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The seismic performance analysis of research reactor plants is crucial for ensuring the safety of the entire reactor system. This paper analyzes the plant structure seismic performance of the 2WMt Thorium Molten Salt Reactor-Liquid Fuel 1 (TMSR-LF1) at the Shanghai Institute of Applied Physics, Chinese Academy of Sciences under the action of frequent earthquakes, fortification earthquakes, and rare earthquakes was analyzed by finite element software PKPM based on the seismic design method of civil code +1°. On this basis, a comparison was made between the seismic responses of structural pushover analysis and elastoplastic time history analysis under the action of rare earthquakes, and the conservatism of these two commonly used methods for elastoplastic analysis was systematically analyzed. The results indicate that the TMSR-LF1 plant structure exhibits well bearing and deformation capacity. It meets the seismic design goal of “no damage under small earthquakes,” “no unrepairable damage under medium earthquakes,” and “no collapse under large earthquakes (using static pushover analysis),” and the critical regions are entirely within the elastic range. Furthermore, the analysis reveals that the elastoplastic time history analysis method produced a significantly higher seismic response than the pushover analysis method, which indicates the conservativeness of the time history method. Therefore, it is recommended to use the elastoplastic time history analysis method to evaluate the seismic performance of research reactor plants under rare earthquake actions. The research in this paper provides important references for the seismic performance analysis of other Class II research reactor plants.

The elite bull plays an extremely important role in the genetic progression of the dairy cow population. The previous results indicated the potential positive relationship of large scrotal circumference (SC) with improved semen volume, concentration, and motility. In order to improve bull’s semen quantity and quality by selection, it is necessary to estimate the genetic parameters of semen traits and their correlations with other conformation traits such as SC that could be used for an indirect selection. In this study, the genetic parameters of seven semen traits (n = 66,260) and nine conformation traits (n = 3,642) of Holstein bulls (n = 453) were estimated by using the bivariate repeatability animal model with the average information-restricted maximum likelihood (AI-REML) approach. The results showed that the estimated heritabilities of semen traits ranged from 0.06 (total number of motile sperm, TNMS) to 0.37 (percentage of abnormal sperm, PAS) and conformation traits ranged from 0.23 (pin width, PW) to 0.69 (hip height, HH). The highest genetic correlations were found between semen volume per ejaculation (SVPE), semen concentration per ejaculation (SCPE), total number of sperm (TNS), and TNMS traits that were 0.97, 0.98, 1.00, and 0.99, respectively. Phenotypic correlations between SC and SVPE, SCPE, TNS, and TNMS were 0.35, 0.35, 0.48, and 0.42, respectively. In summary, the moderate or high heritability of semen traits indicates that genetic improvement of semen quality by selection is feasible, where SC could be a useful trait for indirect selection or as correlated information to improve semen quantity and production in the practical bull breeding programs.

Determining the optimal generalization operators of city buildings is a crucial step during the building generalization process and an important aspect of realizing cross-scale updating of map data. It is a decision-making behavior of the cartographer that can be learned and simulated using artificial intelligence algorithms. Multi-scale data can provide rich generalization samples to train the determination process. However, previous studies have focused primarily on the intelligent use of each generalization operator separately, neglecting the intelligent scheduling issue between multiple operators when they are used simultaneously. Herein, we propose an improved graph neural network (GNN) called self-neighborhood merged GNN (SNGNN) that selects the optimal generalization operators for different buildings. In SNGNN, node and edge information are passed with different weights through two modules to simulate the effects of a building on itself and the neighborhood on either side. SNGNN has been experimentally validated using sample datasets for Ningbo, China, at 1:10,000 and 1:25,000. The F1-score of the testing dataset was 94.19%, and the classification precision of each operator was ≥87%. Compared with other popular intelligent algorithms, the experimental results for SNGNN revealed better performance in determining the optimal generalization operators.

BackgroundCavernous haemangiomas (CHs) commonly occurred in the skin, subcutaneous tissue, muscles, and liver. Pulmonary cavernous haemangiomas (PCHs) are quite rare and usually present with nonspecific clinical symptoms. When lung cancer patients are complicated with pulmonary cavernous haemangiomas, radiologically, these haemangioma lesions can be easily misinterpreted as intrapulmonary metastases, potentially resulting in misdiagnosis, or missed diagnosis.Case presentationThe present study reported the case of a 53−year−old female patient with pulmonary adenocarcinoma coexisting with multiple PCHs. 18F−FDG-Positron emission tomography-computed tomography (PET-CT) showed an elevated glucose metabolism in the apicoposterior segment of the left upper lobe; however, the other nodules were not hypermetabolic. Percutaneous lung biopsy was performed on the nodule in the apicoposterior segment of the left upper lobe, which were diagnosed as primary adenocarcinoma. Some nodules in the upper left lobe underwent wedge resection by video-assisted thoracic surgery (VATS) and intraoperative frozen section identified as PCHs. Finally, the patient underwent lobectomy of the left upper lobe via VATS, cancerous nodule in the apicoposterior segment of the left upper lobe underwent genetic molecular testing of PCR−Sanger sequencing, suggested EGFR mutation, and patient received treatment with Osimertinib. During the 4−months follow−up, contrast−enhanced CT showed no recurrence of either disease. PCHs are rare benign tumours of the lung, which can lead to misdiagnosis due to their non-specific clinical symptoms and radiological features, especially when they coexist with lung cancer. PCHs is easily misunderstood as metastatic lung cancer, in this case, PET-CT can assist in differentiating benign from malignant. For the cases of early lung cancer complicated with PCHs, lung cancer can be surgically resected, and whether PCHs should be removed or not should be determined according to the size and distribution of the lesions.

Our prophase studies have manifested that the sweet triterpenoid glycoside from the leaves of Cyclocarya paliurus (CPST) effectively improved the disorders of glucolipid metabolism in vitro and in patients. The current purpose was to further detect its mechanisms involved. The results demonstrated that CPST could ameliorate high-fat diet (HFD)-induced insulin resistance (IR), which was linked to reducing HFD-induced mice's body weight, serum glucose (GLUO), triglyceride (TG), total cholesterol (T-CHO) and low-density lipoprotein cholesterol (LDL-C), lowering the area under the oral glucose tolerance curve and insulin tolerance, elevating the percentage of brown adipose, high-density lipoprotein cholesterol (HDL-C), reducing fat droplets of adipocytes in interscapular brown adipose tissue (iBAT) and cross-sectional area of adipocytes. Further studies manifested that CPST obviously downregulated TLR4, MyD88, NLRP3, ASC, caspase-1, cleased-caspase-1, IL-18, IL-1β, TXNIP, and GSDMD protein expressions and p-NF-кB/NF-кB ratio in iBAT. These aforementioned findings demonstrated that CPST ameliorated HFD induced IR by regulating TLR4/NF-κB/NLRP3 signaling pathway, which in turn enhancing insulin sensitivity and glucose metabolism.

