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This study focuses on 3D printed alkali-activated recycled sand concrete (AARSC), a material that offers environmental benefits and design flexibility. The 3D printing process creates interfaces between filaments and layers, which may become potential weak points and increase interfacial inhomogeneity and discontinuity. Therefore, evaluating fracture resistance of interfaces is vital for ensuring the reliability of 3D printed materials. This work develops a model that accounts for discontinuity and inhomogeneity, enabling the determination of more realistic interfacial tensile bond strength (ft) and fracture toughness (KIC) for 3D printed AARSC. The model establishes a linear relationship between the maximum load (Fmax) and interfacial fracture parameters, allowing the determination of size-independent ft and KIC through analytical solutions. Three-point bending tests were conducted on 3D printed AARSC beams with different interface types and recycled sand replacement ratios to systematically evaluate the effect of recycled sand content on the interfacial fracture properties. The results show that the predicted interfacial ft and KIC exhibited size-independence as intrinsic interfacial properties. Moreover, ft values of the inter-layer interface were slightly higher than those of the inter-filament interface for the same recycled sand content, with the largest observed difference at 100% recycled sand replacement, being 22.7%. When the replacement ratio increased from 60% to 100%, the decrease in ft became significant, with the reduction rates increasing to 32.0% and 26.4% for Type I and Type II interfaces, respectively. Additionally, a positive correlation was observed between the recycled sand content and the anisotropy in fracture behaviors of 3D printed AARSC.

Abstract Background Previous studies have suggested a significant association between mobile phone addiction (MPA) and non-suicidal self-injury (NSSI) in general adolescents. However, limited research has analyzed this relationship in clinical populations, such as those with major depressive disorder (MDD), and the potential mediation mechanisms remain unclear. Methods This cross-sectional observational study analyzed data from 2343 adolescents with MDD (77.9% females; mean age = 14.99 years, SD = 1.65). Using mediation models, we explored the roles of self-esteem and depression severity (measured by Patient Health Questionnaire-9) in the relationship between MPA and NSSI. Additionally, we evaluated the associations between existing school-implemented mobile phone usage policies and levels of MPA, self-esteem, depression symptoms, and NSSI. Results MPA was significantly associated with NSSI, with low self-esteem and increased depression severity almost entirely mediating this effect (log-odds = 0.016, 95%CI = 0.02–0.013). Subdomains of MPA, including inability to control craving, feelings of anxiety, and productivity loss, followed similar mediation models, while the subdomain of withdrawal/escape had a partial effect mediated by depression severity. Additionally, enforced restrictions on mobile phone usage in schools did not show positive effects on related variables and even exacerbated MPA by increasing cravings and reducing productivity. Conclusion Our study suggests that MPA in adolescents with MDD may be an important risk factor for NSSI occurrence, and that reducing the negative impact of mobile phone usage on self-esteem and depressive symptoms, rather than simply restricting usage, may be crucial for effective intervention.

This study demonstrates the feasibility and effectiveness of utilizing native soils as a resource for inocula to produce n-caproate through the chain elongation (CE) platform, offering new insights into anaerobic soil processes. The results reveal that all five of the tested soil types exhibit CE activity when supplied with high concentrations of ethanol and acetate, highlighting the suitability of soil as an ideal source for n-caproate production. Compared with anaerobic sludge and pit mud, the native soil CE system exhibited higher selectivity (60.53%), specificity (82.32%), carbon distribution (60.00%), electron transfer efficiency (165.00%), and conductivity (0.59 ms∙cm−1). Kinetic analysis further confirmed the superiority of soil in terms of a shorter lag time and higher yield. A microbial community analysis indicated a positive correlation between the relative abundances of Pseudomonas, Azotobacter, and Clostridium and n-caproate production. Moreover, metagenomics analysis revealed a higher abundance of functional genes in key microbial species, providing direct insights into the pathways involved in n-caproate formation, including in situ CO2 utilization, ethanol oxidation, fatty acid biosynthesis (FAB), and reverse beta-oxidation (RBO). The numerous functions in FAB and RBO are primarily associated with Pseudomonas, Clostridium, Rhodococcus, Stenotrophomonas, and Geobacter, suggesting that these genera may play roles that are involved or associated with the CE process. Overall, this innovative inoculation strategy offers an efficient microbial source for n-caproate production, underscoring the importance of considering CE activity in anaerobic soil microbial ecology and holding potential for significant economic and environmental benefits through soil consortia exploration.

Abstract Background Surgical therapy is the most optimal treatment for hepatocellular carcinoma (HCC) combined with bile duct tumor thrombus (BDTT) patients. However, whether to perform bile duct resection (BDR) is still controversial. The purpose of this multicenter research is to compare the effect of BDR on the prognosis of extrahepatic BDTT patients. Methods We collected the data of 111 HCC patients combined with extrahepatic BDTT who underwent radical hepatectomy from June 1, 2004 to December 31, 2021. Those patients had either received hepatectomy with extrahepatic bile duct resection (BDR group) or hepatectomy without bile duct resection (NBDR group). Inverse probability of treatment weighting (IPTW) was used to reduce the potential bias between two groups and balance the influence of confounding factors in baseline data. Then compare the prognosis between the two groups of patients. Cox regression model was used for univariate and multivariate analysis to further determine the independent risk factors that influence the prognosis of HCC-BDTT patients. Results There were 38 patients in the BDR group and 73 patients in the NBDR group. Before and after IPTW, there were no statistical significance in OS, RFS and intraoperative median blood loss between the two groups (all P > 0.05). Before IPTW, the median postoperative hospital stay in the NBDR group was shorter (P = 0.046) and the grade of postoperative complications was lower than BDR group (P = 0.014). After IPTW, there was no difference in postoperative hospital stay between the two groups (P > 0.05). The complication grade in the NBDR group was still lower than that in the BDR group (P = 0.046). The univariate analysis showed that TNM stage and portal vein tumor thrombus (PVTT) were significantly correlated with OS (both P

Abstract Exploring catalytic reaction mechanisms is crucial for understanding chemical processes, optimizing reaction conditions, and developing more effective catalysts. We present a reaction-agnostic framework based on high-throughput deep reinforcement learning with first principles (HDRL-FP) that offers excellent generalizability for investigating catalytic reactions. HDRL-FP introduces a generalizable reinforcement learning representation of catalytic reactions constructed solely from atomic positions, which are subsequently mapped to first-principles-derived potential energy landscapes. By leveraging thousands of simultaneous simulations on a single GPU, HDRL-FP enables rapid convergence to the optimal reaction path at a low cost. Its effectiveness is demonstrated through the studies of hydrogen and nitrogen migration in Haber-Bosch ammonia synthesis on the Fe(111) surface. Our findings reveal that the Langmuir-Hinshelwood mechanism shares the same transition state as the Eley-Rideal mechanism for H migration to NH2, forming ammonia. Furthermore, the reaction path identified herein exhibits a lower energy barrier compared to that through nudged elastic band calculation.

Abstract Background Canine circovirus (CanineCV), a non-enveloped virus with a circular DNA genome, has been identified in various avian and mammalian species, including domestic and wild canids. This study aimed to comprehensively analyze the prevalence of CanineCV across diverse animal species in 11 provinces of China. Results A total of 1,666 serum samples were collected, revealing a 5.82% prevalence of CanineCV in dogs, with the highest rates being observed in southern and eastern China. Phylogenetic analysis of 266 global CanineCV genomes sourced from the NCBI identified six distinct genotypes, elucidating the complex dynamics of their evolution. Evidence suggested a potential bat origin for CanineCV, with positive selection and high rates of evolution being observed. Recombination analysis revealed dynamic genetic exchange, highlighting the intricate nature of CanineCV evolution. Mutational analysis identified key amino acid substitutions likely to influence the virus’s adaptation. Additionally, glycosylation, palmitoylation, and SUMOylation sites were predicted, shedding light on crucial functional properties of the virus. Conclusions This study provides a global perspective on the origin, genetic diversity, and evolutionary dynamics of CanineCV. Understanding these factors is crucial for elucidating its epidemiology and potential health risks.

