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To explore the effect of different drying methods on the floral quality and volatile flavor compounds of Jinmudan tea flowers, three drying techniques were selected including vacuum freeze-drying (pre-freezing for 2 hours, freeze-dried for 6, 8, 10 hours, cold trap temperature −50 ℃, which were treatments 1, 2 and 3 respectively), hot air drying (the treatment time was 3, 4 and 5 hours, and the baking temperature was 75 ℃, which were treatments 4, 5 and 6 respectively), and natural drying (CK). The effects of these drying processes on sensory quality, chemical composition, amino acid profile, and volatile flavor compounds of tea flowers were analyzed. The results revealed that tea flowers dried using the vacuum freeze-drying method exhibited the best sensory quality, with a distinct honey aroma preserved. Among them, the tea flowers subjected to treatment 3 obtained the highest overall sensory evaluation score, along with higher levels of water extract, tea polyphenols, and caffeine content. Furthermore, they exhibited the highest total amino acid content, sweetness amino acid content, freshness amino acid content, and essential amino acid content. A total of 107 volatile compounds were identified across the 3 drying processes, with alcohols, alkanes, and ketones comprising the predominant volatile components. Hierarchical cluster analysis (HCA) based on principal component analysis (PCA) further classified the volatile substances into 4 groups corresponding to 3 drying methods. A partial least squares discriminant analysis (PLS-DA) model was established to select 35 volatile components with variable importance in projection (VIP) values greater than 1, indicating differential markers. Additionally, the volatile substance patchoulol was identified as unique to the CK group. In summary, vacuum freeze-drying is the most effective method for preserving the aroma and bioactive compounds of tea flowers, with treatment 3 demonstrating the optimal overall evaluation. This study provides a theoretical basis for exploring the effects of drying methods on the quality and flavor of tea flowers and their corresponding changes in volatile components.

The test time of impulse tunnels is short, and the heat flux transducers can be easily interfered in the test time. Thus the aerothermal test data analysis of impulse tunnels is complex and usually carried out manually, which leads to low efficiency and nonuniform standards. In this paper, the signals of heat transducers used in the 1 m gun/shock dual-mode impulse tunnel at the China Academy of Aerospace Aerodynamics were investigated. A series of key parameters, e.g., the FFT voltage profile, the correlation profile of nozzle total pressure and transducer heat flux, as well as the time derivative of the heat flux profile, were determined. The characterization capabilities of these parameters with respect to significant features, e.g., the start/end time of the nozzle flow, the time boundary of different operation modes and the effectiveness of the transducer profiles, were certified. Moreover, a profile effectiveness estimation model, a test time interval selection algorithm and a transducer valid time selection algorithm were developed based on convolutional neural networks and density-based clustering algorithms. Thereby the aerothermal test data of impulse tunnels can be analyzed automatically with these data-driven methods. The results show that the accuracy of the profile effectiveness estimation model is as high as 98%. According to the comparison between algorithm and manual results in dealing with 3 568 profiles, about 91% of the results show a difference of less than 10%, which implies that the data-driven method has the value of application to wind tunnel tests.

Abstract Background Metabolic abnormalities and immune inflammation are deeply involved in pulmonary vascular remodelling and the development of pulmonary hypertension (PH). However, the regulatory mechanisms of glycolysis in macrophages are still elusive. Cumulative evidence indicates that β-catenin plays a crucial role in metabolic reprogramming. This study aimed to investigate the effect of β-catenin on macrophage glycolysis in PH. Methods LPS-induced BMDMs were generated via in vitro experiments. A monocrotaline (MCT)-induced PH rat model was established, and the β-catenin inhibitor XAV939 was administered in vivo. The role of β-catenin in glycolysis was analysed. The degree of pulmonary vascular remodelling was measured. Results β-catenin was significantly increased in both in vitro and in vivo models. In LPS-induced BMDMs, β-catenin increased the levels of hexokinase 2 (HK2), phosphofructokinase (PFK), M2-pyruvate kinase (PKM2), lactate dehydrogenase (LDH), and lactate (LA) and the expression of inflammatory cytokines and promoted PASMC proliferation and migration in vitro. XAV939 decreased the level of glycolysis and downregulated the expression of inflammatory cytokines in vivo. MCT promoted pulmonary arterial structural remodelling and right ventricular hypertrophy, and XAV939 alleviated these changes. Conclusions Our findings suggest that β-catenin is involved in the development of PH by promoting glycolysis and the inflammatory response in macrophages. Inhibition of β-catenin could improve the progression of PH.

Abstract Background Salvia miltiorrhiza (Danshen, DS) and Radix Paeoniae Rubra (Chishao, CS) herbal pair (DS-CS) is a famous traditional Chinese combination which has been used as antithrombotic formular for centuries. However, there is still lack of sufficient scientific evidence to illustrate its underlying mechanisms. The purpose of this study is to investigate the antithrombotic effects of DS-CS extract in zebrafish and explore its possible mechanism of action. Methods The quality of traditional Chinese medicines DS and CS granules was evaluated using High Performance Liquid Chromatography (HPLC). Subsequently, the therapeutic effect of the DS-CS combination and its components, Salvianolic Acid A (SAA) and Paeoniflorin (PF), in various concentrations on thrombosis was experimentally validated. Moreover, the interaction between DS-CS and the thrombosis disease targets was analyzed through network pharmacology, predicting the potential antithrombotic mechanism of DS-CS. Molecular docking and in vivo zebrafish experiments were conducted to validate the predicted targets, with qRT-PCR utilized for target validation. Results DS-CS exhibited anti-thrombotic effect in zebrafish with concentrations ranging from 25 to 300 μg/mL. The co-administration of PF and SAA at 25 μg/mL each revealed a synergistic antithrombotic effect exceeding that of individual components when contrasted with PHZ treatment. Protein–protein interaction (PPI) analysis identified key genes, including Albumin (ALB), Proto-oncogene tyro-sine-protein kinase Src (SRC), Matrix metalloproteinase-9 (MMP9), Caspase-3 (CASP3), Epidermal growth factor receptor (EGFR), Fibroblast growth factor 2 (FGF2), Vascular endothelial growth factor receptor 2 (KDR), Matrix metalloprotein-ase-2(MMP2), Thrombin (F2), and Coagulation factor Xa (F10), associated with the antithrombotic action of PF and SAA. Furthermore, KEGG pathway analysis indicated involvement of lipid metabolism and atherosclerosis pathways. Molecular docking revealed strong binding of PF and SAA to pivotal hub genes, such as SRC, EGFR, and F10. The experimental findings demonstrated that DS-CS could upregulate the mRNA expression levels of EGFR while inhibiting F10 and SRC mRNA levels, thereby ameliorating thrombotic conditions. Conclusion This research provided valuable insights into the potential mechanisms underlying the antithrombotic activity of DS-CS. Our findings suggested that PF and SAA could be the key active ingredients responsible for this activity. The antithrombotic effects of DS-CS appeared to be mediated through the regulation of mRNA expression of SRC, EGFR, and F10. These results enhanced our understanding of DS-CS's therapeutic potential and lay the groundwork for future studies to further elucidate its mechanisms of action.