Nowadays, more people are choosing to use cloud storage services to save space and reduce costs. To enhance the durability and persistence, users opt to store important data in the form of multiple copies on cloud servers. However, outsourcing data in the cloud means that it is not directly under the control of users, raising concerns about security and integrity. Recent research has found that most existing multicopy integrity verification schemes can correctly perform integrity verification even when multiple copies are stored on the same Cloud Service Provider (CSP), which clearly deviates from the initial intention of users wanting to store files on multiple CSPs. With these considerations in mind, this paper proposes a scheme for synchronizing the integrity verification of copies, specifically focusing on strongly privacy Internet of Things (IoT) electronic health record (EHR) data. First, the paper addresses the issues present in existing multicopy integrity verification schemes. The scheme incorporates the entity Cloud Service Manager (CSM) to assist in the model construction, and each replica file is accompanied with its corresponding homomorphic verification tag. To handle scenarios where replica files stored on multiple CSPs cannot provide audit proof on time due to objective reasons, the paper introduces a novel approach called probability audit. By incorporating a probability audit, the scheme ensures that replica files are indeed stored on different CSPs and guarantees the normal execution of the public auditing phase. The scheme utilizes identity-based encryption (IBE) for the detailed design, avoiding the additional overhead caused by dealing with complex certificate issues. The proposed scheme can withstand forgery attack, replace attack, and replay attack, demonstrating strong security. The performance analysis demonstrates the feasibility and effectiveness of the scheme.

IntroductionThe hierarchical network architecture of the human brain, pivotal to cognition and behavior, can be explored via gradient analysis using restingstate functional MRI data. Although it has been employed to understand brain development and disorders, the impact of aging on this hierarchical architecture and its link to cognitive decline remains elusive.MethodsThis study utilized resting-state functional MRI data from 350 healthy adults (aged 20–85) to investigate the functional hierarchical network using connectome gradient analysis with a cross-age sliding window approach. Gradient-related metrics were estimated and correlated with age to evaluate trajectory of gradient changes across lifespan.ResultsThe principal gradient (unimodal-to-transmodal) demonstrated a significant non-linear relationship with age, whereas the secondary gradient (visual-to-somatomotor) showed a simple linear decreasing pattern. Among the principal gradient, significant age-related changes were observed in the somatomotor, dorsal attention, limbic and default mode networks. The changes in the gradient scores of both the somatomotor and frontal–parietal networks were associated with greater working memory and visuospatial ability. Gender differences were found in global gradient metrics and gradient scores of somatomotor and default mode networks in the principal gradient, with no interaction with age effect.DiscussionOur study delves into the aging trajectories of functional connectome gradient and its cognitive impact across the adult lifespan, providing insights for future research into the biological underpinnings of brain function and pathological models of atypical aging processes.

Introduction: Xinjiang Brown cattle are a famous dual-purpose (dairy-beef) cultivated breed in China that occupy a pivotal position within the cattle breeding industry in Xinjiang, China. However, little information is available on the genetic background of this breed. To fill this research gap, we conducted a whole-genome screen using specific-locus amplified fragment sequencing to examine the genetic structure and diversity of 130 Xinjiang Brown cattle-grazing type (XBG, traditional type) cattle.Methods: A subsequent joint analysis incorporating two ancestral breeds, specifically 19 Brown Swiss (BS) foreign and nine Kazakh (KZ) Chinese cattle, as well as 20 Xinjiang Brown cattle-housing type (XBH) cattle, was used to explore the genetic background of the Xinjiang Brown cattle.Results: The results showed that, after nearly a century of crossbreeding, XBG cattle formed a single population with a stable genetic performance. The genetic structure, genetic diversity, and selection signature analysis of the two ancestral types showed highly different results compared to that of XBH cattle. Local ancestry inference showed that the average proportions of XGB cattle within the BS and KZ cattle lineages were 37.22% and 62.78%, respectively, whereas the average proportions of XBH cattle within the BS and KZ cattle lineages were 95.14% and 4.86%, respectively. Thus, XGB cattle are more representative of all Xinjiang Brown cattle, in line with their breeding history, which involves crossbreeding. Two complementary approaches, fixation index and mean nucleotide diversity, were used to detect selection signals in the four aforementioned cattle breeds. Finally, the analysis of 26 candidate genes in Xinjiang Brown cattle revealed significant enrichment in 19 Gene Ontology terms, and seven candidate genes were enriched in three pathways related to disease resistance (CDH4, SIRPB1, and SIRPα) and the endocrine system (ADCY5, ABCC8, KCNJ11, and KCNMA1). Finally, development of the core SNPs in XBG cattle yielded 8,379 loci.Conclusion: The results of this study detail the evolutionary process of crossbreeding in Xinjiang Brown cattle and provide guidance for selecting and breeding new strains of this species.

Objective: Lipoprotein assembly and secretion in the small intestine are critical for dietary fat absorption. Surfeit locus protein 4 (SURF4) serves as a cargo receptor, facilitating the cellular transport of multiple proteins and mediating hepatic lipid secretion in vivo. However, its involvement in intestinal lipid secretion is not fully understood. In this study, we investigated the role of SURF4 in intestinal lipid absorption. Methods: We generated intestine-specific Surf4 knockout mice and characterized the phenotypes. Additionally, we investigated the underlying mechanisms of SURF4 in intestinal lipid secretion using proteomics and cellular models. Results: We unveiled that SURF4 is indispensable for apolipoprotein transport and lipoprotein secretion. Intestine-specific Surf4 knockout mice exhibited ectopic lipid deposition in the small intestine and hypolipidemia. Deletion of SURF4 impeded the transport of apolipoprotein A1 (ApoA1), proline-rich acidic protein 1 (PRAP1), and apolipoprotein B48 (ApoB48) and hindered the assembly and secretion of chylomicrons and high-density lipoproteins. Conclusions: SURF4 emerges as a pivotal regulator of intestinal lipid absorption via mediating the secretion of ApoA1, PRAP1 and ApoB48.

Pedestrian trajectory prediction aims to use observed human historical trajectories and surrounding environmental information to predict the future position of the target pedestrian, which has important application value in reducing collision risks for autonomous vehicles in social interactions.However, traditional model-driven pedestrian trajectory prediction methods are difficult to predict pedestrian trajectories in complex and highly dynamic scenes.In contrast, datadriven pedestrian trajectory prediction methods rely on large-scale datasets and can better capture and model more complex pedestrian interaction relationships, thereby achieving more accurate pedestrian trajectory prediction results, and have become a research hotspot in fields such as autonomous driving, robot navigation and video surveillance.In order to macroscopically grasp the research status and key issues of pedestrian trajectory prediction methods, We started with the classification of pedestrian trajectory prediction technology and methods.First, the research progress of existing pedestrian trajectory prediction methods were elaborated and the current key issues and challenges were summarized.Second, according to the modeling differences of pedestrian trajectory prediction models, existing methods were divided into model-driven and data-driven pedestrian trajectory prediction methods, and the advantages, disadvantages and applicable scenarios of different methods were summarized.Then, the mainstream datasets used in pedestrian trajectory prediction tasks were summarized and the performance indicators of different algoriths were compared.Finally, the future development direction of pedestrian trajectory prediction was prospected.

