sensitivity of 99.1%, and a specificity of 93.2%. These results signify the remarkable ability of the LTY-CNN to distinguish between epileptic seizures and nonseizure events. Compared to other existing epilepsy detection classifiers, the LTY-CNN attained higher accuracy and sensitivity. Conclusion: The high accuracy and sensitivity of the LTY-CNN model demonstrate its significant potential for epilepsy management, particularly in terms of predicting and mitigating epileptic seizures. Its value in personalized treatments and widespread clinical applications reflects the broad prospects of deep learning in the health care sector. This also highlights the crucial role of technological innovation in enhancing the quality of life experienced by patients.

Geological remote sensing interpretation plays a pivotal role in the field of regional geological mapping, encompassing the analysis of rock, soil, and water features. However, these geological elements can be obscured by the surrounding geographical environment and can undergo modifications caused by geological activities. The former hinders the effectiveness of satellite remote sensing data, resulting in the invisibility of element features, while the latter leads to the complex distribution of element features and significant spatial variations of geological elements. Consequently, existing deep learning-based models for interpreting geological elements often exhibit limited accuracy. To address these issues, this study proposes the contextually enhanced multiscale feature fusion network for the efficient interpretation of geological elements. First, the context enhancement module is employed to extract abundant feature information and reinforce contextual features, aiming to capture essential features and strengthen their interconnections. Second, the multiscale feature fusion module incorporates the SimAM attention mechanism to adaptively learn features from different channels, emphasizing the feature information that contributes to interpretation results and maximizing the comprehensive and crucial feature information for each element. Extensive experiments demonstrate the superior performance of both the context enhancement module and the multiscale feature fusion module compared to several representative deep learning networks in terms of overall interpretation accuracy on two datasets. The model demonstrated improvements in oPA and mIoU of 2.4% and 2.8%, respectively, on the Landsat 8 dataset, and 3.5% and 3.2%, respectively, on the Sentinel-2 dataset.

This paper presents a varying-parameter finite-time recurrent neural network, called a varying-factor finite-time recurrent neural network (VFFTRNN), which is able to solve the solution of the time-varying Sylvester equation online. The proposed neural network makes the matrix coefficients vary with time and can achieve convergence in a finite time. Apart from this, the performance of the network is better than traditional networks in terms of robustness. It is theoretically proved that the proposed neural network has super-exponential convergence performance. Simulation results demonstrate that this neural network has faster convergence speed and better robustness than the return to zero neural networks and can track the theoretical solution of the time-varying Sylvester equation effectively.

This comprehensive review explores the biological functions of Perilla frutescens seed proteins and peptides, highlighting their significant potential for health and therapeutic applications. This review delves into the mechanisms through which perilla peptides combat oxidative stress and protect cells from oxidative damage, encompassing free radical scavenging, metal chelating, in vivo antioxidant, and cytoprotective activities. Perilla peptides exhibit robust anti-aging properties by activating the Nrf2 pathway, enhancing cellular antioxidant capacity, and supporting skin health through the promotion of keratinocyte growth, maintenance of collagen integrity, and reduction in senescent cells. Additionally, they demonstrate antidiabetic activity by inhibiting α-amylase and α-glucosidase. The cardioprotective effects of perilla peptides are underscored by ACE-inhibitory activities and combat oxidative stress through enhanced antioxidant defenses. Further, perilla peptides contribute to improved gut health by enhancing beneficial gut flora and reinforcing intestinal barriers. In liver, kidney, and testicular health, they reduce oxidative stress and apoptotic damage while normalizing electrolyte levels and protecting against cyclophosphamide-induced reproductive and endocrine disruptions by restoring hormone synthesis. Promising anticancer potential is also demonstrated by perilla peptides through the inhibition of key cancer cell lines, alongside their anti-inflammatory and immunomodulating activities. Their anti-fatigue effects enhance exercise performance and muscle function, while perilla seed peptide nanoparticles show potential for targeted drug delivery. The diverse applications of perilla peptides support their potential as functional food additives and therapeutic agents.

Once the uranium tailings dam collapses, it will cause great harm to the surrounding ecological environment and people’s safety. This study experimentally investigates microbial grouting reinforcement of uranium tailings to advance microbial reinforcement technology and facilitate its large-scale engineering applications. The study simulated original environmental conditions and used tap water to prepare the culture medium and cement without sterilization or pH adjustment. The response surface method was employed to optimize parameters affecting the immobilization of uranium tailings, and the results were verified. The mechanical strength of the immobilized uranium tailings was determined through unconfined compression tests, while their microstructures were analyzed using X-ray diffraction, scanning electron microscopy and computed tomography. The findings indicate that the response surface method optimizes test parameters accurately, with the concentration of the cementation solution and the grouting amount being two main factors influencing the compressive strength of the solidified uranium tailings. Without pH adjustment, sterilization, or slurry modification using tap water, the bacteria−cementation ratio was set at 1, the concentration of the cementation solution was 1.3 mol/L, and the grouting volume was 70 mL. Notably, the strength of the uranium tailings increased 27-fold after seven rounds of grouting compared to the water-only group, and 6-fold compared to the cementation solution-only group. This study contributes to reducing the complexity associated with the application of microbial grouting technology in soil stabilization and provides valuable references for other engineering practices.