Abstract Early identification of IDH mutation status is of great significance in clinical therapeutic decision-making in the treatment of glioma. We demonstrate a technological solution to improve the accuracy and reliability of IDH mutation detection by combining MRI-based prediction and a CRISPR-based automatic integrated gene detection system (AIGS). A model was constructed to predict the IDH mutation status using whole slices in MRI scans with a Transformer neural network, and the predictive model achieved accuracies of 0.93, 0.87, and 0.84 using the internal and two external test sets, respectively. Additionally, CRISPR/Cas12a-based AIGS was constructed, and AIGS achieved 100% diagnostic accuracy in terms of IDH detection using both frozen tissue and FFPE samples in one hour. Moreover, the feature attribution of our predictive model was assessed using GradCAM, and the highest correlations with tumor cell percentages in enhancing and IDH-wildtype gliomas were found to have GradCAM importance (0.65 and 0.5, respectively). This MRI-based predictive model could, therefore, guide biopsy for tumor-enriched, which would ensure the veracity and stability of the rapid detection results. The combination of our predictive model and AIGS improved the early determination of IDH mutation status in glioma patients. This combined system of MRI-based prediction and CRISPR/Cas12a-based detection can be used to guide biopsy, resection, and radiation for glioma patients to improve patient outcomes.

This paper explores the use of digital footprints data to improve on the limited information available on the size and distribution of the residential housing stock in the United Kingdom over the past two decades. We use a subset of a large dataset consisting of the names and addresses of more than one billion individuals dating back to 1997 (LCRs: Linked Consumer Registers) to calibrate property lifecycle information within an authoritative geolocated address and property dataset. We validate the results of our novel calibration method against official estimates by the UK government covering the same period. We further show that our calibration method, based on individual level data, captures a much larger share of the residential housing stock since 1997 than would have been possible with other available data sources. We argue that these housing stock estimates are fundamental to the development of a comprehensive digital footprints data infrastructure that has the potential to significantly enhance population, migration, and other social statistics in the UK. More generally, this study highlights the benefits of using digital footprints data in refining, calibrating, and extending existing datasets.

Background21-Hydroxylase deficiency (21-OHD) is caused by mutations in the CYP21A2 gene. Due to the complex structure and the high genetic heterogeneity of the CYP21A2 gene, genetic testing for 21-OHD is currently facing challenges. Moreover, there are no comparative studies on detecting CYP21A2 mutations by both second-generation sequencing and long-read sequencing (LRS, also known as third-generation sequencing).ObjectiveTo detect CYP21A2 variations in 21-OHD patients using targeted capture with LRS method based on the PacBio (Pacific Biosciences) Sequel II platform.MethodsA total of 67 patients with 21-OHD were admitted in Wuhan Children’s Hospital. The full sequence of CYP21A2 gene was analyzed by targeted capture combined with LRS based on the PacBio Sequel II platform. The results were compared with those of long-polymerase chain reaction (Long-PCR) combined with multiplex ligation probe amplification (MLPA) detection. Based on the in vitro study of 21-hydroxylase activity of common mutations, the patient genotypes were divided into groups of Null, A, B, and C, from severe to mild. The correlation between different genotype groups and clinical typing was observed.ResultsThe study analyzed a total of 67 patients. Among them, 44 (65.67%) were males and 23 (34.33%) were females, with a male-to-female ratio of approximately 1.9:1. A total of 27 pathogenic variants were identified in the 67 patients, of which micro-conversion accounted for 61.9%, new variants of CYP21A2 accounted for 8.2%; deletion accounted for 22.4% (CYP21A2 single deletion and chimeric TNXA/TNXB accounted for 12.7%, chimeric CYP21A1P/CYP21A2 accounted for 9.7%); and duplication accounted for 3.0% (CYP21A2 Gene Duplication). I2G was the most common variant (26.9%). Targeted capture LRS and MLPA combined with Long-PCR detection of CYP21A2 mutations showed 30 detection results with differences. The overall genotype-phenotype correlation was 82.1%. The positive predictive rate of the Null group for salt wasting (SW) type was 84.6%, the A group for SW type was 88.9%, the group B for simple virilization (SV) type was 82.4%, and the group C for SV type was 62.5%. The correlation coefficient rs between the severity of the phenotype and the genotype group was 0.682 (P < 0.05).ConclusionTargeted capture combined with LRS is an integrated approach for detecting CYP21A2 mutations, allowing precise determination of connected sites for multiple deletions/insertions and cis/trans configurations without analyzing parental genomic samples. The overall genotype-phenotype correlation for 21-OHD is generally strong, with higher associations observed between genotype and phenotype for group Null, A, and B mutations, and larger genotype-phenotype variation in group C mutations. Targeted capture with LRS sequencing offers a new method for genetic diagnosis in 21-OHD patients.

The transmission network is generally considered as three-phase balanced, while the consideration of three-phase unbalance is mainly on distribution networks. However, with the increasingly interconnection of renewable energy, such as wind energy, onto transmission networks, non-adoption of commutation long transmission lines usually results in unbalanced line parameters. Therefore, developing reliable three-phase power flow algorithms for transmission and distribution (T&D) systems becomes more and more important for the reliable and safe operation of emerging power systems. Among the many three-phase power flow algorithms, Newton Raphson method (NRM) and its variants occupy a large share, due to their ability in dealing with multiple sources and looped sub-networks. However, they are sensitive to the initial value, and can hardly ensure convergence to a physically meaningful solution with improper initial values, especially for three-phase unbalanced system. To this end, a general three-phase power flow method for T&D systems is proposed based on the holomorphic embedding method (HEM), and the advantages of the proposed method compared with traditional NRM in solving the power flow problem to a physically meaningful solution are theoretically analyzed. Based on the IEEE 33 system, the modified IEEE 123 system, and a regional power grid in China, it is verified that the proposed method has the advantages of high computational efficiency, reliable converging ability, and independence to the initial value.

Summary: This study was to assess the burden, trends, and risk factors associated with female breast cancer from 1990 to 2021 based on the Global Burden of Disease (GBD) 2021 study. In 2021, there were 20.32 million prevalent cases, 2.08 million incident cases, 0.66 million death cases, and 20.26 million disability-adjusted life years (DALYs). It presented an ascending trend in the age-standardized rates of prevalence and incidence over the past 32 years. The age-standardized DALYs rate (ASDR) increased slightly during 2012–2021. The DALYs increase was primarily driven by population aging and growth. High red meat intake accounted for the highest proportion of ASDR. Breast cancer burden attributed to metabolic risks increased, especially in the regions with low social-development index (SDI) and limited health systems. Dietary, behavior, and metabolic risk factors should be controlled to diminish breast cancer burden, especially in countries with lower SDI.

