Search

To address the limitations of current deep learning-based methods in extracting contract bytecode features and representing vulnerability semantics, as well as the shortcomings of the traditional graph neural networks in learning temporal information from contract statements, a method for detecting vulnerabilities in contracts was proposed based on pre-trained and temporal graph neural network. Firstly, the pre-trained model was used to transform smart contract bytecode into a vulnerability semantics-aware contract graph structure. Then, combined with a self-attention mechanism, the event-driven temporal graph neural network was designed to extract temporal information during contract execution. Finally, focusing on reentrant vulnerabilities, timestamp dependency vulnerabilities, and Tx.origin authentication vulnerabilities, extensive experiments were conducted on a dataset of 120 932 actual contracts. The results show that the proposed method significantly outperforms existing approaches.

To improve the work efficiency and stability of discharger in soybean conditioner, this paper combined the discrete element method to simulate the motion process of soybeans in the discharger, and analyzed the effects of rotor blade number, feeding plate angle, and angle between inlet and outlet of the discharger. The results showed that when the velocity of discharger was 12 r/min, the number of rotor blades had a significant negative correlation with the discharger’s work efficiency and stability. The feeding plate angle had no significant on the work efficiency and stability, but it would cause material residue at the inlet of discharger. The larger the angle between the inlet and outlet led to the lower the work efficiency of discharger, but the work stability was better. The above research showed that when the number of the rotor blades was 6, the feeding plate angle was 40°. The angle between inlet and outlet was 180°, and the work efficiency and stability of discharger reached optimal levels.

Abstract [Objective] The study aims to characterize CPP gene family in foxtail millet (Setaria italica L.) and analyze their response to exogenous selenium treatment, in order to provide materials for the breeding of new foxtail millet varieties with high selenium and folate. [Methods] This study used bioinformatics tools to identify the CPP gene family members in foxtail millet, and used qRT-PCR to detect their expression levels in different tissues under exogenous selenium treatment. [Results] (1) 9 CPP genes were identified in foxtail millet genome, which were distributed on 6 chromosomes, named SiCPP1- SiCPP9, respectively. These genes were located in the nucleus. The proportion of random coil in protein secondary structure was the largest. (2) The CPP protein in foxtail millet could be divided into four subfamilies, and the number and distribution of conserved motifs and domains were similar among the same subfamilies. (3) Cis-acting element analysis found that the SiCPP genes had a large number of light, growth and development-related, and hormone and stress response elements. (4) SiCPP genes were expressed differently in roots, stems, leaves, and ears, and SiCPP5, SiCPP6, SiCPP7 and SiCPP8 showed the strongest response to exogenous selenium. [Conclusion] SiCPP genes show tissue-specific expression and respond to exogenous selenium to varying degrees.

Abstract The Beijing-Hangzhou Grand Canal, China’s oldest and most crucial water transportation project, ensures smooth operation and efficient water transportation through interconnected water engineering facilities. Studying the connections among the water engineering facilities of the Beijing-Hangzhou Grand Canal is theoretically and practically significant for preserving and innovating canal heritage. Therefore, this study utilizes social network analysis to comprehensively examine the spatial connections and network status of water engineering facilities along the Beijing-Hangzhou Grand Canal across different channel structure. Gephi 0.10.1 was utilized in this study to construct a relational network of water engineering facilities along the Beijing-Hangzhou Grand Canal, with each facility considered as a network node. By applying network analysis indices such as degree, closeness centrality, and betweenness centrality, the correlation between water engineering facilities was thoroughly investigated. The study’s findings reveal that: (1) the Beijing-Hangzhou Grand Canal possesses numerous overall network nodes with extensive coverage; however, its overall network density is relatively low, and the inter-node connection is weak. (2) Across the entire network, the spatial distribution of degree and betweenness centrality exhibits a clustered pattern. Their distribution patterns are centered on the Lake region section where Hongze Lake is located and the segment from Liucheng to Zhenjiang in the Lake region, the River transport confluence section, and the Nature river section, respectively. The spatial distribution characteristics of closeness centrality show a dispersed shape, with stronger areas mainly concentrated in the canal’s tributaries, especially the Nature river section, which shows more prominence. (3) Analyzed from a channel structure perspective, water engineering facilities in different sections assume distinct linking roles within the network. Facilities in the Lake region section play the strongest overall linkage role, partly due to its highest node proportion. Conversely, in the Nature river section, facilities primarily serve transshipment and direct connection functions, whereas in the River transport confluence section, they act mainly as intermediaries or “bridges”. Notably, water control facilities in the Nature river section and river engineering facilities in the River transport confluence section play pivotal driving roles in their respective sections, warranting special attention and protection as critical canal nodes.

Abstract This research explores the spatial distribution patterns of water engineering facilities along the Grand Canal during the Ming and Qing dynasties. It employs the entropy method to assess the social development status of prefectures during these periods and uses the Tobit model to examine the primary indicators influencing the distribution of water engineering facilities. The results show that the spatial distribution pattern of water engineering facilities was characterized by aggregation during the Ming and Qing dynasties. In contrast, the Qing dynasty’s distribution was more dispersed, with a shift in the construction focus of water engineering facilities towards the south. The spatial distribution pattern of water engineering facilities in the Ming Dynasty centered around the hotspot areas of Shuntian Prefecture, Yanzhou Prefecture, and Yangzhou Prefecture. During continuous improvements, these facilities exhibited a multi-point-regional aggregation phenomenon.The influence of commercial development indicator on the spatial distribution of water engineering facilities is positively correlated in both the Ming and Qing dynasties. However, the impacts of the indicator on different types of water engineering facilities vary between the two dynasties. During the Ming Dynasty, the indicators of transportation accessibility and cultural prosperity facilitated the construction of regional water engineering facilities, whereas in the Qing Dynasty, they significantly influenced several types of water engineering facilities. During the Ming and Qing Dynasties, neither the agricultural development indicator nor the population size indicator significantly affected the distribution of water engineering facilities. However, there was a negative correlation between the population size indicator and the distribution of water distribution facilities in the Ming Dynasty. This study enhances the importance of environmental protection in historical societies and provides a valuable reference for other international studies of linear cultural and material heritage.