Abstract Background Patients with pancreatic ductal adenocarcinoma (PDAC) display an altered oral, gastrointestinal, and intra-pancreatic microbiome compared to healthy individuals. However, knowledge regarding the bile microbiome and its potential impact on progression-free survival in PDACs remains limited. Methods Patients with PDAC (n = 45), including 20 matched pairs before and after surgery, and benign controls (n = 16) were included prospectively. The characteristics of the microbiomes of the total 81 bile were revealed by 16 S-rRNA gene sequencing. PDAC patients were divided into distinct groups based on tumor marker levels, disease staging, before and after surgery, as well as progression free survival (PFS) for further analysis. Disease diagnostic model was formulated utilizing the random forest algorithm. Results PDAC patients harbor a unique and diverse bile microbiome (PCoA, weighted Unifrac, p = 0.038), and the increasing microbial diversity is correlated with dysbiosis according to key microbes and microbial functions. Aliihoeflea emerged as the genus displaying the most significant alteration among two groups (p

Objective The object of this study was to investigate the effect of replacing soybean meal with Clostridium autoethanogenum protein (CAP) in broiler diets on growth performance, blood indicators, antioxidant capacity, and immune function. Methods A total of 180 Arbor Acres broilers were randomly divided into three treatments, each treatment with six replicates and 10 broilers per replicate for a 42-day feeding trial. The control group (CON) was fed corn-soybean meal based diet. The CAP-1 and CAP-2 groups were considered to use CAP to replace 25% or 50% of soybean meal in the diet, respectively. The average daily gain and average daily feed intake of broilers at 1 to 21 d, 22 to 42 d, and 1 to 42 d were measured, and the feed conversion ratio was calculated. At the 42nd day of age, two broilers with similar weights and fasted for 12 h were selected in each replicate for blood collection from the brachial wing vein. The blood routine indicators, serum biochemical indicators, serum antioxidant capacity, and immunoglobulin content of broiler chickens were measured. Results Replacement of soybean meal with 25% (CAP-1) and 50% (CAP-2) CAP significantly increased the average daily gain of 22 to 42 d and 1 to 42 d and decreased the average daily feed intake and feed conversion rate (p

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

Abstract Transition metal chalcogenides have been identified as low-cost and efficient electrocatalysts to promote the hydrogen evolution reaction in alkaline media. However, the identification of active sites and the underlying catalytic mechanism remain elusive. In this work, we employ operando X-ray absorption spectroscopy and near-ambient pressure X-ray photoelectron spectroscopy to elucidate that NiS undergoes an in-situ phase transition to an intimately mixed phase of Ni3S2 and NiO, generating highly active synergistic dual sites at the Ni3S2/NiO interface. The interfacial Ni is the active site for water dissociation and OH* adsorption while the interfacial S acts as the active site for H* adsorption and H2 evolution. Accordingly, the in-situ formation of Ni3S2/NiO interfaces enables NiS electrocatalysts to achieve an overpotential of only 95 ± 8 mV at a current density of 10 mA cm−2. Our work highlighted that the chemistry of transition metal chalcogenides is highly dynamic, and a careful control of the working conditions may lead to the in-situ formation of catalytic species that boost their catalytic performance.

Abstract Archaea possess characteristic membrane-spanning lipids that are thought to contribute to the adaptation to extreme environments. However, the biosynthesis of these lipids is poorly understood. Here, we identify a radical S-adenosyl-L-methionine (SAM) enzyme that synthesizes glycerol monoalkyl glycerol tetraethers (GMGTs). The enzyme, which we name GMGT synthase (Gms), catalyzes the formation of a C(sp3)–C(sp3) linkage between the two isoprenoid chains of glycerol dialkyl glycerol tetraethers (GDGTs). This conclusion is supported by heterologous expression of gene gms from a GMGT-producing species in a methanogen, as well as demonstration of in vitro activity using purified Gms enzyme. Additionally, we show that genes encoding putative Gms homologs are present in obligate anaerobic archaea and in metagenomes obtained from oxygen-deficient environments, and appear to be absent in metagenomes from oxic settings.

Objective Given the distinct physiological and societal traits between women and men, we propose that there are distinct risk factors for lumbar degenerative disc disease surgeries, including lumbar disc herniation (LDH) and lumbar spinal stenosis (LSS), in middle‐aged and older populations. However, few studies have focused on middle‐aged and older women. This study aims to identify these risk factors specifically in this population. Methods In this case–control study, the study group comprised 1202 women aged ≥ 45 years who underwent operative treatment of lumbar degenerative disc disease (LDH, n = 825; LSS, n = 377), and the control group comprised 1168 women without lumbar disease who visited a health examination clinic during the same period. The study factors included demographics (age, body mass index [BMI], smoking, labor intensity, and genetic history), female‐specific factors (menopausal status, number of deliveries, cesarean section, and simple hysterectomy), surgical history (number of abdominal surgeries, hip joint surgery, knee joint surgery, and thyroidectomy), and systemic diseases (hypercholesterolemia, hypertriglyceridemia, hyper‐low‐density lipoprotein cholesterolemia, hypertension, diabetes, cardiovascular disease, and cerebrovascular disease). Multivariate binary logistic regression analysis was used to calculate the odds ratio (OR) and 95% confidence interval (95% CI) of associated factors. Results The risk factors for surgical treatment of LDH in middle‐aged and older women included BMI (OR = 1.603), labor intensity (OR = 1.189), genetic history (OR = 2.212), number of deliveries (OR = 1.736), simple hysterectomy (OR = 2.511), hypertriglyceridemia (OR = 1.932), and hyper‐low‐density lipoprotein cholesterolemia (OR = 2.662). For surgical treatment of LSS, the risk factors were age (OR = 1.889), BMI (OR = 1.671), genetic history (OR = 2.134), number of deliveries (OR = 2.962), simple hysterectomy (OR = 1.968), knee joint surgery (OR = 2.527), hypertriglyceridemia (OR = 1.476), hyper‐low‐density lipoprotein cholesterolemia (OR = 2.413), and diabetes (OR = 1.643). Cerebrovascular disease was a protective factor against surgery for LDH (OR = 0.267). Conclusions BMI, genetic history, number of deliveries, simple hysterectomy, hypertriglyceridemia, and hyper‐low‐density lipoprotein cholesterolemia were independent risk factors for surgical treatment of both LDH and LSS in middle‐aged and older women. Two disparities were found: labor intensity was a risk factor for LDH patients, and knee joint surgery and diabetes were risk factors for LSS patients.

Abstract Background Numerous meta-analyses have explored the association between the triglyceride-glucose (TyG) index and diverse health outcomes, yet the comprehensive assessment of the scope, validity, and quality of this evidence remains incomplete. Our aim was to systematically review and synthesise existing meta-analyses of TyG index and health outcomes and to assess the quality of the evidence. Methods A thorough search of PubMed, EMBASE, and Web of Science databases was conducted from their inception through to 8 April 2024. We assessed the quality of reviews using A Measurement Tool to Assess Systematic Reviews (AMSTAR) and the certainty of the evidence using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) system. This study was registered with PROSPERO (CRD: 42024518587). Results Overall, a total of 95 associations from 29 meta-analyses were included, investigating associations between TyG index and 30 health outcomes. Of these, 83 (87.4%) associations were statistically significant (P

This article aimed to find effective modeling methods to predict the extraction rate of safflower seed oil by subcritical CO2 extraction, and optimize its extraction process conditions. Based on single-factor experiments, Box-Behnken experimental design was adopted to study the effects of extraction pressure, separation temperature, and extraction time on the extraction rate of safflower seed oil. Response surface methodology (RSM) and artificial neural network (ANN) were used to model and analyze the same experiment. The process conditions were optimized using RSM numerical optimization, ANN, and the combination of artificial neural network and genetic algorithm (ANN-GA). The results showed that both RSM and ANN models could accurately predict the extraction rate. However, by comparing the determination coefficient (R2), mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean square error (RMSE) values of the two models, it was concluded that the ANN model (R2=0.9966) had a better predictive effect than the RSM model (R2=0.9950). The optimal extraction conditions and extraction rate determined by ANN-GA were as follows: Extraction pressure of 19.04 MPa, separation temperature of 55.50 °C, extraction time of 134.98 min, and extraction rate of 23.52%. The study showed that both RSM and ANN methods could be used for modeling and optimization of subcritical CO2 extraction of safflower seed oil, but ANN had better prediction accuracy and fitting ability.