Cybersecurity originated from the theoretical testing of computer networks.With the development of information and communication technology (ICT), cybersecurity threats present the ＆quot;4V＆quot; characteristics of high source volume, many varieties, process not visibility, and high-value losses.This is accompanied by a double change in the formation and complexity of cyberspace.With the recent rising of metaverse, the human-centered cyberspace has the ability to map the real world and exposes the real world to cybersecurity threats.However, cybersecurity supervision does not keep up with the changes in cyberspace and still seeks solutions in cyberspace.A parallel supervision system for cybersecurity, ParaDefender was introduced, which was constructed based on artificial systems, computational experiments and parallel execution of ACP method to improve the current dilemma of cybersecurity supervision from the perspective of cyber-physicalsocial systems (CPSS).We demonstrated provided the application solutions of ParaDefender in telecom anti-fraud and industrial IoT scenarios and inspiration and reference for cybersecurity supervision in different fields.

Although deep learning methods have achieved better results than traditional trajectory prediction algorithms, there are still problems such as information loss, interaction and uncertainty difficulties in modelling, and lack of interpretability of predictions when implementing multimodal high-precision prediction for autonomous vehicles in heterogeneous, highly dynamic and complex changing environments.The newly developed Transformer's long-range modelling capability and parallel computing ability make it a great success not only in the field of natural language processing, but also in solving the above problems when extended to the task of multimodal trajectory prediction for autonomous driving.Based on this, the aim of this paper is to provide a comprehensive summary and review of past deep neural network-based approaches, in particular the Transformer-based approach.The advantages of Transformer over traditional sequential network, graphical neural network and generative model were also analyzed and classified in relation to existing challenges, simultaneously.Transformer models can be better applied to multimodal trajectory prediction tasks, and that such models have better generalisation and interpretability.Finally, the future directions of multimodal trajectory prediction were presented.

Here, the complete chloroplast genome sequence of Zingiber teres is described using MGI paired-end sequencing. The genome is 163,428 bp in length and contains a small single-copy region (SSC) of 15,782 bp, a large single-copy region (LSC) of 88,142 bp, and two inverted repeat (IR) regions of 29,752 bp. The overall GC content is 36.1%, and the GC content of the IR regions is 41.1%, which is higher than that of both the LSC region (33.8%) and SSC region (29.5%). The genome of Z. teres contains 133 complete genes, including 88 protein-coding genes (79 protein-coding gene species), 38 tRNA genes (28 tRNA species), and 8 rRNA genes (four rRNA species). Maximum likelihood phylogenetic analysis yielded a well-resolved tree of the genus Zingiber, and Z. teres and Zingiber mioga were sister species in this tree. The development of DNA barcodes could aid the identification of Zingiber species.

Biomass valorization by photoreforming approach provides a promising and alternative strategy to generate value-added chemicals and fuels. In this work, we demonstrate the selective production of lactic acid from glucose photoreforming over pristine graphitic carbon nitride (g-C3N4) photocatalyst. Control experiments screen the best condition for the highest yield of lactic acid, including modulating pH, catalyst loading, and reaction time. 100% glucose conversion is achieved along with almost 100% lactic acid yield under the optimized condition. Density functional theory (DFT) calculations reveal that the rate-determining step (RDS) of the overall reaction on g-C3N4 is the conversion of pyruvaldehyde, where an electron transfer takes place. This present work provides experimental insights and theoretical understanding for selective lactic acid production from biomass photoreforming.

Abstract Background Phosphatase and tensin homolog deleted on chromosome 10 (PTEN) signaling has been known to play a critical role in maintaining cellular and tissue homeostasis, which also has an essential role in the inflammatory response. However, it remains unidentified whether and how the macrophage PTEN may govern the innate immune signaling stimulator of interferon genes (STING) mediated inflammation and hepatocyte necroptosis in APAP-induced liver injury (AILI). Methods Myeloid-specific PTEN knockout (PTENM−KO) and floxed PTEN (PTENFL/FL) mice were treated with APAP (400 mg/kg) or PBS. In a parallel in vitro study, bone marrow-derived macrophages (BMMs) were isolated from these conditional knockout mice and transfected with CRISPR/Cas9-mediated Notch1 knockout (KO) or CRISPR/Cas9-mediated STING activation vector followed by LPS (100 ng/ml) stimulation. Results Here, we report that myeloid-specific PTEN knockout (PTENM−KO) mice were resistant to oxidative stress-induced hepatocellular injury with reduced macrophage/neutrophil accumulation and proinflammatory mediators in AILI. PTENM−KO increased the interaction of nuclear Notch intracellular domain (NICD) and nuclear factor (erythroid-derived 2)-like 2 (NRF2) in the macrophage nucleus, reducing reactive oxygen species (ROS) generation. Mechanistically, it is worth noting that macrophage NICD and NRF2 co-localize within the nucleus under inflammatory conditions. Additionally, Notch1 promotes the interaction of immunoglobulin kappa J region (RBPjκ) with NRF2. Disruption of the Notch1 signal in PTEN deletion macrophages, reduced RBPjκ and NRF2 binding, and activated STING signaling. Moreover, PTENM−KO macrophages with STING activated led to ROS generation and TNF-α release, resulting in hepatocyte necroptosis upon co-culture with primary hepatocytes. Conclusions Our findings demonstrate that the macrophage PTEN-NICD/NRF2-STING axis is critical to regulating oxidative stress-induced liver inflammation and necroptosis in AILI and implies the therapeutic potential for managing sterile liver inflammation. Video Abstract Graphical Abstract

Abstract Phenylketonuria (PKU), an autosomal recessive disorder caused by pathogenic variants in the phenylalanine hydroxylase (PAH) gene, results in the accumulation of blood phenylalanine (Phe) to neurotoxic levels. Current dietary and medical treatments are chronic and reduce, rather than normalize, blood Phe levels. Among the most frequently occurring PAH variants in PKU patients is the P281L (c.842C>T) variant. Using a CRISPR prime-edited hepatocyte cell line and a humanized PKU mouse model, we demonstrate efficient in vitro and in vivo correction of the P281L variant with adenine base editing. With the delivery of ABE8.8 mRNA and either of two guide RNAs in vivo using lipid nanoparticles (LNPs) in humanized PKU mice, we observe complete and durable normalization of blood Phe levels within 48 h of treatment, resulting from corrective PAH editing in the liver. These studies nominate a drug candidate for further development as a definitive treatment for a subset of PKU patients.

Abstract Sperm is essential for successful artificial insemination in dairy cattle, and its quality can be influenced by both epigenetic modification and epigenetic inheritance. The bovine germline differentiation is characterized by epigenetic reprogramming, while intergenerational and transgenerational epigenetic inheritance can influence the offspring’s development through the transmission of epigenetic features to the offspring via the germline. Therefore, the selection of bulls with superior sperm quality for the production and fertility traits requires a better understanding of the epigenetic mechanism and more accurate identifications of epigenetic biomarkers. We have comprehensively reviewed the current progress in the studies of bovine sperm epigenome in terms of both resources and biological discovery in order to provide perspectives on how to harness this valuable information for genetic improvement in the cattle breeding industry.