In order to study the effect of ultrafine grinding time on the quality characteristics of whole wheat flour and dough, wheat was used as raw material and the whole grain wheat was ultra-finely ground by direct grinding method. The effects of particle size on the gelatinization characteristics, thermomechanical properties of whole wheat flour rheological properties of dough, color and texture of dough were investigated. The results showed that with the increase of crushing time, the particle size of whole wheat flour decreased, and the D50 decreased from 107.20 um to 45.65 um. The particle size distribution was more concentrated. The peak viscosity decreased, and the setback value decreased from 623.33 mPa·s to 485.33 mPa·s. The reduction of particle size could delay the aging of dough and product. The hardness of dough gradually decreased with the decrease of particle size, and the elasticity and cohesion gradually increased. The water absorption rate of dough increased from 65.7% to 76.7%, and the stabilization time also showed an upward trend. The low-temperature ultrafine grinding technology of wheat grains can improve the quality of whole wheat flour, and it is feasible to apply this technology to the field of whole grain processing.

This study focused on investigating the heat transfer and flow dynamics of a catalyst granule within a pilot calciner, employing both numerical modeling and computational fluid dynamics. The research comprised two primary components: (1) Simulation of the gas flow within the pilot calciner using the Eulerian–Eulerian approach, treating gases and catalyst particles as distinct phases – gas and granular. The model, encapsulating both heat transfer and flow processes, was developed in Fluent software version 16.0. Its accuracy was confirmed against empirical data from a pilot-scale calciner unit. (2) Subsequent to validation, the model was utilized to examine the distribution characteristics within the flow field, including the temperature profiles of gas and particles, the vector velocity field of the gas across different phases, and the overall heat transfer coefficient. This investigation aims to enhance the understanding of the complex heat transfer and flow dynamics in calciners, facilitating the optimization of operational parameters, performance, and structure of pilot-scale equipment. Furthermore, it provides foundational data pertinent to the future exploration of real-world industrial applications.

Abstract Background The role of red blood cell (RBC) counts as potential independent risk factors for deep vein thrombosis (DVT) in patients with spinal cord injury (SCI) remains uncertain. This study aims to clarify the associations between RBC counts and DVT incidence among this population. Methods A retrospective analysis was performed on 576 patients with SCI admitted to the rehabilitation medicine department from January 1, 2017 to December 31, 2021. After exclusions, 319 patients were analyzed, among which 94 cases of DVT were identified. Results Mode of injury, D-dimer and anticoagulant therapy were significant covariates (P

The existing deep learning based coal gangue recognition methods have problems in complex working conditions such as low lighting, high noise, and motion blur in coal mines, such as low precision of coal gangue recognition, easy omission of small target coal gangue, large model parameter and computational complexity, and difficulty in deploying to devices with limited computing resources. A coal gangue recognition algorithm based on the HGTC-YOLOv8n model is proposed. The method replaces the backbone network of YOLOv8n with HGNetv2 network, effectively extracts multi-scale features to improve coal gangue recognition performance and reduces model storage requirements and computational resource consumption. The method embeds a Triplet Attention mechanism module in the backbone network to capture interaction information between different dimensions. The method enhances the extraction of target features in coal gangue images, and reduces the interference of irrelevant information. The method selects the content aware reassembly of features(CARAFE) to improve the upsampling operator of YOLOv8n neck feature fusion network, utilizing contextual information to enhance perceptual field of view and improve the accuracy of small target coal gangue recognition. The experimental results show the following points.① The average precision of the HGTC-YOLOv8n model is 93.5%, the parameters number of the model is 2.645×106, the number of floating-point operation is 8.0×109, and the frame rate is 79.36 frames/s. ② The average precision of the YOLOv8n model has increased by 2.5% compared to the YOLOv8n model, and the number of parameters and floating-point operations have decreased by 16.22% and 10.11%, respectively. ③ The comparison results with the YOLO series models show that the HGTC-YOLOv8n model has the highest average precision, the least number of parameters and floating-point operations, fast detection speed, and the best overall detection performance. ④ The coal gangue recognition algorithm based on the HGTC-YOLOv8n model has improved the low precision of coal gangue recognition and the easy omission of small target coal gangue under complex working conditions in coal mines. The method meets the requirements of real-time detection of coal gangue images.

The cold winter weather in northern China influences the dietary habits of its residents, contributing to a heightened risk of cardiovascular disorders, such as hypertension and coronary heart disease. Key factors include low vegetable consumption and high salt and fat intakes. This study aims to investigate the relationships between northern dietary nutrient intake in northern China and cardiovascular disorders during the winter season.