Xanthomonas spp. cause severe bacterial diseases. However, effective strategies for prevention and management of these diseases are scarce. Thus, it is necessary to improve the efficiency of control of diseases caused by Xanthomonas. In this study, Xanthomonas oryzae pv. oryzae (Xoo), which causes rice bacterial leaf blight, has been studied as a representative. A transposon insertion library of Xoo, comprising approximately 200,000 individual insertion mutants, was generated. Transposon sequencing data indicated that the mariner C9 transposase mapped at 35.7–36.4% of all potential insertion sites, revealing 491 essential genes required for the growth of Xoo in rich media. The results show that, compared to the functions of essential genes of other bacteria, the functions of some essential genes of Xoo are unknown, 25 genes might be dangerous for the Xanthomonas group, and 3 are specific to Xanthomonas. High-priority candidates for developing broad-spectrum, Xanthomonas-specific, and environment-friendly bactericides were identified in this study. In addition, this study revealed the possible targets of dioctyldiethylenetriamine using surface plasmon resonance (SPR) in combination with high performance liquid chromatography–mass spectrometry (HPLC–MS). The study also provided references for the research of some certain bactericides with unknown anti-bacterial mode of action. In conclusion, this study urged a better understanding of Xanthomonas, provided meaningful data for the management of bacterial leaf blight, and disclosed selected targets of a novel bactericide.

Visual perception is vital for people’s spatial experience. Many factors correlate with visual perception including spatial size, material, color, and geometry. However, studies systematically exploring spatial size are sparse, especially with regard to the interactions between the factors of spatial size. In this study, 15 indoor virtual reality environments with five widths and three heights were used to examine the influence of spatial size on visual perception. The study adopted a preference survey as the primary data-gathering tool assessed using a factorial analysis of variance. The results revealed that the influence of width and height on peoples’ preference levels for the indoor virtual reality environments was significant. However, the preference level did not always improve with an increase in width and/or height. A certain spatial size may enhance or contradict visual perception, but changing the width and height does not always exert a significantly different effect on the preference evaluation for the virtual reality environment. This study proposes a new idea that an indoor virtual environment that can adjust its spatial size can be used as a supplement to improve the quality of a real environment.

Objective: To determine the active components of Eupolyphaga sinensis Walker (Tu Bie Chong) and explore the mechanisms underlying its fracture-healing ability. Methods: A modified Einhorn method was used to develop a rat tibial fracture model. Progression of bone healing was assessed using radiological methods. Safranin O/fast green and CD31 immunohistochemical staining were performed to evaluate the growth of bone cells and angiogenesis at the fracture site. Methylthiazoletetrazolium blue and wound healing assays were used to analyze cell viability and migration. The Transwell assay was used to explore the invasion capacity of the cells. Tubule formation assays were used to assess the angiogenesis capacity of human vascular endothelial cells (HUVECs). qRT-PCR was used to evaluate the changes in gene transcription levels. Results: Tu Bie Chong fraction 3 (TF3) significantly shortened the fracture healing time in model rats. X-ray results showed that on day 14, fracture healing in the TF3 treatment group was significantly better than that in the control group (P = .0086). Tissue staining showed that cartilage growth and the number of H-shaped blood vessels at the fracture site of the TF3 treatment group were better than those of the control group. In vitro, TF3 significantly promoted the proliferation and wound healing of MC3T3-E1s and HUVECs (all P

This study aims to propose a decision-making method based on artificial potential fields (APFs) and finite state machines (FSMs) in emergency conditions. This study presents a decision-making method based on APFs and FSMs for emergency conditions. By modeling the longitudinal and lateral potential energy fields of the vehicle, the driving state is identified, and the trigger conditions are provided for path planning during lane changing. In addition, this study also designed the state transition rules based on the longitudinal and lateral virtual forces. It established the vehicle decision-making model based on the finite state machine to ensure driving safety in emergency situations. To illustrate the performance of the decision-making model by considering APFs and finite state machines. The version of the model in the co-simulation platform of MATLAB and CarSim shows that the developed decision model in this study accurately generates driving behaviors of the vehicle at different time intervals. The contributions of this study are two-fold. A hierarchical vehicle state machine decision model is proposed to enhance driving safety in emergency scenarios. Mathematical models for determining the transition thresholds of lateral and longitudinal vehicle states are established based on the vehicle potential field model, leading to the formulation of transition rules between different states of autonomous vehicles (AVs).

Magnetoelectric dipoles have attracted global research attention due to its broadband, unidirectional, and high front-to-back ratio characteristics. This study implemented a co-simulation between a basic magnetoelectric dipole and its front feeding circuit through the step-by-step numerical extraction of its equivalent circuit model equipped with lumped and frequency-independent components. First, the series resonance subcircuit was derived from the series resonance point in the impedance of the magnetoelectric dipole. Second, the parallel resonance sub-circuit was achieved based on the parallel resonance point. By combining the series and parallel sub-circuits according to the sequence of their resonance frequency, the final form of the equivalent circuit for the basic magnetoelectric dipole was realized. Furthermore, to obtain the component values of the proposed circuit, a numerical fitting technique was adopted to accurately match the input impedance of the antenna and its equivalent circuit. A comparison of the circuit and antenna electromagnetic simulations showed that they agreed well with each other. Hence, the correctness and feasibility of the extraction process were verified. The overall results showed that the proposed circuit model can easily substitute for a basic magnetoelectric dipole in the implementation of antenna/circuit co-simulation in circuit simulators.

Abstract Gastric cancer (GC) stage and tissue differentiation affect treatment efficacy and prognosis, highlighting the importance of understanding the risk factors that affect these parameters. Therefore, this study analyzed risk factors affecting the GC stage and differentiation and the relationships between the cancer site and the sex and age of the patient. We collected clinical data from 6961 patients with GC, including sex, age, endoscopic lesion location, and pathological differentiation. Patients were grouped based on GC stage (early or advanced), differentiation (well or poorly differentiated), and lesion site (upper stomach [cardia and fundus], middle stomach [gastric body], and lower stomach [gastric antrum]). Differences in sex, age, location, stage, and degree of differentiation were assessed based on these groupings. Univariate analysis revealed that the disease location and differentiation significantly differed based on the GC stage (P

Shaped charge warhead is important for enhancing the damage performance of underwater weapons. This paper used finite element analysis software and based on JPC water penetration experiments to examine the influence of liner parameters (wall thickness, material), charge aspect ratio, and stand-off distance on the movement characteristics of JPC in water. The findings reveal that the head diameter of the JPC increases and experiences significant erosion after entering the water, the effective length of the JPC in water undergoes two distinct phases: a growth phase and a decrease phase, with the velocity of the JPC decaying exponentially. Increasing the liner thickness, stand-off distance and the charge aspect ratio can improve the erosion resistance and the velocity retention capacity of the JPC. The optimal ranges for liner thickness and stand-off distance are 0.0363Dk to 0.0545Dk (Dk is the charge diameter), the stand-off distance should be within 1.0Dk. After the charge aspect ratio higher than 1.25, the charge structure exerts minimal influence the movement characteristics of the JPC in water. Material density plays a crucial role in the velocity decay pattern of the JPC during penetration. JPC with higher densities exhibit superior velocity retention capabilities in water, with the velocity decay pattern converging if the densities are similar. Consequently, copper, tantalum and tungsten liners are deemed appropriate for underwater shaped charge warhead. Finally, the results will provide an important reference for the design of underwater shaped charge warhead.