To explore the stress and deformation responses, as well as the failure characteristics of the shield tunnel segment of Hangzhou Metro under the influences of pit excavation and other surrounding projects, a self-developed “shield tunnel segment hydraulic loading system” was used to carry out full-scale loading tests on the three-ring staggered assembled segments. The structural performances and failure process of the tunnel segment under step-by-step asymmetric unloading were studied. A safety index was proposed to describe the bearing capacity of the segment. Next, a finite element model (FEM) was established to analyze the bearing capacity of segment using the test results. Finally, the effect of reinforcement with a steel plate on the deformation and bearing capacity of the segment was analyzed. The results showed that under asymmetric unloading, the peak value and amplitude of the bending moment on the near unloading side converged with a greater value than those on the far side. The concrete internal force exhibited a directional transformation at different load stages. Cracks first appeared at the 180° inner arc surface of the bottom standard block and then expanded to both sides, while the rate of crack propagation of the outer arc surface was relatively lower. The bearing capacity of the segments can be evaluated by the combination of the factors, e.g. the residual bearing capacity coefficient, moment transfer coefficient, and characterization coefficient. The segments approaching failure can facilitate the increase in the residual bearing capacity coefficient by more than 50%. This can provide guidance for the service assessment of metro tunnel operations.

Carbon fiber reinforced polyetheretherketone (CFRPEEK) possesses a similar elastic modulus to that of human cortical bone and is considered as a promising candidate to replace metallic implants. However, the bioinertness and deficiency of antibacterial activities impede its application in orthopedic and dentistry. In this work, titanium plasma immersion ion implantation (Ti-PIII) is applied to modify CFRPEEK, achieving unique multi-hierarchical nanostructures and active sites on the surface. Then, hybrid polydopamine (PDA)@ZnO-EDN1 nanoparticles (NPs) are introduced to construct versatile surfaces with improved osteogenic and angiogenic properties and excellent antibacterial properties. Our study established that the modified CFRPEEK presented favorable stability and cytocompatibility. Compared with bare CFRPEEK, improved osteogenic differentiation of rat mesenchymal stem cells (BMSCs) and vascularization of human umbilical vein endothelial cells (HUVECs) are found on the functionalized surface due to the zinc ions and EDN1 releasing. In vitro bacteriostasis assay confirms that hybrid PDA@ZnO NPs on the functionalized surface provided an effective antibacterial effect. Moreover, the rat infected model corroborates the enhanced antibiosis and osteointegration of the functionalized CFRPEEK. Our findings indicate that the multilevel nanostructured PDA@ZnO-EDN1 coated CFRPEEK with enhanced antibacterial, angiogenic, and osteogenic capacity has great potential as an orthopedic/dental implant material for clinical application.

In the present study, MXene-reinforced Mg matrix composites were manufactured via the electrostatic self-assembly protocol and spark plasma sintering (SPS) process to develop lightweight materials with high mechanical performance. Uniform dispersion of MXene sheets was achieved in MXene/AZ91 composites. A unique interfacial structure was confirmed in these composites, which exhibited an ultrafine MgO interlayer (grain size of ∼10 nm) coherently incorporated or intercalated into MXene layers. The unique interfacial structure contributed to robust interfacial bonding between MXene sheets and Mg matrix, resulting in a substantial mechanical performance enhancement. The yield strength of 325.3 ± 7.9 MPa and elongation of 8.8 ± 0.2% were achieved in 0.3vol% MXene/AZ91 composites, showing a significantly high strengthening efficiency of 159.1 without sacrificing ductility. Quantitatively investigation of strengthening behavior manifested that the load-transfer effect was the primary strengthening mechanism in MXene/AZ91 composites, and the simulated strength was well-matched with experimental results due to the special interfacial structure and excellent dispersion properties. This study could offer significant guidance for developing novel lightweight materials with high mechanical performance for structural applications.

Abstract Dental resin composites (DRCs) are popular materials for repairing caries or dental defect, requiring excellent properties to cope with the complex oral environment. Filler/resin interface interaction has a significant impact on the physicochemical/biological properties and service life of DRCs. Various chemical and physical modification methods on filler/resin interface have been introduced and studied, and the physical micromechanical interlocking caused by the modification of fillers morphology and structure is a promising method. This paper firstly introduces the composition and development of DRCs, then reviews the chemical and physical modification methods of the filler/resin interface, mainly discusses the interface micromechanical interlocking structures and their enhancement mechanism for DRCs, finally give a summary on the existing problems and development potential.

Previous studies of the effects of elevated CO2 (eCO2) concentrations and heavy metal stress conditions on plant growth and physiology have mostly focused on crops rather than vegetables. In this study, we investigated the effects of Cd stress on the growth and antioxidant system of pak choi (Brassica rapa L.), water spinach (Ipomoea aquatica Forssk.), cherry radish (Raphanus raphanistrum subsp. sativus (L.) Domin) and pepper (Capsicum annuum L.) growing in pots under ambient CO2 (aCO2) or eCO2 conditions. In general, Cd stress reduced plant biomass and SPAD values under aCO2 and eCO2 conditions; however, the reduction was smaller under eCO2. Cd stress significantly reduced vegetable superoxide dismutase (SOD) and catalase (CAT) activities under both aCO2 and eCO2 conditions; however, the decrease in cherry radish and pepper peroxidase and SOD activities and in pak choi SOD and CAT activities was significantly less under eCO2. The Cd content of the edible parts of pak choi, water spinach and pepper was significantly lower under eCO2 than under aCO2. Our data suggest that eCO2 concentrations could be beneficial for the growth of some vegetables and reduce the Cd content.

Abstract Obstructive sleep apnea syndrome (OSAS) is a common breathing disorder in sleep in which the airways narrow or collapse during sleep, causing obstructive sleep apnea. The prevalence of OSAS continues to rise worldwide, particularly in middle-aged and elderly individuals. The mechanism of upper airway collapse is incompletely understood but is associated with several factors, including obesity, craniofacial changes, altered muscle function in the upper airway, pharyngeal neuropathy, and fluid shifts to the neck. The main characteristics of OSAS are recurrent pauses in respiration, which lead to intermittent hypoxia (IH) and hypercapnia, accompanied by blood oxygen desaturation and arousal during sleep, which sharply increases the risk of several diseases. This paper first briefly describes the epidemiology, incidence, and pathophysiological mechanisms of OSAS. Next, the alterations in relevant signaling pathways induced by IH are systematically reviewed and discussed. For example, IH can induce gut microbiota (GM) dysbiosis, impair the intestinal barrier, and alter intestinal metabolites. These mechanisms ultimately lead to secondary oxidative stress, systemic inflammation, and sympathetic activation. We then summarize the effects of IH on disease pathogenesis, including cardiocerebrovascular disorders, neurological disorders, metabolic diseases, cancer, reproductive disorders, and COVID-19. Finally, different therapeutic strategies for OSAS caused by different causes are proposed. Multidisciplinary approaches and shared decision-making are necessary for the successful treatment of OSAS in the future, but more randomized controlled trials are needed for further evaluation to define what treatments are best for specific OSAS patients.

Abstract Peritendinous adhesion formation (PAF) can substantially limit the range of motion of digits. However, the origin of myofibroblasts in PAF tissues is still unclear. In this study, we found that the concentration of active TGF-β1 and the numbers of macrophages, mesenchymal stromal cells (MSCs), and myofibroblasts in human and mouse adhesion tissues were increased. Furthermore, knockout of TGF-β1 in macrophages or TGF-β1R2 in MSCs inhibited PAF by reducing MSC and myofibroblast infiltration and collagen I and III deposition, respectively. Moreover, we found that MSCs differentiated into myofibroblasts to form adhesion tissues. Systemic injection of the TGF-β–neutralizing antibody 1D11 during the granulation formation stage of PAF significantly reduced the infiltration of MSCs and myofibroblasts and, subsequently, PAF. These results suggest that macrophage-derived TGF-β1 recruits MSCs to form myofibroblasts in peritendinous adhesions. An improved understanding of PAF mechanisms could help identify a potential therapeutic strategy.