UBE2C is overexpressed in gliomas, and its overexpression has been reported to be correlated with the drug resistance of gliomas to some extent. In this study, we explore the role of UBE2C in regulating temozolomide (TMZ) resistance in glioma and investigate the underlying mechanisms involved. Twenty normal brain tissues and 100 glioma tissues from 50 TMZ-resistant patients and 50 TMZ-sensitive patients are included in this study. TMZ-resistant cell lines are constructed to explore the role of UBE2C in regulating glioma cell viability and TMZ resistance. Our results show that both the mRNA and protein levels of UBE2C are significantly elevated in the brain tissues of glioma patients, especially in those of TMZ-resistant patients. Consistently, UBE2C expression is markedly upregulated in TMZ-resistant cell lines. Overexpression of UBE2C rescues glioma cells from TMZ-mediated apoptosis and enhances cell viability. In contrast, downregulation of UBE2C expression further enhances TMZ function, increases cell apoptosis and decreases cell viability. Mechanistically, UBE2C overexpression decreases p53 expression and enhances aerobic glycolysis level by increasing ATP level, lactate production, and glucose uptake. Downregulation of p53 level abolishes the role of UBE2C downregulation in inhibiting TMZ resistance and aerobic glycolysis in glioma cells. Moreover, an animal assay confirms that downregulation of UBE2C expression further suppresses tumor growth in the context of TMZ treatment. Collectively, this study reveals that downregulation of UBE2C expression enhances the sensitivity of glioma cells to TMZ by regulating the expression of p53 to inhibit aerobic glycolysis.

ObjectiveThis study aimed to investigate the clinical effects of Orff music therapy on children with Autism Spectrum Disorder (ASD) from the perspectives of parents, evaluators, and therapists.Methods93 children with ASD aged 3–6 years participated in the study. They were divided into an observation group (n = 48) receiving comprehensive rehabilitation intervention including Orff music therapy, and a control group (n = 45) receiving only comprehensive rehabilitation intervention. The Autism Behavior Checklist (ABC), Childhood Autism Rating Scale (CARS), and Psycho-educational Profile-3rd edition (PEP-3) were used for assessments before and after the intervention.ResultsThere were no significant demographic differences between the two groups. Both groups showed significant improvements in Sensory, Relating, Language, CVP, EL, RL, VMI, AE, SR, and CARS scores at T1, T2, and T3 (T1 vs. T2, T2 vs. T3, T1 vs. T3) (all p

In order to effectively capture the fault features contained in the vibration signals of the rotating machinery and complete the fault diagnosis task efficiently, a fault diagnosis model combining two-dimensional image features and lightweight neural network is designed. Firstly, the collected one-dimensional vibration signals are decomposed by modified ensemble empirical mode decomposition (MEEMD) to obtain the intrinsic mode function (IMF) components, and the corresponding IMF components are selected for sum reconstruction to enhance the amplitude fluctuation of vibration signals. Then, Markov transition field (MTF) could be used to more effectively characterize the fault features in the reconstructed signals. Secondly, the 2D feature map generated by MTF is input into residual depth separable convolutional neural network (ResDSCNN) for feature extraction and fault diagnosis. The planetary gearbox fault data set is used to verify the performance of the model, and the results show that the diagnosis accuracy of the model for all kinds of gear faults can reach more than 98%.

C17H16OS, monoclinic, P21/n (no. 14), a = 5.4605(12) Å, b = 19.767(4) Å, c = 13.357(4) Å, β = 92.834(3)°, V = 1,439.9(6) Å3, Z = 4, R gt(F) = 0.0398, wR ref(F 2) = 0.1144, T = 296(2) K.

Abstract Water engineering facilities are a crucial component of the Beijing-Hangzhou Grand Canal during the Ming and Qing dynasties, and their distribution is closely related to the hydrological and topographical characteristics of the area. In this study, we reconstructed the canal network distribution map and water engineering facilities database of the Ming and Qing periods using ArcGIS (Geographical information systems software) 10.8 software. We employed Amos (Analyze of Moment Structures) 26.0 software to investigate the influence of various natural environmental factors on the selection of water engineering facility sites. The results revealed a significant correlation between the spatial distribution of water engineering facilities and the main channel slope and slope direction, which had a direct impact. The estimated coefficient for the main channel slope was -0.166, showing a negative correlation with the spatial distribution of water engineering facilities, while the estimated coefficient for the main channel slope direction was − 0.112, also indicating a negative correlation. Moreover, the estimated coefficient for the watershed area where water engineering facilities were located was -0.096, demonstrating a negative correlation. In contrast, the effects of tributary slope and slope direction on the spatial distribution of water engineering facilities were indirect, mediated by the watershed area where these facilities were situated. The effect size for tributary slope was -0.017, showing a negative correlation, while the effect size for tributary slope direction was 0.010, indicating a positive correlation with the spatial distribution of water engineering facilities.The study achieves the integration of the heritage of water engineering facilities along the canal from point to line, provides data support for the construction of the cultural heritage corridor of the canal, and facilitates the promotion of heritage protection and rational layout, which is of great significance to the understanding of the canal culture.

Objective To investigate the prognostic factors of breast cancer brain metastasis (BCBM), and to construct and validate a prediction model for prognosis of BCBM patients. Methods A case-control trial was designed and conducted in this study. A total of 1 133 BCBM patients were screened out from the Surveillance, Epidemiology, and End Results (SEER) database from 2016 to 2020, and were randomly assigned to a training set (n=793) and an internal validation set (n=340) at a ratio of 7 ∶3. The prognostic factors were determined with univariate and multivariate Cox regression analyses, and a nomogram prediction model was constructed. The discrimination, prediction and calibration of the nomograms were evaluated by C-index, receiver operating characteristic (ROC) curve and calibration curve. External validation of the nomogram prediction model was performed in 73 BCBM patients admitted to our hospital from 2004 to 2019. Results Multivariate Cox regression analysis revealed that age, molecular type, surgery, radiotherapy, chemotherapy, lung metastasis and liver metastasis were identified as independent factors (P

This review summarized and analyzed the immunoassay techniques, such as enzyme-linked immunosorbent assay, immunochromatographic assay, and chemiluminescence immunoassay, which have been applied in the detection of amantadine residue, and provides an outlook on their development.