As an important member of innate immunity, macrophages show remarkable plasticity and heterogeneity, and play an important role in immune regulation, tissue development, homeostasis of the internal environment and injury repair. However, the excessive activation of macrophages is closely related to the occurrence and development of many diseases. The prenylated flavonoid structure is one of the characteristic structures isolated from Sophora flavescens, with anti-inflammatory, anti-tumor, anti-allergy and other effects. In this study, the effects of (2R)-3β,7,4′-trihydroxy-5-methoxy-8-prenylflavanone (TMP), a prenylated dihydroflavonol, on the polarization and phagocytosis of macrophages were systematically studied. In LPS-induced M1-type macrophages, TMP dose-dependently inhibited the expression of COX-2, iNOS and the secretion of NO, IL-1β, IL-6 and IL-18, showing an inhibitory effect on M1 polarization. Further experiments revealed that it was related to the inhibition of TLR4-related AKT/mTOR, MAPK and NF-κB signaling pathways; in IL-4-induced M2-type macrophages, TMP down-regulated the expression of M2-related Arg1, IL-10, TGF-β, CD206 and CD163, as well as the phosphorylation levels of AKT1 and STAT6. For macrophages in a physiological state, it was very important for cells to return from a stress state to a phenotypic stability in the M0 state. These results indicated that TMP negatively regulated the M1/M2 polarization of macrophages, and made them tend to M0 homeostasis, which might provide new theoretical and data support for explaining the anti-inflammatory immunoregulatory activity of Sophora flavescens.

Grafting is important for increasing the resistance of grapevines to environmental stress, improving fruit quality, and shortening the reproductive period. In this study, ‘Cabernet Sauvignon’ (CS) grafted on the resistant rootstock 140R (CS/140R), self-grafted grapevines of the resistant rootstock 140R (140R/140R), and self-grafted grapevines of CS (CS/CS) were subjected to high-throughput sequencing; small RNA (sRNA) libraries were constructed, and miRNAs responsive to the grafting process were identified. A total of 177 known miRNAs and 267 novel miRNAs were identified. Many miRNAs responsive to the grafting process were significantly down-regulated in CS/140R leaves relative to CS/CS leaves, such as vvi-miR171c, vvi-miR171e, et al., suggesting that the expression of these miRNAs might be affected by grafting. Kyoto Encyclopedia of Genes and Genomes analysis revealed that the differentially expressed miRNAs regulated the expression of genes in the phenylpropanoid synthesis pathway. Grapevine leaves transiently overexpressing vvi-miR171c were assayed, and the expression of the target gene, VvMYB154, and the resveratrol content were decreased, indicating that vvi-miR171c negatively regulates the expression of VvMYB154. In sum, 140R increased the resveratrol content of the scion by grafting, down-regulating the expression of vvi-miR171c. These results provide new information that will aid future analyses of the effects of grafting on the content of secondary metabolites.

The present microbial reinforcement of rock and soil exhibits limitations, such as uneven reinforcement effectiveness and low calcium carbonate generation rate, resulting in limited solidification strength. This study introduces electroosmosis as a standard microbial grouting reinforcement technique and investigates its solidification effects on microbial-reinforced uranium tailings. The most effective electroosmosis effect on uranium tailings occurs under a potential gradient of 1.25 V/cm. The findings indicate that a weak electric field can effectively promote microbial growth and biological activity and accelerate bacterial metabolism. The largest calcium carbonate production occurred under the gradient of 0.5 V/cm, featuring a good crystal combination and the best cementation effect. Staged electroosmosis and electrode conversion efficiently drive the migration of anions and cations. Under electroosmosis, the cohesion of uranium tailings reinforced by microorganisms increased by 37.3% and 64.8% compared to those reinforced by common microorganisms and undisturbed uranium tailings, respectively. The internal friction angle is also improved, significantly enhancing the uniformity of reinforcement and a denser and stronger microscopic structure. This research demonstrates that MICP technology enhances the solidification effects and uniformity of uranium tailings, providing a novel approach to maintaining the safety and stability of uranium tailings dams.