Abstract Polycystic ovary syndrome (PCOS) is a common endocrine disorder in women of childbearing age. The etiology of PCOS is multifactorial, and current treatments for PCOS are far from satisfactory. Recently, an imbalanced autonomic nervous system (ANS) with sympathetic hyperactivity and reduced parasympathetic nerve activity (vagal tone) has aroused increasing attention in the pathogenesis of PCOS. In this paper, we review an innovative therapy for the treatment of PCOS and related co-morbidities by targeting parasympathetic modulation based on non-invasive transcutaneous auricular vagal nerve stimulation (ta-VNS). In this work, we present the role of the ANS in the development of PCOS and describe a large number of experimental and clinical reports that support the favorable effects of VNS/ta-VNS in treating a variety of symptoms, including obesity, insulin resistance, type 2 diabetes mellitus, inflammation, microbiome dysregulation, cardiovascular disease, and depression, all of which are also commonly present in PCOS patients. We propose a model focusing on ta-VNS that may treat PCOS by (1) regulating energy metabolism via bidirectional vagal signaling; (2) reversing insulin resistance via its antidiabetic effect; (3) activating anti-inflammatory pathways; (4) restoring homeostasis of the microbiota-gut-brain axis; (5) restoring the sympatho-vagal balance to improve CVD outcomes; (6) and modulating mental disorders. ta-VNS is a safe clinical procedure and it might be a promising new treatment approach for PCOS, or at least a supplementary treatment for current therapeutics.

Abstract Mapping tumor metabolic remodeling and their spatial crosstalk with surrounding non-tumor cells can fundamentally improve our understanding of tumor biology, facilitates the designing of advanced therapeutic strategies. Here, we present an integration of mass spectrometry imaging-based spatial metabolomics and lipidomics with microarray-based spatial transcriptomics to hierarchically visualize the intratumor metabolic heterogeneity and cell metabolic interactions in same gastric cancer sample. Tumor-associated metabolic reprogramming is imaged at metabolic-transcriptional levels, and maker metabolites, lipids, genes are connected in metabolic pathways and colocalized in the heterogeneous cancer tissues. Integrated data from spatial multi-omics approaches coherently identify cell types and distributions within the complex tumor microenvironment, and an immune cell-dominated “tumor-normal interface” region where tumor cells contact adjacent tissues are characterized with distinct transcriptional signatures and significant immunometabolic alterations. Our approach for mapping tissue molecular architecture provides highly integrated picture of intratumor heterogeneity, and transform the understanding of cancer metabolism at systemic level.

Abstract Background Felid herpesvirus 1 (FHV-1) is a major pathogenic agent of upper respiratory tract infections and eye damage in felines worldwide. Current FHV-1 vaccines offer limited protection of short duration, and therefore, do not reduce the development of clinical signs or the latency of FHV-1. Methods To address these shortcomings, we constructed FHV ∆gIgE-eGFP, FHV ∆TK mCherry, and FHV ∆gIgE/TK eGFP-mCherry deletion mutants (ΔgI/gE, ΔTK, and ΔgIgE/TK, respectively) using the clustered regularly interspaced palindromic repeats (CRISPR)/CRISP-associated protein 9 (Cas9) system (CRISPR/Cas9), which showed safety and immunogenicity in vitro. We evaluated the safety and efficacy of the deletion mutants administered with intranasal (IN) and IN + subcutaneous (SC) vaccination protocols. Cats in the vaccination group were vaccinated twice at a 4-week interval, and all cats were challenged with infection 3 weeks after the last vaccination. The cats were assessed for clinical signs, nasal shedding, and virus-neutralizing antibodies (VN), and with postmortem histological testing. Results Vaccination with the gI/gE-deleted and gI/gE/TK-deleted mutants was safe and resulted in significantly lower clinical disease scores, fewer pathological changes, and less nasal virus shedding after infection. All three mutants induced virus-neutralizing antibodies after immunization. Conclusions In conclusion, this study demonstrates the advantages of FHV-1 deletion mutants in preventing FHV-1 infection in cats.

Abstract The purpose of this retrospective, longitudinal study is to evaluate the relationship between MD slope from visual field tests collected over a short period of time (2 years) and the current United States’ Food and Drug Administration (FDA) recommended endpoints for visual field outcomes. If this correlation is strong and highly predictive, clinical trials employing MD slopes as primary endpoints could be employed in neuroprotection clinical trials with shorter duration and help expedite the development of novel IOP-independent therapies. Visual field tests of patients with or suspected glaucoma were selected from an academic institution and evaluated based on two functional progression endpoints: (A) five or more locations worsening by at least 7 dB, and (B) at least five test locations based upon the GCP algorithm. A total of 271 (57.6%) and 278 (59.1%) eyes reached Endpoints A and B, respectively during the follow up period. The median (IQR) MD slope of eyes reaching vs. not reaching Endpoint A and B were −1.19 (−2.00 to −0.41) vs. 0.36 (0.00 to 1.00) dB/year and −1.16 (−1.98 to −0.40) vs. 0.41 (0.02 to 1.03) dB/year, respectively (P

Abstract Current biotechnologies can simultaneously measure multiple high-dimensional modalities (e.g., RNA, DNA accessibility, and protein) from the same cells. A combination of different analytical tasks (e.g., multi-modal integration and cross-modal analysis) is required to comprehensively understand such data, inferring how gene regulation drives biological diversity and functions. However, current analytical methods are designed to perform a single task, only providing a partial picture of the multi-modal data. Here, we present UnitedNet, an explainable multi-task deep neural network capable of integrating different tasks to analyze single-cell multi-modality data. Applied to various multi-modality datasets (e.g., Patch-seq, multiome ATAC + gene expression, and spatial transcriptomics), UnitedNet demonstrates similar or better accuracy in multi-modal integration and cross-modal prediction compared with state-of-the-art methods. Moreover, by dissecting the trained UnitedNet with the explainable machine learning algorithm, we can directly quantify the relationship between gene expression and other modalities with cell-type specificity. UnitedNet is a comprehensive end-to-end framework that could be broadly applicable to single-cell multi-modality biology. This framework has the potential to facilitate the discovery of cell-type-specific regulation kinetics across transcriptomics and other modalities.

The identification of the high‐efficiency and non‐invasive biomarkers for hepatocellular carcinoma (HCC) detection is urgently needed. This study aims to screen out potential autoantibodies to tumor‐associated antigens (TAAbs) and to assess their diagnostic value for HCC. Fifteen potential TAAbs were screened out from the Human Proteome Microarray by 30 HCC sera and 22 normal control sera, of which eight passed multiple‐stage validations by ELISA with a total of 1625 human serum samples from normal controls (NCs) and patients with HCC, liver cirrhosis, chronic hepatitis B, gastric cancer, esophageal cancer, and colorectal cancer. Finally, an immunodiagnostic model including six TAAbs (RAD23A, CAST, RUNX1T1, PAIP1, SARS, PRKCZ) was constructed by logistic regression, and yielded the area under curve (AUC) of 0.835 and 0.788 in training and validation sets, respectively. The serial serum samples from HCC model mice were tested to explore the change in TAAbs during HCC formation, and an increasing level of autoantibodies was observed. In conclusion, the panel of six TAAbs can provide potential value for HCC detection, and the strategy to identify novel serological biomarkers can also provide new clues in understanding immunodiagnostic biomarkers.