The rapid development of the Internet also provides the possibility of information flow for cross-cultural communication, and the network not only breaks through the boundaries of time and space but also breaks through the limitations of cultural communication barriers. The study analyzes the influence mechanism of cross-cultural communication through the medium of social networks. A series of characteristics are proposed to characterize the flow of information, and a simulation experiment is carried out on the influencing factors of cross-cultural communication using the infectious disease model (SEIR). We utilize the Twitter dataset of real social networks to examine the effectiveness of the proposed SEIR model of information dissemination and verify its accuracy. The simulation experiment analyzes the influence of the containment mechanism, the time lag mechanism, and the forgetting mechanism on the model of information dissemination in cross-cultural communication, and information dissemination does not occur when R0 1, the cross-cultural communication information will be continuously and stably spread in the social network. This paper’s SEIR model has a positive effect on the dissemination of cross-cultural communication information, as evidenced by the results.

Aiming at the problems existing in the ideological and political education of college students, this paper puts forward the research on the ideological and political education of college students based on CIPP evaluation. From the CIPP evaluation, the fundamental value of ideological and political education evaluation of “enhancing output” and the evaluation objectives of effect, efficiency and effectiveness are clarified, and the four-dimensional evaluation content framework of ideological and political education of college students is formed. An evaluation index system consisting of 4 first-level indicators, 11 second-level indicators, and 36 third-level indicators was finally created by selecting experts. Through the second round of expert consultation, we obtained the results of assigning the degree of importance of indicators at all levels. Then we finalized the weights of indicators at all levels using the hierarchical analysis method. Based on the evaluation index system, colleges and universities’ ideological and political education is analyzed through examples. The results show that the overall evaluation scores of the three colleges and universities are all in the “ good “ range, with the scores of 78.3005, 80.4134 and 81.6171, respectively. This study aims to provide guidance and reference for the practice of ideological and political education for college students, and to promote the standardization and sustainable development of ideological and political education. This study aims to provide guidance and references for the practice of ideological and political education of college students, and promote the standardization and sustainable development of ideological and political education.

Objective: The preventive and therapeutic effects of the aqueous extract of Ficus pumila on COPD model rats were observed and its mechanism was also discussed. Methods: COPD model was established by intratracheal injection of lipopolysaccharide and smoking. Using the pulmonary function test, the level of related inflammatory factors detection in the BALF by ELISA, the blood gas analysis and HE staining for lung pathological observation. Results: The results showed that the indexes of the model rats were consistent with the pathological characteristic of COPD. The model group animals had obvious airflow obstruction, while the high dose of F. pumila aqueous extract group could significantly increase the levels of FVC, Fev0.3, PEF, Fev0.3/FVC （P2 and CO2 in the lungs of the model rats; At the same time, the high dosage of Ficus pumila aqueous extract can significantly improve the pulmonary ventilation function of COPD, and the effect was better than positive drug. Medium dose-, high dose aqueous extract group and positive drug group could significantly reduce the number of leukocytes （P

The main technical means for preventing and controlling karst water damage in the coal seam floor of North China type coal fields are grouting transformation of the water-bearing rock layer. Currently, the main method for testing the grouting effect is to analyze the lithological features before and after grouting. There is a lack of tracking and dynamic monitoring of the entire grouting process, making it difficult to accurately evaluate the grouting effect. In order to solve the above problems, an inter hole resistivity monitoring system is introduced to monitor the entire process of resistivity changes in grouting transformed rock layers, in order to achieve precise detection of the slurry diffusion range. Firstly, an improved electrode and cable device is used to place the resistivity monitoring system in a long directional borehole on the coal seam floor, achieving resistivity monitoring between boreholes. Secondly, a geological model of slurry diffusion is constructed, and the simulated data is processed and interpreted using three-dimensional resistivity inversion. Finally, engineering tests are conducted on the inter hole resistivity monitoring of the entire grouting process at the injection layer underground in the coal mine. The simulation results indicate that inter hole resistivity monitoring can identify the diffusion range of slurry anomalies. Based on the trend of resistivity changes over time, the diffusion range of slurry can be inferred. As the slurry gradually diffuses, the range of anomalous areas gradually increases and the intensity of anomalies gradually increases. The engineering test results show that the resistivity monitoring system is arranged on the grouting layer through drilling for dynamic monitoring. After three-dimensional inversion imaging of the monitoring data, the features of resistivity changes in the grouting layer caused by slurry diffusion can be successfully captured. It provides a feasible technical solution for detecting the grouting effect in coal mines.

In order to explore the influence of the variation of hemispherical bevel gear parameters on the dynamic characteristics of the system, a dynamic model of the hemispherical bevel gear pair is established based on the lumped mass method. Based on high-quality hexahedral mesh model, the dynamic transmission performance of hemispherical bevel gears is analyzed by rigid-flexible coupling flexible body dynamics simulation. The influence of parameters such as the size of hemispherical bevel gears and the shaft angle on the motion state of the system is analyzed. The simulation results show that the transmission accuracy, stability and strength of the system change regularly and are negatively correlated with each other under different parameters. The comprehensive performance of hemispherical bevel gears is the best when the diameter of indexing circle is 65 mm and the angle of intersecting shaft is 120°. The flexible multi-body dynamics simulation analysis provides an important reference for the model design, processing and manufacturing of hemispherical bevel gears.