Kiwi starch (KS) is a new fruit-derived starch-based food material. In this study, wheat flour was partially replaced with 10–20% KS to make bread, and the influence of this substitution on mixed flour, dough processing performance, bread quality, and shelf life was investigated. KS substitution improved the water-binding ability of mixed flour, making it easier to gelatinize while improving viscoelasticity but reducing the integrity of the dough's gluten network structure. As the substitution rate increases, the hardness, air-cell ratio, and width-to-height ratio of bread significantly increased, while the springiness, resilience, baking loss, and specific volume reduced significantly (p

Introduction: Road traffic injuries stands as a major concern globally, as they result in significant loss of life, economic impact, and erode trust in government and societal safety. The influence of weather on road traffic safety is undeniable, impacting road conditions, individuals, and vehicles. However, the specific influence of weather on road traffic casualties has seldom been explored. Method: This study assesses the effect of weather factors on road traffic casualties in China from 2006 to 2021. Vector error correction models (VECM) were utilized to determine the Granger causality between weather factors and covariates. Furthermore, panel autoregressive distribution lag models (ARDL) were applied to quantify the association between weather factors and road traffic casualties. Results: The findings indicate that rainfall and temperature exert a short-term negative impact on casualty risk, which intriguingly becomes positive in the long term. A standout discovery is the significant role of health investments, which are shown to reduce casualty numbers in both the short and long-terms. In the long run, the gross domestic product significantly enhances casualties, while expressway mileage notably decreases them. Conclusions: These results demonstrate the significant influence of weather on road traffic casualties and highlight the critical roles played by factors such as gross domestic product, health investment, and expressway mileage. The evidence presented in the study underscores the urgent need for more effective strategies to mitigate road traffic casualties. Thus, some effective measures are proposed to reduce road traffic casualties. This study is conducive to the improvement of traffic in severe weather in China and provides guidance for traffic management departments.

The incidence rate of prostate cancer (PCa) has risen by 3% per year from 2014 through 2019 in the United States. An estimated 34,700 people will die from PCa in 2023, corresponding to 95 deaths per day. Castration resistant prostate cancer (CRPC) is the leading cause of deaths among men with PCa. Androgen receptor (AR) plays a critical role in the development of CRPC. N-terminal domain (NTD) is the essential functional domain for AR transcriptional activation, in which modular activation function-1 (AF-1) is important for gene regulation and protein interactions. Over last 2 decades drug discovery against NTD has attracted interest for CRPC treatment. However, NTD is an intrinsically disordered domain without stable three-dimensional structure, which has so far hampered the development of drugs targeting this highly dynamic structure. Employing high throughput cell-based assays, small-molecule NTD inhibitors exhibit a variety of unexpected properties, ranging from specific binding to NTD, blocking AR transactivation, and suppressing oncogenic proliferation, which prompts its evaluation in clinical trials. Furthermore, molecular dynamics simulations reveal that compounds can induce the formation of collapsed helical states. Nevertheless, our knowledge of NTD structure has been limited to the primary sequence of amino acid chain and a few secondary structure motif, acting as a barrier for computational and pharmaceutical analysis to decipher dynamic conformation and drug-target interaction. In this review, we provide an overview on the sequence-structure-function relationships of NTD, including the polymorphism of mono-amino acid repeats, functional elements for transcription regulation, and modeled tertiary structure of NTD. Moreover, we summarize the activities and therapeutic potential of current NTD-targeting inhibitors and outline different experimental methods contributing to screening novel compounds. Finally, we discuss current directions for structure-based drug design and potential breakthroughs for exploring pharmacological motifs and pockets in NTD, which could contribute to the discovery of new NTD inhibitors.

Background: Hepatocellular carcinoma (HCC) is among the most prevalent digestive system malignancies and is associated with a poor prognosis. Necroptosis, a form of regulated death mediated by death receptors, exhibits characteristics of both necrosis and apoptosis. Long non-coding RNAs (lncRNAs) have been identified as crucial regulators in tumor necroptosis. This study aims to identify the necroptosis-related lncRNAs (np-lncRNA) in HCC and investigate their relationships with prognosis. Method: The RNA-sequencing data, along with clinicopathological and survival information of HCC patients were sourced from The Cancer Genome Atlas (TCGA) database. The np-lncRNAs were analyzed to assess their potential in predicting HCC prognosis. Prognostic signatures related to necroptosis were constructed using stepwise multivariate Cox regression analysis. The prognosis of patients was compared using Kaplan-Meier (KM) analysis. The accuracy of the prognostic signature was evaluated using Receiver operating characteristic (ROC) analysis and decision curve analysis (DCA). Quantitative real-time polymerase chain reaction(qPCR) was employed to validate the lncRNAs expression levels of lncRNAs among samples from an independent cohort. Results: The np-lncRNAs ZFPM2-AS1, AC099850.3, BACE1-AS, KDM4A-AS1 and MKLN1-AS were identified as potential prognostic biomarkers. The prognostic signature constructed from these np-lncRNAs achieved an Area Under the Curve (AUC) of 0.773. Based on the risk score derived from the signature, patients were divided into two groups, with the high-risk group exhibiting poorer overall survival. Gene Set Enrichment Analysis (GSEA) revealed significantly different between the low risk and high risk groups in tumor-related pathways (such as mTOR, MAPK and p53 signaling pathways) and immune-related functions (like T cell receptor signaling pathway and natural killer cell mediated cytotoxicity). The increased expression of np-lncRNAs was confirmed in another independent HCC cohort. Conclusions: This signature offers a dependable method for forecasting the prognosis of HCC patients. Our findings indicate a subset of np-lncRNA biomarkers that could be utilized for prognosis prediction and personalized treatment strategies of HCC patients.

Investigating the influences of different sterilization methods on overall juice quality is essential for the production of high-quality juice. The effects of ultra-high temperature instantaneous sterilization (UHT), thermosonication (TS), high hydrostatic pressure sterilization (HHP), and irradiation sterilization (IS) on the physicochemical properties, functional components, and color of Aronia melanocarpa juice (AMJ) were investigated. In addition, anthocyanin target metabolomics were used to explore the influences of different sterilization methods on the AMJ anthocyanin profile. All sterilization treatments effectively ensured the microbial safety of AMJ, and the AMJ viscosity was noticeably declined after sterilization (p < 0.05). Except for HHP, the other treatments aggravated AMJ browning (p < 0.05). Both TS and HHP treatments significantly enhanced or preserved the total polyphenols, flavonoids, and anthocyanins in AMJ and retained the original juice color, whereas UHT and IS treatments were not conducive to maintaining these characteristics. TS treatment significantly increased cyanidin-3-O-galactoside (C-3-O-gal) and cyanidin-3-O-arabinoside (C-3-O-ara) contents in AMJ by 7.98% and 5.90%, while IS resulted in a significant decrease of 15.74% and 10.46% (p < 0.05). C-3-O-gal and C-3-O-ara were the major reasons for the significant upregulation and downregulation of the total monomeric anthocyanins contents (TMAC) in the AMJ after TS and IS treatment, respectively. Malvidin-3-O-glucoside (M-3-O-glu), Cyanidin-3-O-(6-O-malonyl-β-D-glucoside) and Kaempferol-3-O-rutinoside (K-3-O-rut) might be markers of differential metabolites produced by the TS, HHP, and IS treatments, respectively. Correlation analysis indicated that Cyanidin-3-O-xyloside (C-3-O-xyl), C-3-O-ara, and Pelargonidin-3-O-arabinoside (P-3-O-ara) might be the principal contributed to the antioxidant capacity of AMJ. The research results are anticipated to supply technical reference for AMJ processing.