Abstract The application of cyber‐physical systems (CPSs) in many areas is threatened by its embedded structure. This paper considers the design of an adaptive controller for linear CPSs against deception attacks. Specifically, a corrective signal is designed to suppress or offset the impact of sensor and actuator attacks, especially when the controller and the correction signal are also attacked. First, an adaptive controller is developed for time‐invariant deception attacks and further extended to time‐varying deception attacks. In each case, state‐independent sensor attacks and input‐independent actuator attacks, as well as state‐dependent sensor attacks and input‐dependent actuator attacks, are discussed. For the considered closed‐loop system with time‐invariant state‐dependent sensor attacks and input‐dependent actuator attacks, the controller the authors developed ensures the asymptotic stability of the systems. For the other three cases of the corresponding system, the controllers are also designed, which ensures uniform ultimate boundedness. Finally, several numerical examples are given to explain the availability of our control scheme.

Nickel powders of nominal sizes (i.e., 50 nm, 300 nm, and 2 μm) were pre-coated on copper substrates and then subjected to laser shock processing (LSP) for producing nickel coating. The shockwave consolidation behavior, microstructure, and bonding performance were investigated as a function of particle size. Results indicated that nano-coating had better surface quality, decreased microstructural defects (pores and cracks), and higher bonding strength (approximately twice the hardness value) than its micro-counterpart. Microstructure analysis revealed that nano/submicron particles were consolidated by a mixed solid-liquid sintering behavior, whereas micron particles were consolidated only by solid-state sintering under laser shock. A mixed microstructure of nanocoating was obtained, consisting of solid-state atomic bonds between solid-state sintered particles and amorphous phases between liquid-phase sintered particles. After LSP, the cold shock characteristics of LSP could not only reduce the overall grain growth and oxidation of nano coating, but also induce fine nanocrystalline at the inter-particle interface of the micron coating by dynamic recrystallization.

Abstract Serine proteases are among the most important biological additives in various industries such as detergents, leather, animal feed and food. A serine protease gene, Fgapt4, from Fusarium graminearum 2697 was identified, cloned and expressed in Pichia pastoris. The optimal pH and temperature of FgAPT4 were 8.5 and 40°C, respectively. The relative activity was >30% even at 10°C. It had a wide range of pH stability (4.0–12.0) and detergent compatibility. To improve the catalytic activity, a strategy combining molecular docking and evolutionary analysis was adopted. Twelve amino acid residue sites and three loops (A, B and C) were selected as potential hot spots that might play critical roles in the enzyme's functional properties. Twenty‐eight mutants targeting changes in individual sites or loops were designed, and mutations with good performance were combined. The best mutant was FgAPT4‐M3 (Q70N/D142S/A143S/loop C). The specific activity and catalytic efficiency of FgAPT4‐M3 increased by 1.6 (1008.5 vs. 385.9 U/mg) and 2.2‐fold (3565.1 vs. 1106.3/s/mM), respectively. Computational analyses showed that the greater flexibility of the substrate pocket may be responsible for the increased catalytic activity. In addition, its application in detergents indicated that FgAPT4‐M3 has great potential in washing.

Abstract Background Myeloid neoplasms (MN) tend to relapse and deteriorate. Exploring the genomic mutation landscape of MN using next‐generation sequencing (NGS) is a great measure to clarify the mechanism of oncogenesis and progression of MN. Methods This multicenter retrospective study investigated 303 patients with MN using NGS from 2019 to 2021. The characteristics of the mutation landscape in the MN subgroups and the clinical value of gene variants were analyzed. Results At least one mutation was detected in 88.11% of the patients (267/303). TET2 was the most common mutation in the cohort, followed by GATA2, ASXL1, FLT3, DNMT3A, and TP53. Among patients with myeloid leukemia (ML), multivariate analysis showed that patients aged ≥60 years had lower overall survival (OS, p = 0.004). Further analysis showed TET2, NPM1, SRSF2, and IDH1 gene mutations, and epigenetic genes (p

Abstract Background Diabetes is a chronic non-communicable disease that causes a substantial economic burden on diabetic suffers and their households. The aim of this study was to explore the prevalence, equity, and determinants of catastrophic health expenditure (CHE) among households with people with diabetes in Northwest China. Methods A total of 3,000 households were included in the 6th Health services survey in Gansu Province, China of which 270 households with people with diabetes. The equity of CHE was evaluated by concentration curve and concentration index (CI). We adopted the Pareto chart to analyze the main economic intervals of the occurrence of CHE. Finally, we combined the decision tree and logistic model and analyzed the determinants of the occurrence of CHE. Results The incidence of CHE at 15%, 25% and 40% were 75.19%, 58.89% and 35.19%, respectively. CHE tended to occur in households with a lower economic level, with the phenomenon being more pronounced at Z = 40%. The Pareto chart showed that households in the group with an annual per capita income of 0–740 USD (0–5,000 Chinese Yuan) were most likely to experience CHE. Both decision tree and logistic models suggested that economic level, comorbidities, and small household size were potential risk factors. In addition, the decision tree model also suggested the interaction between the influencing factor of health checks in the past 12 months and the number of chronic diseases. Conclusions In summary, Households with people with diabetes were more likely to incur CHE. It is essential to focus on low- and middle-income households with people with diabetes, strengthen the management of patients with diabetes, and provide timely health interventions to reduce the occurrence of chronic comorbidity and the risk of CHE in households.

Abstract Wildlife is reservoir of emerging viruses. Here we identified 27 families of mammalian viruses from 1981 wild animals and 194 zoo animals collected from south China between 2015 and 2022, isolated and characterized the pathogenicity of eight viruses. Bats harbor high diversity of coronaviruses, picornaviruses and astroviruses, and a potentially novel genus of Bornaviridae. In addition to the reported SARSr-CoV-2 and HKU4-CoV-like viruses, picornavirus and respiroviruses also likely circulate between bats and pangolins. Pikas harbor a new clade of Embecovirus and a new genus of arenaviruses. Further, the potential cross-species transmission of RNA viruses (paramyxovirus and astrovirus) and DNA viruses (pseudorabies virus, porcine circovirus 2, porcine circovirus 3 and parvovirus) between wildlife and domestic animals was identified, complicating wildlife protection and the prevention and control of these diseases in domestic animals. This study provides a nuanced view of the frequency of host-jumping events, as well as assessments of zoonotic risk.