Abstract Background This study aimed to determine the factors that contribute to the failure of bowel preparation in patients undergoing colonoscopy and to develop a risk prediction model. Methods A total of 1115 outpatients were included. Patients were randomly divided into two groups: the modeling group (669 patients) and the validation group (446 patients). In the modeling group, patients were further divided into two groups based on their success and failure in bowel preparation using the Boston Bowel Preparation Scale. A logistic regression analysis model was used to determine the risk factors of bowel preparation failure, which was subsequently visualized using an alignment diagram. Results After controlling for relevant confounders, multifactorial logistic regression results showed that age ≥ 60 years (OR = 2.246), male (OR = 2.449), body mass index ≥ 24 (OR = 2.311), smoking (OR = 2.467), chronic constipation (OR = 5.199), diabetes mellitus (OR = 5.396) and history of colorectal surgery (OR = 5.170) were influencing factors of bowel preparation failure. The area under the ROC curve was 0.732 in the modeling group and 0.713 in the validation group. According to the calibration plot, the predictive effect of the model and the actual results were in good agreement. Conclusions Age ≥ 60 years, male, body mass index ≥ 24, smoking, chronic constipation, diabetes mellitus, and history of colorectal surgery are independent risk factors for bowel preparation failure. The established prediction model has a good predictive efficacy and can be used as a simple and effective tool for screening patients at high risk for bowel preparation failure.

Abstract Background Cervical cancer poses a heavy health burden in China, with the second highest incidence and mortality rate among female tumors, yet human papillomavirus (HPV) vaccination rate among female university students remain remains low. This study conducted a cross-sectional survey to assess the degree of HPV vaccine hesitancy among female university students and to explore the potential association between knowledge, risk perception, trust, and HPV vaccine hesitancy. Methods A total of 1,438 female university students from four Chinese cities were recruited through stratified, multistage, cluster sampling method. The mediation model was constructed using the Bootstrap method, introducing trust and risk perception as mediating variables to examine the effect of knowledge on HPV vaccine hesitancy. Results The study found that 8.9% (95%CI:7.4%∼10.4%) of the female university students exhibited HPV vaccine hesitancy. Pearson’s correlation analysis revealed a negative association between vaccine hesitancy and knowledge, risk perception, and trust. The mediation model showed that knowledge had significant indirect effects on HPV vaccine hesitancy through trust (indirect effect: -0.224, 95% CI: -0.293 ∼ -0.167) and risk perception (indirect effect: -0.013, 95% CI: -0.033 ∼ -0.002). Conclusion HPV vaccine hesitancy among female university students has mitigated, but still needs to be addressed. In addition, trust and risk perception are mediators mediating the relationship between knowledge with HPV vaccine hesitancy. Therefore, there is a need to strengthen public health education to improve knowledge, with a particular focus on providing information about trust and risk perception to reduce HPV vaccine hesitancy.

The continuous drive for miniaturization and enhanced functionality in micro-electronic devices demands highly integrated circuit (IC) packaging. This trend leads to a dense network of micro-electronic packaging interconnections, facilitated by the reduction in traditional solder interconnection sizes. However, these advancements bring about significant challenges, including thermal expansion differences between materials used in the package and the presence of non-planar substrates. Such issues can lead to thermomechanical stresses in interconnections and warpage, resulting in serious reliability issues. In response, nanostructured compliant interconnections have emerged as a promising solution. These interconnections effectively manage thermal expansion variations and substrate non-coplanarity, mitigating the risks associated with miniaturization and high integration demands in IC packaging. This review explores the latest trends and advancements in developing nanostructured compliant interconnections for modern micro-electronics. The focus is on integrating various interconnection materials, including nanoparticles (via sintering), nanoporous materials, nanowires (NWs) and carbon nanotubes (CNTs). This integration aims to improve the performance and mechanical reliability of interconnections under extreme thermal loading conditions. Advanced bonding techniques and their significant impacts on interconnection reliability are also discussed. Additionally, the study provides insights into future developments of nanostructured compliant interconnections, guiding researchers toward specific technical areas for future exploration.

Abstract The advancement of Zn–Se batteries has been hindered by significant challenges, such as the sluggish kinetics of Se cathodes, limited Se loading, and uncontrollable formation of Zn dendrites. In this study, a bidirectional optimization strategy is devised for both cathode and anode to bolster the performance of Zn–Se batteries. A novel bowl‐in‐ball structured carbon (BIBCs) material is synthesized to serve as a nanoreactor, in which tin‐based materials are grown and derived in situ to construct cathodes and anodes. Within the cathode, the multifunctional host material (SnSe@BIBCs) exhibits large adsorption capacity for selenium, and demonstrates supreme catalytic properties and spatially confined characteristics toward the selenium reduction reaction (SeRR). On the anode, Sn@BIBCs displays triple‐induced properties, including the zincophilic of the internal metallic Sn, the homogenized spatial electric field from the 3D spatial structure, and the curvature effect of the bowl‐shaped carbon. Collectively, these factors induce preferential nucleation of Zn, ensuring its uniform deposition. As a result, the integrated Zn–Se battery system achieves a remarkable specific capacity of up to 603 mAh g−1 and an impressive energy density of 581 W kg−1, highlighting its tremendous potential for practical applications.

Summary: Lupus nephritis (LN), a severe complication of systemic lupus erythematosus (SLE), exhibits significant heterogeneity. Recent evidence suggests that non-immune factors contribute to end-organ damage, challenging the traditional view of LN solely arising from immune dysregulation. To investigate this, we employed autoimmune-prone Gnaq+/− mice receiving intraperitoneal pristane injections. Bone marrow transfer (BMT) distinguished the roles of immune versus non-immune cells. We observed that: (1) BMT from wild-type (WT) mice to Gnaq+/− recipients resulted in severe proteinuria and diffuse proliferative nephritis after pristane exposure; (2) GNAQ knockdown increased the expression of IFI16/Ifi202b and activated the NF-κB pathway in endothelial cells; and (3) increased IFI16 expression in human kidney biopsies correlated with proliferative LN. Taken together, these findings suggest that GNAQ acts as an inflammatory regulator in kidney endothelial cells via the IFI16/NF-κB pathway, potentially linking it to the development of LN in humans.

The mountainous areas of the Loess Plateau in China are crisscrossed with ravines, fragile ecological environment, and frequent landslide hazards. Landslides often cause building collapses and casualties, seriously affecting the sustainability of economic and social development in the region. In order to study the damage of loess landslides to village and town buildings, the paper takes the Xingwang landslide in Fugu County, Shaanxi Province, China as an example, and uses discrete element method and finite element method to study the dynamic process of landslide and its damage to houses. Firstly, the geological characteristics of the landslide were identified by means of investigation, surveying, engineering exploration and geotechnical testing. Secondly, a three-dimensional numerical model of the landslide area was established by using the particle flow code system (PFC3D). Finally, the entire movement process of the landslide was simulated, and the impact damage to houses induced from landslide was analyzed and predicted. The results show that the whole movement of the landslide lasted a total of 180 s, with a maximum average velocity of 2.01 m/s and a maximum average displacement of 73.7 m. The first and second rows of houses located at the foot of the landslide will suffer serious damage, with most bricks displacement ranging from 0.1 to 2.5 m and a maximum displacement of 10.3 m, posing a serious safety risk to the houses. Only a portion of the third row houses will be damaged, and the fourth row houses will not be threatened by landslide. By comparing with the prediction results of other methods and the current situation of buildings deformation, the results of this paper have a certain credibility. This study provides a numerical method for quantitative assessment of the risk and building damage for loess landslide, which can be used as a reference. It also provides technical support for formulating hazard prevention and reduction plans for the Xingwang landslide.