Streptococcus agalactiae is an important zoonotic pathogen that affects milk production and quality and poses a threat to public health. Treatment of infections with this bacterium exploits antimicrobials, to which the resistance of S. agalactiae is a growing problem. Addressing the possibility of a correlation between this pathogen’s genetic factors for antimicrobial resistance and virulence, this study attempted to identify the relevant genes.

Egg granuloma formation in the liver is the main pathological lesion caused by Schistosoma japonicum infection, which generally results in liver fibrosis and may lead to death in advanced patients. MicroRNAs (miRNAs) regulate the process of liver fibrosis, but the putative function of miRNAs in liver fibrosis induced by S. japonicum infection is largely unclear. Here, we detect a new miRNA, miR-182-5p, which shows significantly decreased expression in mouse livers after stimulation by soluble egg antigen (SEA) of S. japonicum or S. japonicum infection. Knockdown or overexpression of miR-182-5p in vitro causes the increased or decreased expression of tristetraprolin (TTP), an important immunosuppressive protein in the process of liver fibrosis. Furthermore, knockdown of miR-182-5p in vivo upregulates TTP expression and significantly alleviates S. japonicum-induced hepatic fibrosis. Our data demonstrate that downregulation of miR-182-5p increases the expression of TTP in mouse livers following schistosome infection, which leads to destabilization of inflammatory factor mRNAs and attenuates liver fibrosis. Our results uncover fine-tuning of liver inflammatory reactions related to liver fibrosis caused by S. japonicum infection and provide new insights into the regulation of schistosomiasis-induced hepatic fibrosis.

With the implementation of “photovoltaic power stations for poverty alleviation”， it becomes a new idea of earning extra income for farmer households with access to photovoltaic power and incorporating solar panels with power grid. In view of the characteristics of rural distribution networks， large-scale integration of photovoltaic power aggravates voltage quality. Firstly， given PV output fluctuations and complex distribution of rural loads， a typical system scenario is established using a clustering method based on AP （affinity propagation）. Secondly， the paper establishes a voltage quality control and planning model of double-layer hybrid distribution networks based on constraints of active power sources and reactive power sources， including bi-directional power flow， voltage constraint， PV， energy storage， and SVG. Finally， the paper presents a comprehensive solution to line loss rate and voltage quality control using distributed robust planning algorithms based on typical system scenarios. The results show that the proposed voltage control scheme can reduce costs and line loss rate without exceeding the voltage limit， and is proved safe and economical.

Objective: In this study, the finite element simulation was integrated into random vibration experiment to provide a new way of thinking about transportation packaging. Methods: The red wine inner packaging spacer, made of three different cushioning materials, was used as the research object, and the vibration response was studied through random vibration experiment. Then the finite element simulation was used to analyze the correlation between the experiment and the simulation results. Results: The results of random vibration test were highly consistent with the results of finite element simulation, and the finite element simulation was less material-and time-consuming, compared with the random test. Conclusion: The combination of random experiment and finite element method can improve the efficiency of the experiment. The finite element simulation method can provide effective guidance for the analysis and design of product inner packaging under the vibration environment of transportation.

Hyperuricemia is another common metabolic disease, which is considered to be closely related to the development of many chronic diseases, in addition to the “three highs.” Currently, although drugs show positive therapeutic effects, they have been shown to produce side effects that can damage the body. There is growing evidence that medicinal and edible plants and their bioactive components have a significant effect on hyperuricemia. In this paper, we review common medicinal and edible plants with uric acid-lowering effects and summarize the uric acid-lowering mechanisms of different bioactive components. Specifically, the bioactive components are divided into five categories: flavonoids, phenolic acids, alkaloids, polysaccharides, and saponins. These active substances exhibit positive uric acid-lowering effects by inhibiting uric acid production, promoting uric acid excretion, and improving inflammation. Overall, this review examines the potential role of medicinal and edible plants and their bioactive components as a means of combating hyperuricemia, with the hope of providing some reference value for the treatment of hyperuricemia.

The issues of both system security and safety can be dissected integrally from the perspective of behavioral appropriateness. That is, a system that is secure or safe can be judged by whether the behavior of certain agent(s) is appropriate or not. Specifically, a so-called appropriate behavior involves the right agent performing the right actions at the right time under certain conditions. Then, according to different levels of appropriateness and degrees of custodies, behavioral authentication can be graded into three levels, i.e., the authentication of behavioral Identity, Conformity, and Benignity. In a broad sense, for the security and safety issue, behavioral authentication is not only an innovative and promising method due to its inherent advantages but also a critical and fundamental problem due to the ubiquity of behavior generation and the necessity of behavior regulation in any system. By this classification, this review provides a comprehensive examination of the background and preliminaries of behavioral authentication. It further summarizes existing research based on their respective focus areas and characteristics. The challenges confronted by current behavioral authentication methods are analyzed, and potential research directions are discussed to promote the diversified and integrated development of behavioral authentication.