Abstract Background Diabetic kidney disease (DKD) is a microvascular complication of diabetes mellitus, contributing to end-stage renal disease with limited treatment options. The development of DKD is attributed to podocyte injury resulting from abnormal podocyte autophagy. Consequently, the restoration of podocyte autophagy is deemed a practicable approach in the treatment of DKD. Methods Diabetic mice were induced by streptozotocin and high-fat diet feeding. Following 8 weeks of “QN” agarwood treatment, metrics such as albuminuria, serum creatinine (Scr), and blood urea nitrogen (BUN) were evaluated. Renal histological lesions were evaluated by H&E, PAS, Masson, and Sirius red staining. Evaluation of the effects of “QN” agarwood on renal inflammation and fibrosis in DKD mice through WB, q-PCR, and IHC staining analysis. Cytoscape 3.7.1 was used to construct a PPI network. With the DAVID server, the gene ontology (GO) functional annotation and the Kyoto encyclopedia of genes and genomes (KEGG) signaling pathways of the target enrichment were performed. Molecular docking and binding affinity calculations were conducted using AutoDock, while PyMOL software was employed for visualizing the docking results of active compounds and protein targets. Results The results of this study show that “QN” agarwood reduced albuminuria, Scr, and BUN in DKD mice, and improved the renal pathological process. Additionally, “QN” agarwood was observed to downregulate the mRNA and protein expression levels of pro-inflammatory and pro-fibrotic factors in the kidneys of DKD mice. Network pharmacology predicts that “QN” agarwood modulates the epidermal growth factor receptor (EGFR) signaling pathway. “QN” agarwood can increase the expression of LC3B and Nphs1 in DKD mice while reducing the expression of EGFR. Conclusion The present study demonstrated that “QN” agarwood ameliorated renal injury in DKD by targeting EGFR and restoring podocyte autophagy. Graphical Abstract

This study investigated the storage characteristics of probiotic fermented kiwifruit juice under 4 ℃ refrigeration. The research focused on the changes in the viable lactic acid bacteria count physicochemical properties, sensory quality, nutritional quality and functional properties of the juice during 14 days storage period. Additionally, preliminary shelf-life prediction was made based on the changes in ascorbic acid during the storage. The results showed that the fermented kiwifruit juice maintained good probiotic activity throughout the entire storage process with a consistently higher viable bacterial count of over 8.7 lg CFU/mL. Meanwhile, the fermented juice maintained stable physicochemical properties and color and odor characteristics during storage. Compared to unfermented juice, probiotic fermentation contributed to retaining and maintaining ascorbic acid, total phenols and antioxidant activity of juice during storage. In particular, the unfermented juice experienced a 67.98% loss in ascorbic acid after storage, while fermented juice only lost 23.94%. Moreover, based on the zero-order kinetic model, the study effectively predicted the changes in ascorbic acid in kiwifruit juice during storage. The prediction results indicated that fermented juice could be stored at 4 ℃ for 50 d, while unfermented juice could only be stored for 15 d, based on whether ascorbic acid could be effectively supplemented. This showed that fermented kiwifruit juice could maintain high nutritional quality for an extended period during cold storage, further providing the possibility for the commercialization of fermented kiwifruit juice.

Wolfberry, esteemed as a traditional Chinese medicinal material and functional food, is replete with nutrients and boasts a diverse array of health benefits, including hypoglycemic, antitumor, antioxidant, anti-inflammatory, and immune-enhancing properties. Notably, inflammation is a pivotal factor in the onset and progression of numerous diseases. Despite this, there is a paucity of research on the comprehensive evaluation of the components found in different wolfberries, and the exploration of their primary active components is limited. To address this issue, we conducted a comprehensive targeted metabolomics analysis, employing statistical methods such as principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA), KEGG pathway analysis, and volcano plots to delineate the compositional differences among red, black, and yellow wolfberries. Furthermore, we investigated the anti-inflammatory effects of their primary components through in vitro experiments. Our analysis revealed a total of 1,104 chemical compositions in the three wolfberries, with alkaloids, phenolic acids, flavonoids, and lipids being the predominant nutritional components. KEGG enrichment analysis indicated that these compositions were primarily involved in the biosynthesis of secondary metabolites, ABC transport, and galactose metabolism pathway. Moreover, our study demonstrated that quercetin exhibited dose-dependent anti-inflammatory activity in LPS-stimulated HUVECs. It effectively inhibited the production of inflammatory factors such as TNF-α, MCP-1, and IL-1β, while also down-regulating the gene and protein expression levels of ICAM-1 and VCAM-1. In conclusion, our findings indicate that there are variations in compositions among the three wolfberries, with flavonoids being the most abundant, and in vitro studies also confirmed the anti-inflammatory potential of quercetin. It is worth noting that Lycium ruthenicum contains higher levels of antioxidant components and possesses greater nutritional value, providing valuable insights for the future development and utilization of the three wolfberries.

BackgroundObservational studies have indicated that immune dysregulation in primary sclerosing cholangitis (PSC) primarily involves intestinal-derived immune cells. However, the causal relationship between peripheral blood immune cells and PSC remains insufficiently understood.MethodsA bidirectional two-sample Mendelian randomization (MR) analysis was implemented to determine the causal effect between PBC and 731 immune cells. All datasets were extracted from a publicly available genetic database. The standard inverse variance weighted (IVW) method was selected as the main method for the causality analysis. Cochran’s Q statistics and MR-Egger intercept were performed to evaluate heterogeneity and pleiotropy.ResultsIn forward MR analysis, the expression ratios of CD11c on CD62L+ myeloid DC (OR = 1.136, 95% CI = 1.032–1.250, p = 0.009) and CD62L-myeloid DC AC (OR = 1.267, 95% CI = 1.086–1.477, p = 0.003) were correlated with a higher risk of PSC. Each one standard deviation increase of CD28 on resting regulatory T cells (Treg) (OR = 0.724, 95% CI = 0.630–0.833, p < 0.001) and CD3 on secreting Treg (OR = 0.893, 95% CI = 0.823–0.969, p = 0.007) negatively associated with the risk of PSC. In reverse MR analysis, PSC was identified with a genetic causal effect on EM CD8+ T cell AC, CD8+ T cell AC, CD28− CD127− CD25++ CD8+ T cell AC, CD28− CD25++ CD8+ T cell AC, CD28− CD8+ T cell/CD8+ T cell, CD28− CD8+ T cell AC, and CD45 RA− CD28− CD8+ T cell AC.ConclusionOur study indicated the evidence of causal effects between PSC and immune cells, which may provide a potential foundation for future diagnosis and treatment of PSC.

Non-alcoholic fatty liver disease (NAFLD) is increasingly recognized for its global prevalence and potential progression to more severe liver diseases such as non-alcoholic steatohepatitis (NASH). The primary treatment for NASH is modifying lifestyle through dietary or exercise interventions. The aim of the current study is to investigate the roles of Fufang Zhenzhu Tiaozhi polysaccharides (FTZPs) in mice with NASH. FTZPs were concurrently administered to high-fat diet (HFD)-induced 24-week NASH model mice. FTZPs treatment effectively improved liver lipid metabolism, reduced inflammation and fibrosis, improved the integrity of the intestinal mucosal barrier, and modulated the structure of the intestinal microbiota. FTZPs treatment significantly reduced the abundance of Gammaproteobacteria, Clostridium, and Coprococcus while as induced the abundance of Dehalobacteraceae and Dehalobacterium. Furthermore, sixteen differential metabolites were screened by metabolomics, and the change of asparagine was the most significant. In addition, the correlation analysis showed that there was a significant correlation between asparagine and the aforementioned differential bacteria. The present study demonstrated that FTZPs, as the fundamental pharmacological elements of FTZ (Fufang Zhenzhu Tiaozhi), protect against NASH by improving intestinal barrier damage and regulating intestinal flora with the increase in asparagine.