ObjectiveRecent studies have demonstrated that the Dietary Inflammatory Index (DII) is relevant to abnormal gut health. However, there is a lack of studies that have explicitly explored the link between fecal incontinence (FI) and DII. The current study aims to explore the relationship between DII and FI.MethodsThe cross-sectional study enrolled a total of 11,747 participants aged 20–85 from NHANES 2005–2010. Weighted logistic regression was conducted to evaluate the relationship between DII and FI, and restricted cubic spline (RCS) was employed to assess the dose-response relationship between DII and FI. Subgroup analyses were performed according to age, gender, race, and BMI.ResultDII levels were found to be significantly higher in patients with FI than in the normal population (p = 0.016). After adjusting for all covariates, DII was found to be significantly correlated with FI (model 2: Q4 vs. Q1, OR = 1.49, 95% CI: 1.04–2.14, p = 0.032, p for trend = 0.039). The dose-response curve revealed that there was no non-linear correlation between DII and FI (p-non-linear = 0.234). Subsequent subgroup analyses uncovered that DII was notably associated with FI in the old (Q4 vs. Q1, OR = 1.84, 95% CI: 1.07–3.18, p = 0.030), female (Q4 vs. Q1: OR = 2.02, 95% CI: 1.23–3.33, p = 0.008), non-Hispanic white (Q4 vs. Q1: OR = 1.70, 95% CI: 1.12–2.59, p = 0.015) populations.ConclusionDII was positively associated with FI, particularly among old, female and non-Hispanic white individuals. Decreasing daily dietary inflammatory levels may be an effective tactic to prevent FI, but the precise mechanisms need to be further investigated.

BackgroundAccumulating evidence reveals mitochondrial dysfunction exacerbates intestinal barrier dysfunction and inflammation. Despite the growing knowledge of mitochondrial dysfunction and ulcerative colitis (UC), the mechanism of mitochondrial dysfunction in UC remains to be fully explored.MethodsWe integrated 1137 UC colon mucosal samples from 12 multicenter cohorts worldwide to create a normalized compendium. Differentially expressed mitochondria-related genes (DE-MiRGs) in individuals with UC were identified using the “Limma” R package. Unsupervised consensus clustering was utilized to determine the intrinsic subtypes of UC driven by DE-MiRGs. Weighted gene co-expression network analysis was employed to investigate module genes related to UC. Four machine learning algorithms were utilized for screening DE-MiRGs in UC and construct MiRGs diagnostic models. The models were developed utilizing the over-sampled training cohort, followed by validation in both the internal test cohort and the external validation cohort. Immune cell infiltration was assessed using the Xcell and CIBERSORT algorithms, while potential biological mechanisms were explored through GSVA and GSEA algorithms. Hub genes were selected using the PPI network.ResultsThe study identified 108 DE-MiRGs in the colonic mucosa of patients with UC compared to healthy controls, showing significant enrichment in pathways associated with mitochondrial metabolism and inflammation. The MiRGs diagnostic models for UC were constructed based on 17 signature genes identified through various machine learning algorithms, demonstrated excellent predictive capabilities. Utilizing the identified DE-MiRGs from the normalized compendium, 941 patients with UC were stratified into three subtypes characterized by distinct cellular and molecular profiles. Specifically, the metabolic subtype demonstrated enrichment in epithelial cells, the immune-inflamed subtype displayed high enrichment in antigen-presenting cells and pathways related to pro-inflammatory activation, and the transitional subtype exhibited moderate activation across all signaling pathways. Importantly, the immune-inflamed subtype exhibited a stronger correlation with superior response to four biologics: infliximab, ustekinumab, vedolizumab, and golimumab compared to the metabolic subtype.ConclusionThis analysis unveils the interplay between mitochondrial dysfunction and the immune microenvironment in UC, thereby offering novel perspectives on the potential pathogenesis of UC and precision treatment of UC patients, and identifying new therapeutic targets.

BackgroundThe cGAS-STING axis-mediated type I interferon pathway is a crucial strategy for host defense against DNA virus infection. Numerous evasion strategies developed by the pseudorabies virus (PRV) counteract host antiviral immunity. To what extent PRV-encoded proteins evade the cGAS-STING signaling pathway is unknown.MethodsUsing US2 stably expressing cell lines and US2-deficient PRV model, we revealed that the PRV tegument protein US2 reduces STING protein stability and downregulates STING-mediated antiviral signaling.ResultsTo promote K48-linked ubiquitination and STING degradation, US2 interacts with the LBD structural domain of STING and recruits the E3 ligase TRIM21. TRIM21 deficiency consistently strengthens the host antiviral immune response brought on by PRV infection. Additionally, US2-deficient PRV is less harmful in mice.ConclusionsOur study implies that PRV US2 inhibits IFN signaling by a new mechanism that selectively targets STING while successfully evading the host antiviral response. As a result, the present study reveals a novel strategy by which PRV evades host defense and offers explanations for why the Bartha-K61 classical vaccine strain failed to offer effective defense against PRV variant strains in China, indicating that US2 may be a key target for developing gene-deficient PRV vaccines.

In China, fence net aquaculture practices have been established in some subsidence waters that have been formed in coal mining subsidence areas. Within this dynamic ecological context, diverse fish species grow continuously until being harvested at the culmination of their production cycle. The purpose of this study was to investigate diverse factors influencing the bioavailability and distribution of mercury (Hg) and methylmercury (MeHg), which have high physiological toxicity in fish, in the Guqiao coal mining subsidence area in Huainan, China. Mercury and MeHg were analyzed in 38 fish samples of eight species using direct mercury analysis (DMA-80) and gas chromatography–cold vapor atomic fluorescence spectrometry (GC-CVAFAS). The analysis results show that the ranges of Hg and MeHg content and methylation rate in the fish were 7.84–85.18 ng/g, 0.52–3.52 ng/g, and 0.81–42.68 %, respectively. Meanwhile, conclusions are also summarized as following: (1) Monophagous herbivorous fish that were fed continuously in fence net aquaculture areas had higher MeHg levels and mercury methylation rates than carnivorous fish. Hg and MeHg contents were affected by different feeding habits of fish. (2) Bottom-dwelling fish show higher MeHg levels, and habitat selection in terms of water depth also partially affected the MeHg content of fish. (3) The effect of fence net aquaculture on methylation of fish in subsidence water is mainly from feed and mercury-containing bottom sediments. However, a time-lag is observed in the physiological response of benthic fishes to the release of Hg from sediments. Our findings provides baseline reference data for the ecological impact of fence net aquaculture in waters affected by soil subsidence induced by coal mining in China. Prevalent environmental contaminants within coal mining locales, notably Hg, may infiltrate rain-induced subsidence waters through various pathways.