Abstract Zinc‐based batteries are a very promising class of next‐generation electrochemical energy storage systems, with high safety, eco‐friendliness, abundant resources, and the absence of rigorous manufacturing conditions. However, practical applications of zinc‐based rechargeable batteries are impeded by the low Coulombic efficiency, inferior cyclability, and poor rate capability, due to the instability of zinc anode. Herein, effective strategies for dendrite‐free zinc anode are symmetrically reviewed, especially highlighting specific mechanisms, delicate design of electrode and current collectors, controlled electrode|electrolyte interface, ameliorative electrolytes, and advanced separators design. First, the particular mechanisms of dendrites formation and the associated fundamentals of the stable Zn metal anodes are presented elaborately. Then, recent key strategies for dendrites prevention and hydrogen evolution reaction suppression are categorized, discussed, and analyzed in detail in view of the electrodes, electrolytes, and separators. Finally, the challenging perspectives and major directions of stable zinc anodes are briefly discussed for further industrialization and commercialization of zinc‐based rechargeable batteries.

Abstract Purely organic phosphorescent materials with dynamically tunable optical properties and persistent luminescent characteristics enable more novel applications in intelligent optoelectronics. Herein, we reported a concise and universal strategy to achieve photoactivated ultralong phosphorescence at room temperature through stereo-hindrance engineering. Such dynamically photoactivated phosphorescence behavior was ascribed to the suppression of non-radiative transitions and improvement of spin-orbit coupling (SOC) as the variation of the distorted molecular conformation by the synergistic effect of electrostatic repulsion and steric hindrance. This “trainable” phosphorescent behavior was first proposed to mimic biological synaptic plasticity, especially for unique experience-dependent plasticity, by the manipulation of pulse intensity and numbers. This study not only outlines a principle to design newly dynamic phosphorescent materials, but also broadens their utility in intelligent sensors and robotics.

Abstract Background There are a large number of infertile couples in China, but its treatment is notoriously expensive and not currently covered by insurance. The utility of preimplantation genetic testing for aneuploidy as an adjunct to in vitro fertilization has been debated. Objective To investigate the cost-effectiveness of preimplantation genetic testing for aneuploidy (PGT-A) versus conventional technology in in vitro fertilization (IVF) from the perspective of the healthcare system in China. Methods Following the exact steps in the IVF protocol, a decision tree model was developed, based on the data from the CESE-PGS trial and using cost scenarios for IVF in China. The scenarios were compared for costs per patient and cost-effectiveness. One-way sensitivity analysis and probabilistic sensitivity analysis were performed to confirm the robustness of the findings. Main outcome measures Costs per live birth, Costs per patient, Incremental cost-effectiveness for miscarriage prevention. Results The average costs per live birth of PGT-A were estimated as ¥39230.71, which is about 16.8% higher than that of the conventional treatment. Threshold analysis revealed that PGT-A would need to increase the pregnancy rate of 26.24–98.24% or a cost reduction of ¥4649.29 to ¥1350.71 to achieve the same cost-effectiveness. The incremental costs per prevented miscarriage was approximately ¥45600.23. The incremental cost-effectiveness for miscarriage prevention showed that the willingness to pay would be ¥43422.60 for PGT-A to be cost-effective. Conclusion The present cost-effectiveness analysis demonstrates that embryo selection with PGT‑A is not suitable for routine applications from the perspective of healthcare providers in China, given the cumulative live birth rate and the high costs of PGT‑A.

Abstract Background Understanding the evolutionary forces related to climate changes that have been shaped genetic variation within species has long been a fundamental pursuit in biology. In this study, we generated whole-genome sequence (WGS) data from 65 cross-bred and 45 Mongolian cattle. Together with 62 whole-genome sequences from world-wide cattle populations, we estimated the genetic diversity and population genetic structure of cattle populations. In addition, we performed comparative population genomics analyses to explore the genetic basis underlying variation in the adaptation to cold climate and immune response in cross-bred cattle located in the cold region of China. To elucidate genomic signatures that underlie adaptation to cold climate, we performed three statistical measurements, fixation index (FST), log2 nucleotide diversity (θπ ratio) and cross population composite likelihood ratio (XP-CLR), and further investigated the results to identify genomic regions under selection for cold adaptation and immune response-related traits. Results By generating WGS data, we investigated the population genetic structure and phylogenetic relationship of studied cattle populations. The results revealed clustering of cattle groups in agreement with their geographic distribution. We detected noticeable genetic diversity between indigenous cattle ecotypes and commercial populations. Analysis of population structure demonstrated evidence of shared genetic ancestry between studied cross-bred population and both Red-Angus and Mongolian breeds. Among all studied cattle populations, the highest and lowest levels of linkage disequilibrium (LD) per Kb were detected in Holstein and Rashoki populations (ranged from ~ 0.54 to 0.73, respectively). Our search for potential genomic regions under selection in cross-bred cattle revealed several candidate genes related with immune response and cold shock protein on multiple chromosomes. We identified some adaptive introgression genes with greater than expected contributions from Mongolian ancestry into Molgolian x Red Angus composites such as TRPM8, NMUR1, PRKAA2, SMTNL2 and OXR1 that are involved in energy metabolism and metabolic homeostasis. In addition, we detected some candidate genes probably associated with immune response-related traits. Conclusion The study identified candidate genes involved in responses to cold adaptation and immune response in cross-bred cattle, including new genes or gene pathways putatively involved in these adaptations. The identification of these genes may clarify the molecular basis underlying adaptation to extreme environmental climate and as such they might be used in cattle breeding programs to select more efficient breeds for cold climate regions.

Highlights The effects of canopy height, leaf area index, and growth stage on the accurate monitoring of canopy height with different 3D sensors were systematically evaluated. Field-measured canopy height may not be as accurate as believed, especially in the plots with higher canopy height and at later growth stages. 3D sensing methods achieved higher heritable canopy height estimation than field measurement.

The inability to distinguish two-bond from long-range HMBC correlation has historically impeded NMR structure elucidation. Here the authors developed a practical iHMBC methodology utilizing accurate isotope shift measurement to overcome this limitation.

Abstract Introduction This study aimed to predict the fracture resistance of a mandibular first molar (MFM) with diverse endodontic cavities using finite element analysis (FEA). Methods Five experimental finite element models representing a natural tooth (NT) and 4 endodontically treated MFMs were generated. Treated MFM models were with a traditional endodontic cavity (TEC) and minimally invasive endodontic (MIE) cavities, including guided endodontic cavity (GEC), contracted endodontic cavity (CEC) and truss endodontic cavity (TREC). Three loads were applied, simulating a maximum bite force of 600 N (N) vertically and a normal masticatory force of 225 N vertically and laterally. The distributions of von Mises (VM) stress and maximum VM stress were calculated. Results The maximum VM stresses of the NT model were the lowest under normal masticatory forces. In endodontically treated models, the distribution of VM stress in GEC model was the most similar to NT model. The maximum VM stresses of the GEC and CEC models under different forces were lower than those of TREC and TEC models. Under vertical loads, the maximum VM stresses of the TREC model were the highest, while under the lateral load, the maximum VM stress of the TEC model was the highest. Conclusion The stress distribution of tooth with GEC was most like NT. Compared with TECs, GECs and CECs may better maintain fracture resistance, TRECs, however, may have a limited effect on maintenance of the tooth resistance.