This review focuses on changes in nutrition and functional properties of protein-rich foods, primarily attributed to alterations in protein structures. We provide a comprehensive overview and comparison of commonly used laboratory methods for protein structure identification, aiming to offer readers a convenient understanding of these techniques. The review covers a range of detection technologies employed in food protein analysis and conducts an extensive comparison to identify the most suitable method for various proteins. While these techniques offer distinct advantages for protein structure determination, the inherent complexity of food matrices presents ongoing challenges. Further research is necessary to develop and enhance more robust detection methods to improve accuracy in protein conformation and structure analysis.

Abstract Traditional Chinese medicine (TCM) has been widely used for several centuries for metabolic diseases, including non-alcoholic fatty liver disease (NAFLD). At present, NAFLD has become the most prevalent form of chronic liver disease worldwide and can progress to non-alcoholic steatohepatitis (NASH), cirrhosis, and even hepatocellular carcinoma. However, there is still a lack of effective treatment strategies in Western medicine. The development of NAFLD is driven by multiple mechanisms, including genetic factors, insulin resistance, lipotoxicity, mitochondrial dysfunction, endoplasmic reticulum stress, inflammation, gut microbiota dysbiosis, and adipose tissue dysfunction. Currently, certain drugs, including insulin sensitizers, statins, vitamin E, ursodeoxycholic acid and betaine, are proven to be beneficial for the clinical treatment of NAFLD. Due to its complex pathogenesis, personalized medicine that integrates various mechanisms may provide better benefits to patients with NAFLD. The holistic view and syndrome differentiation of TCM have advantages in treating NAFLD, which are similar to the principles of personalized medicine. In TCM, NAFLD is primarily classified into five types based on clinical experience. It is located in the liver and is closely related to spleen and kidney functions. However, due to the multi-component characteristics of traditional Chinese medicine, its application in the treatment of NAFLD has been considerably limited. In this review, we summarize the advances in the pathogenesis and treatment of NAFLD, drawn from both the Western medicine and TCM perspectives. We highlight that Chinese and Western medicine have complementary advantages and should receive increased attention in the prevention and treatment of NAFLD.

The reliability and safety of energy-storage battery packs have always been an industry priority. Large energy-storage battery modules are characterized by high power, numerous built-in energy-storage batteries, complex structures, and a heightened risk of thermal runaway. Monitoring the core temperature in energy-storage battery packs in a noncontact, real-time manner is essential for preventing and controlling thermal runaway events. In response to the challenge of incomplete temperature data acquisition, especially in industrial settings where arranging multiple temperature measurement points inside the battery pack may not be feasible, this study introduced the Gappy POD reconstruction algorithm. Gappy POD is a data analysis method based on proper orthogonal decomposition (POD), which is commonly used in inverse heat transfer and fluid mechanics problems. This enables the prediction of the internal core temperature by monitoring the surface temperature of the battery pack. Considering the safety concerns of battery experiments, this study simulated battery temperature changes using a simplified simulated energy-storage battery experimental platform. The platform tests the stability and real-time reconstruction capabilities of the Gappy POD algorithm under stable and drastic changes in operating conditions. Although we did not introduce the equivalent circuit model in the experiment, this preliminary study verified the reconstruction ability of the algorithm under significant fluctuations in working conditions. Neural networks are renowned for their nonlinear solid prediction capabilities and have extensive applications in predicting the temperatures of energy-storage batteries. This study compares the reconstruction ability of the Gappy POD algorithm with the prediction capability of a back-propagation (BP) neural network. This study also explored the reconstruction and prediction capabilities of the Gappy POD and BP neural networks under varying database sizes for training. The research presented in this study indicates that the Gappy POD reconstruction algorithm exhibits high prediction accuracy, particularly under stable working conditions and with smaller training sample sizes. In these scenarios, it outperformed the BP neural network. Moreover, this algorithm demonstrates strong stability and low dependence on the volume of database data, providing a solid foundation for further applications in the thermal management of energy-storage batteries. It also presents a viable approach for noncontact monitoring of the core temperature of energy-storage battery packs. In conclusion, this study acknowledges areas for improvement in the current research and outlines prospects for future research.

Maximum power point tracking (MPPT) technology is well suited to photovoltaic (PV) system analysis, which can improve power generation efficiency and control effectiveness. However, the nonlinear intrinsic characteristics of the PV system cannot guarantee that the power generation system always works stably at the maximum power point (MPP). Additionally, the accuracy and complexity of the system modeling are crucial to the performance of the PV system. In this article, a novel adaptive Rao-Blackwellized cubature Kalman filter (ARBCKF) scheme is developed that can be efficiently applied to estimate MPPT for PV systems. At first, a comprehensive analysis of the cubature Kalman filter (CKF) is conducted in the context of MPPT. Second, the LogWright function is utilized to represent the current as an explicit function of the voltage, which achieves faster and more accurate execution. Finally, an adaptive-Rao-Blackwellized method is applied to dynamic systems with nonlinear equations of state and linear equations of measurement, which can capitalize on adapting the noise covariance and improving the performance. Compared with the widely adopted other Kalman filter methods, computation results show that MPP estimation accuracy can be significantly increased in diverse transient and steady-state scenarios.

Most existing road extraction methods prioritize region accuracy at the expense of ignoring road boundaries and connectivity quality. The occluding objects such as buildings, trees, and vehicles in remote sensing data usually cause discontinuous mask outputs, and consequently affect road extraction accuracy. In this article, a road extraction fusion network perceiving region and boundary features is proposed. The combination of a location-aware transformer and convolutional neural network is responsible for focusing regional semantic information through adaptive weight filtering. Combining spatial and channel information, the graph convolutional network is improved by constructing an integrated adjacency matrix to consider the relationships between nodes at different scales, which allows for better capture of multiscale contexts. Boundary details are used to complement regional features, thereby enhancing the connectivity of masks. Comprehensive quantitative and qualitative experiments demonstrate that our method significantly outperforms state-of-the-art methods on two public benchmarks, which can improve road extraction by handling interruptions related to shadows and occlusions, producing high-resolution masks.

Digital transformation has become an inevitable choice for enterprises to survive and compete. This article aims to investigate mechanisms and impacts of peer effects in digital transformation within supply chain networks. Using a sample of listed companies in China from 2011 to 2020, the findings suggest the existence of peer effects in the digital transformation of enterprises within supply chain networks. These effects become more significant as the perception of uncertainty and environmental uncertainty increase. Further analysis reveals that the greater the disparity in discourse power and the degree of digital transformation among peer enterprises within the supply chain, the stronger the peer effects. The study also examines various scenarios in which enterprises operate, finding that greater supply chain stability significantly enhances the peer effects of digital transformation. Heterogeneity tests indicate that peer effects in digital transformation are more evident when peer enterprises within the supply chain are located in different regions, operate in different industries, are non-state-owned, have directorial connections and common institutional ownership, and possess fluctuating executive teams. Additionally, the study discusses the spillover effects of digitalization among peer enterprises on the focal company. This research provides a micro-level exploration of the peer effects of digital transformation from a supply chain perspective, offering theoretical references and practical insights for enterprises seeking to achieve digital transformation.

This study presents a novel massively high-throughput reinforcement learning (RL) framework specifically designed for addressing classic control problems, leveraging our proposed architecture and algorithms optimized for efficient concurrent computations on GPUs. Our research demonstrates the effectiveness of our methods in efficiently training RL agents across various classic control problems, encompassing both discrete and continuous domains, while achieving rapid and stable performance up to 10K concurrent environment instances. Furthermore, we observe that RL exploration with a large number of parallel instances significantly enhances the stability of updating a shared model. For instance, we show that the stability of Deep Deterministic Policy Gradient (DDPG) training can be achieved without requiring experience replay, as evidenced in our study.