ObjectiveThis study investigates the efficacy of training methodologies aimed at mitigating asymmetries in lower limb strength and explosiveness among basketball players.MethodsThirty male university basketball athletes were enrolled in this research. Initial assessments were made regarding their physical attributes, strength, and explosiveness. Subsequently, the participants were randomly allocated into two groups: an experimental group (EG, n = 15) and a control group (CG, n = 15). Over 10 weeks, the EG engaged in a unilateral compound training regimen, incorporating resistance training exercises such as split squats, Bulgarian split squats, box step-ups, and single-leg calf raises (non-dominant leg: three sets of six repetitions; dominant leg: one set of six repetitions) and plyometric drills including lunge jumps, single-leg hops with back foot raise, single-leg lateral jumps, and single-leg continuous hopping (non-dominant leg: three sets of 12 repetitions; dominant leg: one set of 12 repetitions). The CG continued with their standard training routine. Assessments of limb asymmetry and athletic performance were conducted before and after the intervention to evaluate changes.Results1) Body morphology assessments showed limb length and circumference discrepancies of less than 3 cm. The initial average asymmetry percentages in the single-leg countermovement jump (SLCMJ) for jump height, power, and impulse were 15.56%, 12.4%, and 4.48%, respectively. 2) Post-intervention, the EG demonstrated a significant reduction in the asymmetry percentages of SLCMJ height and power (p < 0.01), along with improvements in the isometric mid-thigh pull (IMTP) test metrics (p < 0.05). 3) The EG also showed marked enhancements in the double-leg countermovement jump (CMJ) and standing long jump (SLJ) outcomes compared to the CG (p < 0.01), as well as in squat performance (p < 0.05).ConclusionThe 10-week unilateral compound training program effectively reduced the asymmetry in lower limb strength and explosiveness among elite male university basketball players, contributing to increased maximal strength and explosiveness.

Laminated glass has been widely used as safety glass for decades owing to its remarkable post-breakage load-bearing capacity. The post-breakage behaviour of laminated glass is mainly affected by several key factors such as the interlayer property, the adhesion property of the glass-interlayer interface, and the size of glass fragments. In this study, the adhesion properties of polyvinyl butyral (PVB) laminated glass under high-speed uniaxial tension were studied by through-cracked tensile (TCT) tests. Two adhesion grades (i.e., BG-R15 medium adhesion grade and BG-R20 high adhesion grade) PVB-laminated glass and three loading rates (i.e., 0.1m/s, 0.5m/s, and 5m/s) were considered in the tests. The delamination behaviour of PVB-laminated glass was modelled using a numerical cohesive zone model (CZM) to accurately calibrate the interfacial adhesion properties. It was found that BG-R15 PVB-laminated glass exhibits a progressive delamination behaviour under high-speed loading, which results in a stable but low post-cracking force, whereas the delamination was significantly constrained for BG-R20 PVB-laminated glass, which leads to a higher post-cracking force but very poor deformability. The deformability of high adhesion grade laminated glass increases with the crack number since more PVB participates into the stretching of cracked laminated glass. The interfacial adhesion property shows a significant rate effect, with the bonding strength and energy release rate of BG-R15 PVB-laminated glass increase by nearly 25% and 50%, respectively, as the loading rate increases from 0.1m/s to 5m/s. In general, the energy dissipation capacity of the BG-R15 PVB-laminated glass is much higher than that of the BG-R20 PVB-laminated glass. This study can provide a valuable reference for the design of laminated glass under blast or impact loads.

National parks play a crucial role in global biodiversity preservation, with China’s Giant Panda National Park (GPNP) serving as a key stronghold for protecting unique flora and fauna endemic to diverse mountainous regions. This study focused on unraveling the dynamics of diversity within local giant panda populations and their sympatric species in the Ya’an section of the GPNP. Five specific local population patches (LPPs) were selected as subjects, utilizing data from the 4th National Giant Panda Survey. Through identification, classification, and analysis of observed species within each LPP, α and β diversity patterns were revealed, leading to actionable recommendations. A comprehensive record of 34 species spanning 5 orders and 16 families was documented. Notably, 8 species were under the first-class of the National Key Protected Wildlife List in China, and the IUCN Red List has identified 3 species – Rhinopithecus roxellana, Moschus berezovskii, and Ailurus styani – as endangered, showing its high biodiversity and conservation significance. While α-diversity assessment highlighted the DaxianglingA2 (DXLA2) with the highest Shannon-Wiener and Simpson’s indices, the QionglaishanA3 (QLSA3) exhibited greater species richness. However, these differences lacked statistical significance (P > 0.05). The Jaccard similarity coefficient indicated a stronger turnover process compared to nestedness. The dominance of turnover in total β-diversity accentuated the importance of encompassing all five LPPs in conservation strategies. The study underscored the imperative of conservation management for each LPP, with a focus on enhancing habitat connectivity between disparate small LPPs to prevent species extinction by fostering species exchange and gene flow. This pioneering research shed light on spatial utilization patterns and diversity drivers for local giant panda populations and their sympatric species within the GPNP. It provides valuable references to appraise conservation strategy effectiveness and offers scientific backing to optimize biodiversity conservation and management within national parks and protected areas.

Abstract Energy enterprises are an important basis for ensuring national energy security and economic development, and their social responsibility is closely related to addressing environmental concerns such as over-exploitation of resources and excessive discharge of pollution. The casual effects of management compensation incentives on corporate social & environmental responsibility are explored based on the panel data of Chinese energy enterprises from 2010 to 2021 using the instrumental variable estimation method. The results indicate that management salary incentives can significantly promote the implementation of corporate social responsibility and environmental responsibility, while the proportion of management shareholding will reduce corporate social responsibility (CSR) and environmental responsibility (CER) activities. In addition, there are obvious industry differences and corporate ownership differences in the effects of management compensation incentives on CSR and CER. The negative impact of equity incentives on CSR and CER is even more pronounced in the electricity and environmental industry, and salary incentives have a greater positive effect on CSR for state-owned enterprises. The study shows that enterprises should focus on the salary incentive of managers and appropriately reduce their shareholding. The government should pay attention to the development of state-owned energy enterprises, and limit the shareholding ratio of management through policies and other incentive systems.

Abstract Background Sofosbuvir/Velpatasvir (Epclusa, ECS) is the first pan-genotype direct-acting antiviral agent (DAA) for hepatitis C virus (HCV) infection, and Danoprevir (DNV) is the first DAA developed by a Chinese local enterprise, which is suitable for combined use with other drugs to treat genotype 1b chronic hepatitis C. However, previous reports have never compared the real-world data of ECS and DNV. Patients and methods 178 chronic hepatitis C patients were retrospectively recruited, and 94cases were accepted with Sofosbuvir/Velpatasvir ± Ribavirin (ECS group), and others (n = 84 treated with DNV combination therapy (DNV group). The HCV genotype, virological response, adverse effects and some laboratory biochemical indexes were contrasted between above two groups in the real world study. Results DNV group had significantly lower level of alpha-fetoprotein (AFP), lower rates of decompensated cirrhosis ( P

Abstract Background DNMT3L is a crucial DNA methylation regulatory factor, yet its function and mechanism in hepatocellular carcinoma (HCC) remain poorly understood. Bioinformatics-based big data analysis has increasingly gained significance in cancer research. Therefore, this study aims to elucidate the role of DNMT3L in HCC by integrating big data analysis with experimental validation. Methods Dozens of HCC datasets were collected to analyze the expression of DNMT3L and its relationship with prognostic indicators, and were used for molecular regulatory relationship evaluation. The effects of DNMT3L on the malignant phenotypes of hepatoma cells were confirmed in vitro and in vivo. The regulatory mechanisms of DNMT3L were explored through MSP, western blot, and dual-luciferase assays. Results DNMT3L was found to be downregulated in HCC tissues and associated with better prognosis. Overexpression of DNMT3L inhibits cell proliferation and metastasis. Additionally, CDO1 was identified as a target gene of DNMT3L and also exhibits anti-cancer effects. DNMT3L upregulates CDO1 expression by competitively inhibiting DNMT3A-mediated methylation of CDO1 promoter. Conclusions Our study revealed the role and epi-transcriptomic regulatory mechanism of DNMT3L in HCC, and underscored the essential role and applicability of big data analysis in elucidating complex biological processes.