ABSTRACTIn this work, microporous MgO refractory aggregates with nano-sized pores were prepared by in situ decomposition method using Mg(OH)2 as raw material. The effects of firing temperatures (1600–1700°C) and compacting pressures (100–200 MPa) on the microstructures and properties of microporous MgO refractory aggregates were thoroughly studied. The results showed that the microporous MgO refractory aggregates contained two types of pore structures, which were intra-particle pores with pore sizes of 180.0–230.0 nm formed by in situ decomposition of Mg(OH)2 and inter-particle pores with pore sizes of 1.5–3.0 μm derived from particle packing between Mg(OH)2 pseudomorph particles, respectively. Besides, the firing temperatures had a great influence on the intra-particle pore size and microcrystallite size. And the compacting pressures not only influenced the intra-particle pore size via packing behaviors but also affected the inner firing behaviors of the pseudomorph particles due to the increase in H2O vapor pressure. Overall, at a compacting pressure of 150 MPa and firing temperature of 1650°C, the sample had the best comprehensive performance with a bulk density of 1.92 g/cm3, a compressive strength of 11.9 MPa, an apparent porosity of 45.0%, a relative aggregate tube strength of 25.2% and a median pore size of 262.3 nm.

The subcellular localization of messenger RNAs (mRNAs) is a pivotal aspect of biomolecules, tightly linked to gene regulation and protein synthesis, and offers innovative insights into disease diagnosis and drug development in the field of biomedicine. Several computational methods have been proposed to predict the subcellular localization of mRNAs within cells. However, there remains a deficiency in the accuracy of these predictions. In this study, we propose an mRCat predictor based on the gradient boosting tree algorithm specifically to predict whether mRNAs are localized in the nucleus or in the cytoplasm. This predictor firstly uses large language models to thoroughly explore hidden information within sequences and then integrates traditional sequence features to collectively characterize mRNA gene sequences. Finally, it employs CatBoost as the base classifier for predicting the subcellular localization of mRNAs. The experimental validation on an independent test set demonstrates that mRCat obtained accuracy of 0.761, F1 score of 0.710, MCC of 0.511, and AUROC of 0.751. The results indicate that our method has higher accuracy and robustness compared to other state-of-the-art methods. It is anticipated to offer deep insights for biomolecular research.

Each application of neurostimulators requires unique stimulation parameter specifications to achieve effective stimulation. Balancing the current magnitude with stimulation resolution, waveform, size, and channel count is challenging, leading to a loss of generalizability across broad neural interfaces. To address this, this paper proposes a highly scalable, programmable neurostimulator with a System-on-Chip (SOC) capable of 32 channels of independent stimulation. The compliance voltage reaches up to ±22.5 V. A pair of 8-bit current-mode DACs support independent waveforms for source and sink operations and feature a user-selectable dual range for low-current intraparenchymal microstimulation with a resolution of 4.31 μA/bit, as well as high current stimulation for spinal cord and DBS applications with a resolution of 48.00 μA/bit, achieving a wide stimulation range of 12.24 mA while maintaining high-resolution biological stimulation. A dedicated communication protocol enables full programmable control of stimulation waveforms, effectively improving the range of stimulation parameters. In vivo electrophysiological experiments successfully validate the functionality of the proposed stimulator. This flexible stimulator architecture aims to enhance its generality across a wide range of neural interfaces and will provide more diverse and refined stimulation strategies.

To investigate the mechanical properties and energy evolution laws of rocks under true triaxial unloading conditions, a study was conducted using a true triaxial rock testing system on three different types of rocks: coal, sandy mudstone, and siltstone. The study examined the mechanical behavior, failure patterns, and fractal dimensions of these rocks under true triaxial unloading conditions. The tests revealed significant variations in stress–strain curves and failure patterns among the different rock types. Observation indicated that rocks with lower peak strength exhibited higher fractal dimensions and increased fragmentation upon failure. Subsequently, based on the experimental data of siltstone, the impact of the unloading rate and particle size distribution on the energy evolution under true triaxial single-sided unloading paths was further investigated using the three-dimensional particle flow software PFC3D 6.0, revealing the micro-mechanisms of rock energy evolution. The study revealed that when the initial stress unloading level was low, the total energy and strain energy at the peak strength exhibited a strong linear relationship with the unloading rate. Before the stress peak, the dissipative energy was mainly composed of frictional energy. After the stress peak, the dissipative energy consisted of frictional energy, damping energy, and kinetic energy. The heterogeneity of rock significantly affected the distribution of dissipative energy, with an increase in rock heterogeneity leading to a decrease in frictional energy and an increase in kinetic energy.

Deep geothermal energy is a sustainable and renewable spacing heating source. Although many studies have discussed the design optimization of deep borehole systems, few have accomplished optimization and in-depth analysis of system operation control. In this study, an analytical model of the U-type deep borehole heat exchanger is proposed, and the average relative error between the simulated outlet temperatures and experimental data is −3.2%. Then, this paper presents an integrated model for the operation optimization study of the U-type deep-borehole ground source heat pump system. The optimal control of flow rate is adopted to match the variation in heating load. Compared with the constant-flow rate (110 m3/h) operation mode, the variable flow rate method reduces the power consumption of the heat pump and circulating pump by 22.1%, from 288,423 kW·h to 224,592 kW·h, during 2112 h of operation. In addition, the system has a larger RHS and COP when the thermal conductivity of the backfill material increases. When the borehole depth increases by 200 m from 2300 m, the energy consumption of the circulating pump will drop from 85,844 kW·h to 56,548 kW·h. The COP of the heat pump unit will decrease approximately linearly as the heating load increases, and the total power consumption will increase accordingly. This work can provide guidance for the design and optimization of U-shaped GSHP systems.

Currently, China has entered the development stage of a “low birth rate” demographically. There is a huge contradiction between the unbalanced and inadequate distribution of preschool education facilities (PEFs) and the people’s expectations for “full and good education for children”. This study took the Lingui New District, a typical new urban area in West China as the research area, and through the introduction of POI big data and GIS analysis methods, supplemented by GeoDA Bivariate Moran index analyses, established a kindergarten spatial database. The study found that preschool education facilities have problems such as insufficient quantity, uneven quality, low service coverage, poor accessibility, etc. Therefore, it is suggested to increase the proportion of public affordable preschool education facilities including kindergartens and nurseries, optimize the spatial distribution of preschool education, and improve the accessibility of preschool services to promote affordable, safe, and high-quality development of preschool education and to provide reference suggestions for the revision of relevant standards and the adjustment of the layout of preschool education in undeveloped regions of China.

Landslide susceptibility prediction usually involves the comprehensive analysis of terrain and other factors that may be distributed with spatial patterns. Without considering the spatial correlation and mutual influence between pixels, conventional prediction methods often focus only on information from individual pixels. To address this issue, the present study proposes a new strategy for neighboring pixel collaboration based on the Unified Perceptual Parsing Network (UPerNet), the Vision Transformer (ViT), and Vision Graph Neural Networks (ViG). This strategy efficiently utilizes the strengths of deep learning in feature extraction, sequence modeling, and graph data processing. By considering the information from neighboring pixels, this strategy can more accurately identify susceptible areas and reduce misidentification and omissions. The experimental results suggest that the proposed strategy can predict landslide susceptibility zoning more accurately. These predictions can identify flat areas such as rivers and distinguish between areas with high and very high landslide susceptibility. Such refined zoning outcomes are significant for landslide prevention and mitigation and can help decision-makers formulate targeted response measures.