Abstract Objective Tobacco has been identified as a significant contributory element to the development of breast cancer. Our objective was to evaluate the spatiotemporal trends of tobacco-related breast cancer at the global, regional, and national scales during 1990–2019. Methods We extracted data on mortality, disability adjusted of life years (DALYs), age-standardized mortality rate (ASMR), and age-standardized DALYs rate (ASDR) from the Global Burden of Disease (GBD) study 2019. Estimated annual percentage change (EAPC) was computed to assess the temporal change in ASDR and ASMR. Results In 2019, the deaths and DALYs attributed to tobacco-related breast cancer were estimated to be 35,439 (95% UI: 22,179–48,119) and 1,060,590 (95% UI: 622,550–1,462,580), respectively. These figures accounted for 5.1% and 5.2% of the total burden of breast cancer. ASMR and ASDR increased in low SDI regions, remained stable in low-middle and middle SDI regions and declined in high and high-middle SDI regions. The burden of breast cancer attributable to tobacco varied notably among regions and nations. Oceania, Southern Latin America, and Central Europe were the GBD regions with the highest number of ASMR and DALYs. There was a positive relationship between age-standardized rate and SDI value in 2019 across 204 nations or territories. A negative association was observed between the EAPC in ASMR or ASDR and the human development index (HDI) in 2019 (R = -0.55, p

The major vascular complications associated with diabetes make the management of diabetic mellitus erectile dysfunction (DMED) a challenging endeavor. Notable factors contributing to DMED include oxidative stress, nitric oxide (NO)/cyclic guanosine monophosphate (cGMP) pathway activation, and apoptosis, while nitro-oleic acid (NO2-OA) has been shown to be beneficial in treating these aspects of this condition. We, herein, investigated the effects and possible mechanisms of NO2-OA on erectile function as assessed in a streptozotocin-induced rat model of diabetes. Our results revealed that the erectile function of DMED rats was significantly impaired compared with that of the control group. However, in response to 4 weeks of NO2-OA treatment, there was an improvement in erectile function. The expression of oxidative stress-related indicators was significantly increased and the NO/cGMP pathway was impaired in the DMED group. The expression of proapoptotic factors was increased, while that of antiapoptotic factors was decreased in the DMED group. Moreover, the cell morphology in the cavernous tissue of the DMED group also changed adversely. NO2-OA treatment significantly reversed all these changes observed in the DMED group. In conclusion, NO2-OA treatment partially improved erectile function in DMED rats through mechanisms that included inhibition of oxidative stress, activation of the NO/cGMP pathway, and a reduction in apoptosis.

Clutter removal in ground-penetrating radar (GPR) based on deep learning has been studied in recent years. However, existing methods are primarily designed for homogeneous background conditions and utilize only local spatial information via the convolution operation. In order to solve these issues, a subspace projection attention (SPA) network is proposed for GPR heterogeneous clutter removal in this article. First, a heterogeneous concrete dataset based on a numerical model with randomly placed aggregates is constructed, which incorporates the complex electromagnetic propagation process accurately to improve the effectiveness for heterogeneous clutter removal. In addition, the clutter basis learning neural network is designed by integrating the SPA module into the skip connection paths of U-Net architecture. By learning the subspace basis vectors adaptively, the SPA exploits both local and global spatial information to extract target features precisely. At the same time, the feature maps are projected to the target subspace to remove heterogeneous clutter features. Finally, the performance and effectiveness of proposed method are validated by simulations and experiments.

This paper provides an overview of the study of optical resonant cavity stability, focusing on the relevant principles, key technological advances, and applications of optical resonant cavities in a variety of high-precision measurement techniques and modern science and technology. Firstly, the vibration characteristics, thermal noise, and temperature characteristics of the reference cavity are presented. Subsequently, the report extensively discusses the advances in key technologies such as mechanical vibration isolation, thermal noise control, and resistance to temperature fluctuations. These advances not only contribute to the development of theory but also provide innovative solutions for practical applications. Typical applications of optical cavities in areas such as laser gyroscopes, high-precision measurements, and gravitational wave detection are also discussed. Future research directions are envisioned, emphasising the importance of novel material applications, advanced vibration isolation technologies, intelligent temperature control systems, multifunctional integrated optical resonator design, and deepening theoretical models and numerical simulations.

Canine circovirus (CanineCV), which is a new mammalian circovirus first reported in the United States in 2012, mainly causes diarrhea and vomiting in dogs. As CanineCV evolves and new subtypes emerge, there is an urgent need for new detection technologies to improve the sensitivity and detection rates of viruses in complex scenarios. A chip digital PCR(cdPCR) assay was established for the detection of CanineCV in this study. The results showed good reproducibility, specificity and a linear relationship; the minimum detection limit of CanineCV by cdPCR was 6.62 copies/μL, which is 10 times more sensitive than quantitative real-time PCR (qPCR). The qPCR-positive detection rate was 1 %, while CanineCV cdPCR (2.1 %) exhibited a greater positive detection rate. Fifteen complete genomes were sequenced and subdivided into CanineCV-1 and CanineCV-3. In conclusion, we developed a rapid, reliable, and specific cdPCR method for screening and monitoring canine CV.

Abstract Innovation is the main driver of regional economic development. Exploring the spatial patterns of regional innovation can elucidate the regional differences in innovation development. Nearly all the researches on spatial patterns of innovation take the administrative divisions of provinces, cities and counties as spatial units, and portray the spatial patterns of regional innovation from the macroscopic overall, but lack the spatial patterns within the regions. This paper employed patents of Jiangsu province, China in 2019 as a sample, divided the spatial units based on geographic coordinates of patent data, calculated the technological innovation capability index of within the spatial units, overcoming the drawbacks of the research method that fails to reveal the internal pattern of cities by using provinces, cities and counties as the research scale, and analysed the spatial patterns of technological innovation capability in Jiangsu province by using spatial autocorrelation analysis and standard deviation ellipse. The results show that: (1) In terms of distribution, the spatial pattern of technological innovation capability in Jiangsu province is obviously “one core and one belt” in southern Jiangsu, with Nanjing as the core and Suzhou, Wuxi and Changzhou as a southeast-northwest belt of high innovation capacity, while multi-point scattered in northern Jiangsu. (2) From the perspective of aggregation mode, each city has the largest number of H-H agglomeration units, relatively presenting a zonal distribution in the Suzhou-Wuxi-Changzhou area and Nanjing, and less distribution in other places. (3) Industrially speaking, the development of technological innovation capability of the secondary industry in many cities is better and centralized, while secondary and tertiary industries move hand in hand around the city centre in Nanjing, and the tertiary industry dominates comparably in Suzhou and Wuxi.