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

Abstract To develop a fast and effective image deblurring method, the blind recovery of motion‐blurred images based on DeblurGAN(GAN, Generative Adversarial Networks) is researched.Firstly, the number of residual modules in the DeblurGAN network is changed, and an attempt is made to optimize the network structure to achieve better results in the blind recovery of motion‐blurred images. Secondly, an image deblurring method based on the improved DeblurGAN network is proposed.This paper makes corresponding adjustments to the generator and discriminator networks to change their input and output size to 512 × 512 while keeping the overall structure of the network unchanged, and the experimental results show that the quality of the restored images has been greatly improved. In addition, the images were divided into four classes of images,to achieve improved restoration of blurred images with specific content. Experimental results on the benchmark GoPro dataset validate that the improved DeblurGAN achieves more than 1.5 dB improvement than DeblurGAN in terms of peak signal‐to‐noise ratio (PSNR) as trained utilizing the same amount of data, and structural similarity assessment (SSIM) evaluation means and maximum values increased between 0.2 and 0.3. The improved DeblurGAN is more effective in terms of both blur removal and detail recovery.

Given its capacity to generate 2-D fine images of observation areas, very high resolution (VHR) synthetic aperture radar (SAR) has become increasingly popular in myriad fields, including remote sensing, geoscience, and surveillance. In this article, we present a comprehensive overview of VHR SAR systems and imaging to highlight the related research and promote further development. First, we provide a summary of VHR SAR applications and summarize the typical airborne and spaceborne systems. Subsequently, a detailed overview is provided to demonstrate the range VHR technologies by introducing dechirp processing, stepped frequency, and microwave photonic. In addition, VHR imaging methods on different platforms, i.e., ideal trajectory, airborne, and spaceborne, are reviewed. Finally, the challenges and prospects of VHR SAR are presented to inform future research directions. This work provides a valuable resource to improve the system design and signal processing of VHR SAR.

The study of non-axisymmetric fuel dispersal and detonation can provide reference for the prevention of industrial cloud explosion accidents and the design of fuel air explosive (FAE). The concentration and detonation fields of 85 kg cylindrical and fan-shaped fuel are investigated by experiments and numerical simulations. A dynamic model of the whole process for fuel dispersal and detonation is built. The concentration distribution of fuel is used as the initial condition to calculate the detonation stage, thus solving the initial value problem of detonation field. The phase and component changes of fuel cloud at different locations are compared. The fuel cloud is divided into directions of 0°, 90°, 135° and 180°. The results show that the maximum cloud radius is 20.94 m in 135° and the minimum is 12.04 m in 0°. The diameter of the detonation fireball is 53.6 m, and the peak temperature is 3455 K. The highest peak overpressure is 3.44 MPa in 0° and the lowest is 2.97 MPa in 135°. The proportion of liquid phase in 0° is 22.90%, and the fuel loss is 11.8% and 9% higher than that in 135° and cylindrical charge, respectively. The stable propagation distance of blast wave in 135° is 42.50% longer than 0° and 28.37% longer than cylindrical charge.

Abstract Background Metabotropic glutamate receptor 5 (mGluR5) is involved in regulating integrative brain function and synaptic transmission. Aberrant mGluR5 signaling and relevant synaptic failure play a key role in the initial pathophysiological mechanism of Alzheimer’s disease (AD). The study aims to investigate the association between mGluR5 availability and AD’s biomarkers and cognitive function. Methods We examined 35 individuals with mGluR5 tracer [18F]PSS232 to assess mGluR5 availability, and with [18F]Florbetapir PET to assess global amyloid deposition, and [18F]FDG PET to assess glucose metabolism. The plasma neurofilament light (NfL) and p-tau181 levels in a subset of individuals were measured (n = 27). The difference in mGluR5 availability between the AD and normal control (NC) groups was explored. The associations of mGluR5 availability with amyloid deposition, glucose metabolism, gray matter volume (GMV), neuropsychological assessment scores, and plasma biomarkers were analyzed. Results The mGluR5 availability was significantly reduced in AD patients’ hippocampus and parahippocampal gyrus compared to NCs. Global amyloid deposition was positively associated with mGluR5 availability in the AD group and reversely associated in the NC group. The mGluR5 availability was positively correlated with regional glucose metabolism in the overall and stratified analyses. The availability of mGluR5 in the hippocampus and parahippocampal gyrus demonstrated a strong relationship with the GMV of the medial temporal lobe, plasma p-tau181 or NfL levels, and global cognitive performance. Conclusions [18F]PSS232 PET can quantify the changes of mGluR5 availability in the progression of AD. mGluR5 availability correlated not only with neuropathological biomarkers of AD but also with neurodegenerative biomarkers and cognitive performance. mGluR5 may be a novel neurodegenerative biomarker, and whether mGluR5 could be a potential therapeutic target for AD needs to be further studied.

The sensory perception of food is a dynamic process, which is closely related to the release of flavor substances during oral processing. It's not only affected by the food material, but also subjected to the individual oral environment. To explore the oral processing characteristics of soft-boiled chicken, the sensory properties, texture, particle size, viscosity, characteristic values of electronic nose and tongue of different chicken samples were investigated. The correlation analysis showed that the physical characteristics especially the cohesiveness, springiness, resilience of the sample determined oral processing behavior. The addition of chicken skin played a role in lubrication during oral processing. The particle size of the bolus was heightened at the early stage, and the fluidity was enhanced in the end, which reduced the chewing time to the swallowing point and raised the aromatic compounds signal of electronic nose. But the effect of chicken skin on chicken thigh with relatively high fat content, was opposite in electronic nose, which had a certain masking effect on the perception of umami and sweet taste. In conclusion, fat played a critical role in chicken oral processing and chicken thigh had obvious advantages in comprehensive evaluation of soft-boiled chicken, which was more popular among people.

Abstract 3D printing can produce intuitive, precise, and personalized anatomical models, providing invaluable support for precision medicine, particularly in areas like surgical training and preoperative planning. However, conventional 3D printed models are often significantly more rigid than human organs and cannot undergo repetitive resection, which severely restricts their clinical value. Here we report the stereolithographic 3D printing of personalized liver models based on physically crosslinked self-healing elastomers with liver-like softness. Benefiting from the short printing time, the highly individualized models can be fabricated immediately following enhanced CT examination. Leveraging the high-efficiency self-healing performance, these models support repetitive resection for optimal trace through a trial-and-error approach. At the preliminary explorative clinical trial (NCT06006338), a total of 5 participants are included for preoperative planning. The primary outcomes indicate that the negative surgery margins are achieved and the unforeseen injuries of vital vascular structures are avoided. The 3D printing of liver models can enhance the safety of hepatic surgery, demonstrating promising application value in clinical practice.

Abstract Unsupervised domain adaptation transfers empirical knowledge from a label-rich source domain to a fully unlabeled target domain with a different distribution. A core idea of many existing approaches is to reduce the distribution divergence between domains. However, they focused only on part of the discrimination, which can be categorized into optimizing the following four objectives: reducing the intraclass distance between domains, enlarging the interclass distances between domains, reducing the intraclass distances within domains, and enlarging the interclass distances within domains. Moreover, because few methods consider multiple types of objectives, the consistency of data representations produced by different types of objectives has not yet been studied. In this paper, to address the above issues, we propose a zeroth- and first-order difference discrimination (ZFOD) approach for unsupervised domain adaptation. It first optimizes the above four objectives simultaneously. To improve the discrimination consistency of the data across the two domains, we propose a first-order difference constraint to align the interclass differences across domains. Because the proposed method needs pseudolabels for the target domain, we adopt a recent pseudolabel generation method to alleviate the negative impact of imprecise pseudolabels. We conducted an extensive comparison with nine representative conventional methods and seven remarkable deep learning-based methods on four benchmark datasets. Experimental results demonstrate that the proposed method, as a conventional approach, not only significantly outperforms the nine conventional comparison methods but is also competitive with the seven deep learning-based comparison methods. In particular, our method achieves an accuracy of 93.4% on the Office+Caltech10 dataset, which outperforms the other comparison methods. An ablation study further demonstrates the effectiveness of the proposed constraint in aligning the objectives.