The medicinal value of P. zhennan has been documented in traditional Chinese medicine books. The aim of this paper was to study the antioxidant activity of alcoholic extracts of P. zhennan leavesusing 1,1-diphenyl-2-picrylhydrazyl (DPPH) and 2-phenyl-4,4,5,5-tetramethylimidazolineoxyl-1-oxyl-3-oxide (PTIO) radical scavenging and ferric ion reducing antioxidant power (FRAP) assays. The active components of the leaves were identified via headspace solid-phase microextraction and gas chromatography–mass spectrometry (HS-SPME-GC-MS). The results showed that the scavenging rate of DPPH was 94.67%with an EC50 value of 0.674 mg/mL at a concentration of 2 mg/mL. The maximum scavenging rate was 47.40% at a Trolox equivalent of 0.33 mg TE/mL for PTIO radicals. The FRAP reached 84.80% at 0.20 mg/mL concentration. The results confirmed the strong antioxidant activity of the extracts. Furthermore, 44 compounds, mostly terpenoids, obtained from the alcoholic extracts of P. zhennan leaves were analyzed using HS-SPME-GC-MS and 15 of these compounds had a relative content exceeding 1%. The strong antioxidant activity of the alcoholic extracts of P. zhennan leaves could be attributed to the presence of copaene (33.97%), β-caryophyllene (4.42%), δ-cadinene (11.04%), γ-muurolene (4.78%), cis-calamenene (2.02%), linalool (1.04%), α-pinene (1.46%), borneol acetate (1.5%), and γ-terpinene (0.66%). This study demonstrates the potential medicinal value of alcoholic extracts of P. zhennan leaves.

Abstract Pyroptosis is inflammation-associated caspase-1-dependent programmed cell death, which confers a crucial role in sepsis. The present study intends to investigate the regulatory network and function of the microarray-predicted YTHDF1 in caspase-1-dependent pyroptosis of sepsis. Peripheral blood of patients with sepsis was collected to determine WWP1 and YTHDF1 expression. An in vitro sepsis cell model was induced in RAW264.7 cells using lipopolysaccharide (LPS) and ATP and an in vivo septic mouse model by cecal ligation and perforation (CLP). After gain- and loss-of-function assays in vitro and in vivo, TNF-α and IL-1β levels and the cleavage of gasdermin-D (GSDMD) were detected by ELISA and Western blot assay, followed by determination of lactate dehydrogenase (LDH) activity. Immunoprecipitation and meRIP assay were performed to detect the ubiquitination of NLRP3 and the m6A modification of WWP1 mRNA. The binding of WWP1 to YTHDF1 was explored using RIP-RT-qPCR and dual luciferase gene reporter assay. It was noted that WWP1 and YTHDF1 were downregulated in clinical sepsis samples, LPS + ATP-treated RAW264.7 cells, and CLP-induced mice. The ubiquitination of NLRP3 was promoted after overexpression of WWP1. WWP1 translation could be promoted by YTHDF1. Then, WWP1 or YTHDF1 overexpression diminished LDH activity, NLRP3 inflammasomes and caspase-1-mediated cleavage of GSDMD in LPS + ATP-induced RAW264.7 cells. Overexpressed YTHDF1 restrained inflammatory response in CLP-induced mice. Collectively, the alleviatory effect of m6A reader protein YTHDF1 may be achieved through promotion of NLRP3 ubiquitination and inhibition of caspase-1-dependent pyroptosis by upregulating WWP1.

BACKGROUND Oil sand is an important unconventional oil and gas resource, which is composed of bitumen, solid particles (including coarse and fine particles) and water. The key to its development and utilization is to improve the extraction efficiency of bitumen. Solvent extraction technology is expected to replace the existing water-based extraction technology due to its high bitumen extraction efficiency and environmental friendliness. The high residue rate of solid particles in bitumen and low recovery efficiency of organic solvent in gangues are two main problems during solvent extraction, which is closely related to the composition, structure and surface properties of solid particles. Therefore, it is very important to understand the mineral composition and surface properties, especially hydrophilicity/hydrophobicity, of solid particles in oil sand. The oil sands in Inner Mongolia, China are characterized by abundant reserves and high oil content. At present, the mineral composition and hydrophilicity/hydrophobicity of solid particles in the oil sands in this area are not clear. OBJECTIVES To investigate the mineral composition and hydrophilicity/hydrophobicity of solid particles isolated from Inner Mongolia oil sands. METHODS Cyclohexane was adopted to separate the bitumen and solid particles from the oil sands. Fine particles and coarse particles were then separated using a 45μm standard sieve. The composition and structure of the particles were investigated by laser particle size analyzer, X-ray diffraction analyzer, specific surface area and porosity analyzer, Fourier transform infrared spectroscopy, organic element analyzer, scanning electron microscopy-energy dispersive X-ray spectrometry (SEM-EDX). The hydrophilicity/hydrophobicity of the particles was determined by film floatation and water vapor adsorption methods. RESULTS The contents of fine particles and coarse particles in the oil sands were 53.4% and 46.2%, respectively. The fine particles contained montmorillonite, kaolinite, illite, α-quartz and anorthite, while the coarse particles contained α-quartz and anorthite with minor kaolinite, illite and montmorillonite. The contents of bitumen and hydroxyl group in the fine particles were higher than those in the coarse particles. The mean critical surface tensions for fine particles and coarse particles were >47.62mN/m and >45.55mN/m, respectively, and the average water vapor adsorptions per unit area were 1.27mg/m2 and 0.41mg/m2, respectively, indicating that the coarse particles were more hydrophobic than the fine particles. CONCLUSIONS Regarding the adverse effects of hydrophobic solid particles on the separation and extraction of oil sand bitumen and the recovery of organic solvents, it is necessary to pay attention to fine solid particles and strengthen the research on the influence of coarse solid particles.