Abstract Quzhou Aurantii Fructus (QAF) has a long history as a folk medicine and food for the treatment of liver diseases. While our earlier study provided evidence of hepatoprotective properties contained within the flavonoids and limonins constituents in QAF, the potential preventative effects afforded by essential oil components present within QAF remains enigmatic. In this study, we prepared Quzhou Aurantii Fructus essential oil (QAFEO) and confirmed its anti-inflammatory effects on liver inflammation through experimentation on lipopolysaccharide and D-galactosamine (LPS/D-GalN) induced acute liver failure (ALF) mouse models. Using RNA-sequence (RNA-seq) analysis, we found that QAFEO prevented ALF by systematically blunting the pathways involved in response to LPS and toll-like receptor signaling pathways. QAFEO effectively suppressed the phosphorylation of tank-binding kinase 1 (TBK1), TGF-beta activated kinase 1 (TAK1), interferon regulatory factor 3 (IRF3), and the activation of mitogen activated kinase-like protein (MAPK) and nuclear factor-kappa B (NF-κB) pathways in vivo and in vitro. Importantly, QAFEO substantially reduced myeloid differentiation primary response gene 88 (MyD88)- toll-like receptor 4 (TLR4) interaction levels. Moreover, 8 compounds from QAFEO could directly bind to REAL, TAK1, MyD88, TBK1, and IRF3. Taken together, the results of our study support the notion that QAFEO exerts a hepatoprotective effect through inhibiting LPS-mediated inflammatory response. Graphical abstract

Abstract Background Prothrombin induced by vitamin K absence‐II (PIVKA‐II) and Alpha‐fetoprotein (AFP) have been widely used as diagnostic markers in hepatocellular carcinoma (HCC), but the prognostic values of the two serum markers and their clinical usefulness in patient selection for different surgical approaches remain largely unclear. Methods HCC patients received surgical treatment between 2015 and 2019 were included. Patients were divided into four statuses according to the serum PIVKA‐II and AFP secretion status: PIVKA‐II (−) AFP (−) (status 1); PIVKA‐II (+) AFP (−) (status 2); PIVKA‐II (−) AFP (+) (status 3); PIVKA‐II (+) AFP (+) (status 4). Kaplan–Meier analyses were conducted to compare the survivals of the four groups and the HCC patients received different surgical interventions; time‐dependent AUC curves were introduced to evaluate the prognostic value of the PIV‐AFP status; Cox regression model was used to identify prognostic indexes for overall survival (OS) and recurrence‐free survival (RFS). Results A total of 518 patients were included. Patients with PIVKA‐II (+) and APF (+) presented significantly decreased OS and RFS comparing to the other statuses. The areas under ROC curves of PIV‐AFP status in predicting OS and RFS were superior to the PIVKA‐II or the AFP alone. The HCC patients in early stages with PIVKA‐II (+) and APF (+) had worse RFS when received laparoscopic hepatectomy than those who received open hepatectomy, whereas there was no difference in other secretion statuses. The PIVKA‐II (+) and AFP (+) secretion status was an independent risk factor for OS, RFS. Conclusions The PIV‐AFP secretion status is of favorable clinical utility in predicting the OS and RFS of the HCC patients; extra caution is needed when applicated the laparoscopic approach in the HCC patients with PIVKA‐II (+) and AFP (+).

On schematic metro maps, high-quality label placement is helpful to passengers performing route planning and orientation tasks. It has been reported that the artificial neural network (ANN) has the potential to place labels with learned labeling knowledge. However, the previous ANN-based method only considered the effects of station points and their connected edges. Indeed, unconnected but surrounding features (points, edges, and labels) also significantly affect the quality of label placement. To address this, we have proposed an improved method. The relations between label positions and both connected and surrounding features are first modeled based on labeling natural intelligence (i.e., the experience, knowledge, and rules of labeling established by cartographers). Then, ANN is employed to learn such relations. Quantitative evaluations show that our method reaches lower percentages of label–point overlap (0.00%), label–edge overlap (4.12%), and label–label overlap (20.58%) compared to the benchmark (4.17%, 14.29%, and 35.11%, respectively). On the other hand, our method effectively avoids ambiguous labels and ensures labels from the same line are placed on the same side. Qualitative evaluations show that approximately 75% of users prefer our results. This novel method has the potential to advance the automated generation of schematic metro maps.

In this study, we tackle the task of road segmentation from Synthetic Aperture Radar (SAR) imagery, which is vital for remote sensing applications including urban planning and disaster management. Despite its significance, SAR-based road segmentation is hindered by the scarcity of high-resolution, annotated SAR datasets and the distinct characteristics of SAR imagery, which differ significantly from more commonly used electro-optical (EO) imagery. To overcome these challenges, we introduce a multi-source data approach, creating the HybridSAR Road Dataset (HSRD). This dataset includes the SpaceNet 6 Road (SN6R) dataset, derived from high-resolution SAR images and OSM road data, as well as the DG-SAR and SN3-SAR datasets, synthesized from existing EO datasets. We adapt an off-the-shelf road segmentation network from the optical to the SAR domain through an enhanced training framework that integrates both real and synthetic data. Our results demonstrate that the HybridSAR Road Dataset and the adapted network significantly enhance the accuracy and robustness of SAR road segmentation, paving the way for future advancements in remote sensing.

The intermittent and stochastic characteristics of wind power pose a higher demand on the complementarity of hydropower. Studying the optimal coordinated operation of hydro–wind power systems has become an extremely effective way to create safe and efficient systems. This paper aims to study the optimal coordinated operation of a hybrid power system based on a newly established Simulink model. The analysis of the optimal coordinated operation undergoes two simulation steps, including the optimization of the complementary mode and the optimization of capacity allocation. The method of multiple complementary indicators is adopted to enable the optimization analysis. The results from the complementary analysis show that the hydraulic tracing effect obviously mitigates operational risks and reduces power losses under adverse wind speeds. The results from the analysis of capacity allocation also show that the marginal permeation of installed wind capacity will not exceed 250 MW for a 100 MW hydropower plant under random wind speeds. These simulation results are obtained based on the consideration of some real application scenarios, which help power plants to make the optimal operation plan with a high efficiency of wind energy and high hydro flexibility.

The long-term use of fertilizers and pesticides in conventional cultivation has resulted in a decrease in soil productivity and vegetable yields in greenhouses. However, there is little research exploring the changes in soil organic carbon and the microbial community mediated by soil aggregates, or their impacts on soil productivity. This study investigated the properties of soil aggregates, including the levels of organic carbon fractions, microbial community, and enzyme activity with the three aggregate classes: microaggregates (2 mm) under conventional cultivation (CC), integrated cultivation (IC), and organic cultivation (OC) in greenhouses. The results showed that (1) OC and IC promoted the formation of small macroaggregates and enhanced aggregate stability compared to CC; (2) SOC in the three size fractions of OC increased by 92.06–98.99% compared to CC; EOC increased by 98.47–117.59%; POC increased by 138.59–208.70%; MBC increased by 104.71–230.61%; and DOC increased by 21.93–40.90%, respectively; (3) organic cultivation significantly increased enzyme activity in all three particle-size aggregates and increased the relative abundance of bacteria in microaggregates as well as the relative abundance of fungi in small macroaggregates. Structural equation model (SEM) analysis revealed that organic farming practices fostered the development of smaller macroaggregates, elevated microbial and enzyme activities within soil aggregates, and facilitated the conversion of soil nutrients and carbon sequestration. Therefore, long-term organic cultivation increases soil carbon content and vegetable yield in greenhouses by increasing the proportion of small aggregates. In conclusion, long-term organic cultivation in greenhouses improves soil structure, increase soil fertility and vegetable yield, and has a positive impact on the environment. Organic cultivation increases soil fertility and contributes to maintaining ecological balance and protecting the environment in greenhouses.

Concrete-cored sand–gravel piles are a kind of composite pile formed by wrapping a concrete-cored pile with a sand–gravel shell, which has the advantages of both a rigid pile and bulk-material pile. The bearing characteristics of the concrete-cored sand–gravel pile composite foundation were investigated by establishing a three-dimensional discrete element numerical model for a cyclic dynamic loading test. The results show that the vertical stress of the core pile body fluctuates greatly at the beginning of loading, and the fluctuation amplitude decreases with the depth, and gradually tends to be stable in the middle and late stages, and the vertical-stress distribution is relatively uniform. The radial stress in the upper part of the core pile body fluctuates greatly, the fluctuation in the lower part is small, and the radial stress in each part of the core pile body gradually tends to be stable in the late-loading period. The radial stress factor of the core pile body reaches the stable speed with the foundation depth decreasing; the fluctuation amplitude of the pile-soil stress ratio decreases with the foundation depth and gradually tends to be stable with the increase in loading. The results of this study can provide a reference for the design and construction of a core sand pile composite foundation.