Abstract Water Diversion Projects have become increasingly popular in improving water quality in various water ecosystems. However, these projects also require a more comprehensive evaluation. In this study, we introduced a digital stable marker tracing module and proposed a continuation-dynamic constitution analysis approach. We applied this approach to analyze the ecological tidal water diversion in Changshu town, China. The results showed that the mean diversion water age of the Yangtze River water source was 10.80 h, the residence time of the background water source in Baimaotang was approximately 4.0 h, and the contribution of inflow water sources from tributaries accounted for 15% of discharges. The results can demonstrate practicality of our approach in quantitatively evaluating water diversion impacts and optimizing cooperative diversion projects. Furthermore, our discussion led to the design of an ecological tidal water diversion based on optimized cooperative diversion, which showed element-complementary and whole-comprehensive effects. This indicates that the ecological tidal water diversion can extend the impact of cooperative diversion. The continuation-dynamic constitution analysis approach enhances the tracing capacity of inflow constitution and enables the distinction of different time-varying distributions of each inflow constitution. Therefore, this approach holds promise as an embedded “Digital stable marker tracing” module in the model.

Abstract Background Goat products have played a crucial role in meeting the dietary demands of people since the Neolithic era, giving rise to a multitude of goat breeds globally with varying characteristics and meat qualities. The primary objective of this study is to pinpoint the pivotal genes and their functions responsible for regulating muscle fiber growth in the longissimus dorsi muscle (LDM) through DNA methylation modifications in Hainan black goats and hybrid goats. Methods Whole-genome bisulfite sequencing (WGBS) was employed to scrutinize the impact of methylation on LDM growth. This was accomplished by comparing methylation differences, gene expression, and their associations with growth-related traits. Results In this study, we identified a total of 3,269 genes from differentially methylated regions (DMR), and detected 189 differentially expressed genes (DEGs) through RNA-seq analysis. Hypo DMR genes were primarily enriched in KEGG terms associated with muscle development, such as MAPK and PI3K-Akt signaling pathways. We selected 11 hub genes from the network that intersected the gene sets within DMR and DEGs, and nine genes exhibited significant correlation with one or more of the three LDM growth traits, namely area, height, and weight of loin eye muscle. Particularly, PRKG1 demonstrated a negative correlation with all three traits. The top five most crucial genes played vital roles in muscle fiber growth: FOXO3 safeguarded the myofiber’s immune environment, FOXO6 was involved in myotube development and differentiation, and PRKG1 facilitated vasodilatation to release more glucose. This, in turn, accelerated the transfer of glucose from blood vessels to myofibers, regulated by ADCY5 and AKT2, ultimately ensuring glycogen storage and energy provision in muscle fibers. Conclusion This study delved into the diverse methylation modifications affecting critical genes, which collectively contribute to the maintenance of glycogen storage around myofibers, ultimately supporting muscle fiber growth.

AbstractBrain tumor accounts for about 1.6% of incidence and 2.5% of mortality of all tumors, and the median survival for brain tumor patients is only about 20 months. The treatment for brain tumor still faces many challenges, such as the blood-brain barrier (BBB), blood-brain tumor barrier (BBTB), the overexpressed efflux pumps, the infiltration, invasion, high heterogeneity of tumor cells, drug resistance and immune escape caused by tumor microenvironment (TME) and cancer stem cells (CSC). This review attempts to clarify the challenges for multi-functional nano drug delivery systems (NDDS) to cross the BBB and target the cancer cells or organelles, and also provides a brief description of the different types of targeted multi-functional NDDS that have shown potential for success in delivering drugs to the brain. Further, this review also summarizes the research progress of multi-functional NDDS in the combination therapy of brain tumors from the following sections, the combination of chemotherapy drugs, chemotherapy-chemodynamic combination therapy, chemotherapy-immunization combination therapy, and chemotherapy-gene combination therapy. We also provide an insight into the recent advances in designing multi-functional NDDS for combination therapy.

ABSTRACT: Gut health of broiler chickens is essential for production performance. The present study aimed to evaluate the impact of dietary supplementation with potassium diformate (KDF) on growth performance and intestinal health in broiler chickens. A total of 180 Arbor Acres (AA) broiler chickens were randomly allocated into 3 treatments, with 6 replicates, containing 10 chicks in each replicate. The treatment groups were: control group (CON) was fed a basal diet; KDF-4 groups fed the basal diet with 4 g/kg KDF; KDF-8 groups fed the basal diet with 8 g/kg KDF. The experiment period lasted for 42 d. During the starter phase, the ADFI and F/G of broilers in KDF groups were lower (P < 0.05) compared to the CON group. Furthermore, the BW and ADG in KDF-4 group was improved (P

Background The relationship between oral and overall health is of interest to health care professionals and patients alike. This study investigated the correlation between oral health-related quality of life (OHRQoL) and health-related quality of life (HRQoL) in a general adult population. Methods This cross-sectional study used a convenience sample of adult participants (N = 607) attending the 2022 Minnesota County and State fairs in USA, the 5-item Oral Health Impact Profile (OHIP-5) assessed OHRQoL, and the 10-item PROMIS v.1.2 Global Health Instrument assessed HRQoL. Spearman and Pearson correlations were used to summarize the bivariable relationship between OHRQoL and HRQoL (both physical and mental health dimensions). A structural equation model determined OHRQoL-HRQoL correlations (r). Correlations’ magnitude was interpreted according to Cohen’s guidelines (r = 0.10, 0.30, and 0.50 to demarcate “small,” “medium,” and “large” effects, respectively). Results OHRQoL and HRQoL correlated with r = 0.52 (95% confidence interval, CI: [0.50–0.55]), indicating that the two constructs shared 27% of their information. According to Cohen, this was a “large” effect. OHRQoL, and the physical and mental HRQoL dimensions correlated with r = 0.55 (95% CI: [0.50–0.59]) and r = 0.43 (95% CI: [0.40–0.46]), respectively, indicating a “large” and a “medium” effect. OHRQoL and HRQoL were substantially correlated in an adult population. Conclusion Using OHIP-5 to assess their dental patients’ oral health impact allows dental professionals to gain insights into patients’ overall health-related wellbeing.

This review reports recent breakthroughs in piezoelectric wearable energy harvesting technology, specifically focusing on their harnessing biomechanical energy from all over the human motion. Wearable technology has significantly reshaped our daily lives, prompting a pressing demand for intelligent and novel sensing mechanisms. These wearable devices and sensors often rely on batteries, necessitating frequent replacements or recharging. Leveraging the biomechanical energy of the human body, this paper underscores piezoelectric-based wearable energy harvesting from human motion. The sources of the human body's motion energy are categorized into three distinct groups based on their roles as excitation sources for energy harvesting. Additionally, this paper reviews the latest advancements in piezoelectric wearable technology for electricity generation, explicating the fundamental operational principles, structural designs, materials, and potential applications of piezoelectric wearable energy harvesters. Furthermore, it discusses the prevailing challenges associated with this technology in a dedicated section. Concluding with recommended guidelines, this paper underscores potential opportunities and shed light on future exploration.