Abscisic acid (ABA) is an important plant hormone, which can control seed and bud dormancy, organ size control, senescence and death, and participate in both biological and abiotic stress, inhibit plant growth, and participate in plant disease resistance. In order to determine the content of ABA in plants quickly and accurately, a new type of ABA immunosensor was developed. To improve the detection performance of the sensor, the detection performance of the sensor was increased by modifying GR-COOH and SA on the electrode surface. The concentration of GR-COOH , SA, and ABA-Antibody were optimized, the optimal conditions for the three materials were 1.5 mg/ml, 1.25 mg/ml and 0.5 mg/ml. The immunosensor was constructed based on the electrode impedance changes (△Z ) due to the binding reaction of ABA antibody and antigen . It was found that the sensor showed linear relationship with ABA in the response range of 10 pmol/L~1 μmol/L, R2 was 0.99927, and the detection limit was about 10 pmol/L. The sensor also had good selectivity and stability. Using the electrochemical immunosensor, the content of ABA in navel orange leaf that have been successfully inoculated with citrus Huanglongbing by PCR was determined, and healthy plants were used as control. The test results showed that the impedance changes(△Z ) of healthy leaves and diseased leaves were 72 and 823, respectively, which indicated that the level of ABA in the infected plants increased significantly. The sensor provides a tool for the detection of plant hormone levels under disease stress. The results showed that the content of ABA increased in the leaves of navel orange infected by citrus Huanglongbing, which indicated that ABA played an important role in plant disease resistance. Furthermore, the changes of gene expression of key enzymes CitZEP in ABA synthesis pathway were studied, The results showed that the expression of CitZEP increased in plants infected with Huanglongbing disease, and the results were consistent with the detection results of the sensor, which indicated that the sensor had good practicability.

ObjectiveTo construct a YOLOv3-based model for diatom identification in scanning electron microscope images, explore the application performance in practical cases and discuss the advantages of this model.MethodsA total of 25 000 scanning electron microscopy images were collected at 1 500× as an initial image set, and input into the YOLOv3 network to train the identification model after experts’ annotation and image processing. Diatom scanning electron microscopy images of lung, liver and kidney tissues taken from 8 drowning cases were identified by this model under the threshold of 0.4, 0.6 and 0.8 respectively, and were also identified by experts manually. The application performance of this model was evaluated through the recognition speed, recall rate and precision rate.ResultsThe mean average precision of the model in the validation set and test set was 94.8% and 94.3%, respectively, and the average recall rate was 81.2% and 81.5%, respectively. The recognition speed of the model is more than 9 times faster than that of manual recognition. Under the threshold of 0.4, the mean recall rate and precision rate of diatoms in lung tissues were 89.6% and 87.8%, respectively. The overall recall rate in liver and kidney tissues was 100% and the precision rate was less than 5%. As the threshold increased, the recall rate in all tissues decreased and the precision rate increased. The F1 score of the model in lung tissues decreased with the increase of threshold, while the F1 score in liver and kidney tissues with the increase of threshold.ConclusionThe YOLOv3-based diatom electron microscope images automatic identification model works at a rapid speed and shows high recall rates in all tissues and high precision rates in lung tissues under an appropriate threshold. The identification model greatly reduces the workload of manual recognition, and has a good application prospect.

High-throughput sequencing technology combined with plate colony counting method was used to detect and analyze the microflora of water kefir and its starter water kefir granules. Probiotics were screened from naturally fermented water kefir and water kefir granules, and the selected probiotics were identified by individual and population morphological observation, physiological and biochemical experiments and 16S rDNA sequence analysis. The results showed that lactic acid bacteria were the dominant bacteria in the two samples; whether it is water kefir or water kefir grain, Firmicutes and Proteus are the dominant bacteria, Lactobacillus and Acetobacter are the dominant bacteria, The bacterial diversity and richness of water kefir granules were higher than those of water kefir；A total of 7 strains of lactic acid bacteria with potential probiotics of acid and bile resistant salts were screened, and the identification results were four strains of Lactobacillus fermentum, one strain of Lactobacillus paracasei, one strain of Lactobacillus harbinensis and one strain of Lactobacillus rubrum were identified and named Lactobacillus fermentum cc4、Lactobacillus fermentum cc8、Lactobacillus fermentum cc9、Lactobacillus fermentum cc22、Lactobacillus paracasei cc1、Lactobacillus harbinensis cc5、Lactobacillus satsumensis cc12.

Abstract Background To explore the correlation between the preoperative systemic immune inflammation index (SII) and the prognosis of patients with gastric carcinoma (GC). Methods The clinical data of 771 GC patients surgically treated in the Department of Gastrointestinal Surgery, Qinghai University Affiliated Hospital from June 2010 to June 2015 were retrospectively analyzed, and their preoperative SII was calculated. The optimal cut-off value of preoperative SII was determined using the receiver operating characteristic (ROC) curve, the confounding factors between the two groups were eliminated using the propensity score matching (PSM) method, and the correlation between preoperative SII and clinicopathological characteristics was assessed by chi-square test. Moreover, the overall survival was calculated using Kaplan-Meier method, the survival curve was plotted, and log-rank test was performed for the significance analysis between the curves. Univariate and multivariate analyses were also conducted using the Cox proportional hazards model. Results It was determined by the ROC curve that the optimal cut-off value of preoperative SII was 489.52, based on which 771 GC patients were divided into high SII (H-SII) group and low SII (L-SII) group, followed by PSM in the two groups. The results of Kaplan-Meier analysis showed that before and after PSM, the postoperative 1-, 3-, and 5-year survival rates in L-SII group were superior to those in H-SII group, and the overall survival rate had a statistically significant difference between the two groups (P < 0.05). Before PSM, preoperative SII [hazard ratio (HR) = 2.707, 95% confidence interval (CI) 2.074-3.533, P < 0.001] was an independent risk factor for the prognosis of GC patients. After 1:1 PSM, preoperative SII (HR = 2.669, 95%CI 1.881–3.788, P < 0.001) was still an independent risk factor for the prognosis of GC patients. Conclusions Preoperative SII is an independent risk factor for the prognosis of GC patients. The increase in preoperative SII in peripheral blood indicates a worse prognosis.

Abstract Background In recent years, immunotherapies and targeted therapies contribute to population-level improvement in NSCLC cancer-specific survival, however, the two novel therapeutic options have mainly benefit patients containing mutated driven genes. Thus, to explore other potential genes related with immunity or targeted therapies may provide novel options to improve survival of lung cancer patients without mutated driven genes. CTSF is unique in human cysteine proteinases. Presently, CTSF has been detected in several cell lines of lung cancer, but its role in progression and prognosis of lung cancer remains unclear. Methods CTSF expression and clinical datasets of lung cancer patients were obtained from GTEx, TIMER, CCLE, THPA, and TCGA, respectively. Association of CTSF expression with clinicopathological parameters and prognosis of lung cancer patients was analyzed using UALCAN and Kaplan–Meier Plotter, respectively. LinkedOmics were used to analyze correlation between CTSF and CTSF co-expressed genes. Protein–protein interaction and gene–gene interaction were analyzed using STRING and GeneMANIA, respectively. Association of CTSF with molecular markers of immune cells and immunomodulators was analyzed with Immunedeconv and TISIDB, respectively. Results CTSF expression was currently only available for patients with NSCLC. Compared to normal tissues, CTSF was downregulated in NSCLC samples and high expressed CTSF was correlated with favorable prognosis of NSCLC. Additionally, CTSF expression was correlated with that of immune cell molecular markers and immunomodulators both in LUAD and LUSC. Noticeably, high expression of CTSF-related CTLA-4 was found to be associated with better OS of LUAD patients. Increased expression of CTSF-related LAG-3 was related with poor prognosis of LUAD patients while there was no association between CTSF-related PD-1/PD-L1 and prognosis of LUAD patients. Moreover, increased expression of CTSF-related CD27 was related with poor prognosis of LUAD patients while favorable prognosis of LUSC patients. Conclusions CTSF might play an anti-tumor effect via regulating immune response of NSCLC.

Abstract Background Mitochondria have been shown to play vital roles during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) development. Currently, it is unclear whether mitochondrial DNA (mtDNA) variants, which define mtDNA haplogroups and determine oxidative phosphorylation performance and reactive oxygen species production, are associated with COVID-19 risk. Methods A population-based case–control study was conducted to compare the distribution of mtDNA variations defining mtDNA haplogroups between healthy controls (n = 615) and COVID-19 patients (n = 536). COVID-19 patients were diagnosed based on molecular diagnostics of the viral genome by qPCR and chest X-ray or computed tomography scanning. The exclusion criteria for the healthy controls were any history of disease in the month preceding the study assessment. MtDNA variants defining mtDNA haplogroups were identified by PCR-RFLPs and HVS-I sequencing and determined based on mtDNA phylogenetic analysis using Mitomap Phylogeny. Student’s t-test was used for continuous variables, and Pearson’s chi-squared test or Fisher’s exact test was used for categorical variables. To assess the independent effect of each mtDNA variant defining mtDNA haplogroups, multivariate logistic regression analyses were performed to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) with adjustments for possible confounding factors of age, sex, smoking and diseases (including cardiopulmonary diseases, diabetes, obesity and hypertension) as determined through clinical and radiographic examinations. Results Multivariate logistic regression analyses revealed that the most common investigated mtDNA variations (> 10% in the control population) at C5178a (in NADH dehydrogenase subunit 2 gene, ND2) and A249d (in the displacement loop region, D-loop)/T6392C (in cytochrome c oxidase I gene, CO1)/G10310A (in ND3) were associated with a reduced risk of severe COVID-19 (OR = 0.590, 95% CI 0.428–0.814, P = 0.001; and OR = 0.654, 95% CI 0.457–0.936, P = 0.020, respectively), while A4833G (ND2), A4715G (ND2), T3394C (ND1) and G5417A (ND2)/C16257a (D-loop)/C16261T (D-loop) were related to an increased risk of severe COVID-19 (OR = 2.336, 95% CI 1.179–4.608, P = 0.015; OR = 2.033, 95% CI 1.242–3.322, P = 0.005; OR = 3.040, 95% CI 1.522–6.061, P = 0.002; and OR = 2.890, 95% CI 1.199–6.993, P = 0.018, respectively). Conclusions This is the first study to explore the association of mtDNA variants with individual’s risk of developing severe COVID-19. Based on the case–control study, we concluded that the common mtDNA variants at C5178a and A249d/T6392C/G10310A might contribute to an individual’s resistance to developing severe COVID-19, whereas A4833G, A4715G, T3394C and G5417A/C16257a/C16261T might increase an individual’s risk of developing severe COVID-19.

High-purity and bulk Ta4AlC3 ceramics were successfully fabricated by spark plasma sintering (SPS) and subsequent heat treatment, using the raw materials including TaC and Ta2AlC powders. These raw materials were first synthesized by self-propagation high temperature synthesis from elements tantalum, aluminium and carbon black powders, followed by pressure-less sintering. The as-fabricated bulk Ta4AlC3 was relatively stable when subjected to heat treatment at elevated temperature of 1500°C. Moreover, prolonging the heat treatment time resulted in bigger grain sizes and higher densities of the Ta4AlC3. The flexural strength and the fracture toughness of the Ta4AlC3 fabricated by SPS were found to be 411MPa and 7.11MPa•m1/2, respectively. After the heat treatment at 1500°C for 8 h, the flexural strength and the fracture toughness of the Ta4AlC3 could reach 709MPa and 9.23MPa•m1/2, respectively. The special structural characteristics of the ternary ceramics and the increase of density after the heat treatment are the main reasons for the variation in mechanical properties of ternary ceramics.