Drug-induced liver injury (DILI) is a common clinical pharmacogenic disease. In the United States and Europe, DILI is the most common cause of acute liver failure. Drugs can cause hepatic damage either directly through inherent hepatotoxic properties or indirectly by inducing oxidative stress, immune responses, and inflammatory processes. These pathways can culminate in hepatocyte necrosis. The role of the gut microecology in human health and diseases is well recognized. Recent studies have revealed that the imbalance in the gut microecology is closely related to the occurrence and development of DILI. The gut microecology plays an important role in liver injury caused by different drugs. Recent research has revealed significant changes in the composition, relative abundance, and distribution of gut microbiota in both patients and animal models with DILI. Imbalance in the gut microecology causes intestinal barrier destruction and microorganism translocation; the alteration in microbial metabolites may initiate or aggravate DILI, and regulation and control of intestinal microbiota can effectively mitigate drug-induced liver injury. In this paper, we provide an overview on the present knowledge of the mechanisms by which DILI occurs, the common drugs that cause DILI, the gut microbiota and gut barrier composition, and the effects of the gut microbiota and gut barrier on DILI, emphasizing the contribution of the gut microecology to DILI.

Abstract Background Hepatocyte-cholangiocyte transdifferentiation (HCT) is a potential origin of proliferating cholangiocytes in liver regeneration after chronic injury. This study aimed to determine HCT after chronic liver injury, verify the impacts of HCT on liver repair, and avoid harmful regeneration by understanding the mechanism. Methods A thioacetamide (TAA)-induced liver injury model was established in wild-type (WT-TAA group) and COX-2 panknockout (KO-TAA group) mice. HCT was identified by costaining of hepatocyte and cholangiocyte markers in vivo and in isolated mouse hepatocytes in vitro. The biliary tract was injected with ink and visualized by whole liver optical clearing. Serum and liver bile acid (BA) concentrations were measured. Either a COX-2 selective inhibitor or a β-catenin pathway inhibitor was administered in vitro. Results Intrahepatic ductular reaction was associated with COX-2 upregulation in chronic liver injury. Immunofluorescence and RNA sequencing indicated that atypical cholangiocytes were characterized by an intermediate genetic phenotype between hepatocytes and cholangiocytes and might be derived from hepatocytes. The structure of the biliary system was impaired, and BA metabolism was dysregulated by HCT, which was mediated by the TGF-β/β-catenin signaling pathway. Genetic deletion or pharmaceutical inhibition of COX-2 significantly reduced HCT in vivo. The COX-2 selective inhibitor etoricoxib suppressed HCT through the TGF-β-TGFBR1-β-catenin pathway in vitro. Conclusions Atypical cholangiocytes can be derived from HCT, which forms a secondary strike by maldevelopment of the bile drainage system and BA homeostasis disequilibrium during chronic liver injury. Inhibition of COX-2 could ameliorate HCT through the COX-2-TGF-β-TGFBR1-β-catenin pathway and improve liver function.

BackgroundThe molecular mechanisms of hepatic fibrosis (HF), closely related to autophagy, remain unclear. This study aimed to investigate autophagy characteristics in HF.MethodsGene expression profiles (GSE6764, GSE49541 and GSE84044) were downloaded, normalized, and merged. Autophagy-related differentially expressed genes (ARDEGs) were determined using the limma R package and the Wilcoxon rank sum test and then analyzed by GO, KEGG, GSEA and GSVA. The infiltration of immune cells, molecular subtypes and immune types of healthy control (HC) and HF were analyzed. Machine learning was carried out with two methods, by which, core genes were obtained. Models of liver fibrosis in vivo and in vitro were constructed to verify the expression of core genes and corresponding immune cells.ResultsA total of 69 ARDEGs were identified. Series functional cluster analysis showed that ARDEGs were significantly enriched in autophagy and immunity. Activated CD4 T cells, CD56bright natural killer cells, CD56dim natural killer cells, eosinophils, macrophages, mast cells, neutrophils, and type 17 T helper (Th17) cells showed significant differences in infiltration between HC and HF groups. Among ARDEGs, three core genes were identified, that were ATG5, RB1CC1, and PARK2. Considerable changes in the infiltration of immune cells were observed at different expression levels of the three core genes, among which the expression of RB1CC1 was significantly associated with the infiltration of macrophage, Th17 cell, natural killer cell and CD56dim natural killer cell. In the mouse liver fibrosis experiment, ATG5, RB1CC1, and PARK2 were at higher levels in HF group than those in HC group. Compared with HC group, HF group showed low positive area in F4/80, IL-17 and CD56, indicating decreased expression of macrophage, Th17 cell, natural killer cell and CD56dim natural killer cell. Meanwhile, knocking down RB1CC1 was found to inhibit the activation of hepatic stellate cells and alleviate liver fibrosis.ConclusionATG5, RB1CC1, and PARK2 are promising autophagy-related therapeutic biomarkers for HF. This is the first study to identify RB1CC1 in HF, which may promote the progression of liver fibrosis by regulating macrophage, Th17 cell, natural killer cell and CD56dim natural killer cell.

Cryptococcus neoformans poses a threat to human health, but anticryptococcal therapy is hampered by the emergence of drug resistance, whose underlying mechanisms remain poorly understood. Herein, we discovered that Isw1, an imitation switch chromatin remodeling ATPase, functions as a master modulator of genes responsible for in vivo and in vitro multidrug resistance in C. neoformans. Cells with the disrupted ISW1 gene exhibited profound resistance to multiple antifungal drugs. Mass spectrometry analysis revealed that Isw1 is both acetylated and ubiquitinated, suggesting that an interplay between these two modification events exists to govern Isw1 function. Mutagenesis studies of acetylation and ubiquitination sites revealed that the acetylation status of Isw1K97 coordinates with its ubiquitination processes at Isw1K113 and Isw1K441 through modulating the interaction between Isw1 and Cdc4, an E3 ligase. Additionally, clinical isolates of C. neoformans overexpressing the degradation-resistant ISW1K97Q allele showed impaired drug-resistant phenotypes. Collectively, our studies revealed a sophisticated acetylation–Isw1–ubiquitination regulation axis that controls multidrug resistance in C. neoformans.

Electrospun films (ESF) are gaining attention for active delivery due to their biocompatibility and biodegradability. This study investigated the impact of adding soy protein amyloid fibrils (SAFs) to ESF. Functional ESF based on SAFs/pullulan were successfully fabricated, with SAFs clearly observed entangled in the electrospun fibers using fluorescence microscopy. The addition of SAFs improved the mechanical strength of the ESF threefold and increased its surface hydrophobicity from 24.8° to 49.9°. Moreover, the ESF demonstrated antibacterial properties against Escherichia coli and Staphylococcus aureus. In simulated oral disintegration tests, almost 100% of epigallocatechin gallate (EGCG) dissolved within 4 min from the ESF. In summary, the incorporation of SAFs into ESF improved their mechanical strength, hydrophobicity, and enabled them to exhibit antibacterial properties, making them promising candidates for active delivery applications in food systems. Additionally, the ESF showed efficient release of EGCG, indicating their potential for controlled release of bioactive compounds.

This paper presents a novel multiscale explicit topology optimisation approach for concurrently optimizing the structure at the macro level and the bio-mimicking porous infillings at the micro level. Solid bar components with cross-section control at the macro level and sphere components at the micro level are constructed as the minimal control units to replace the manipulation of material distribution at each grid. The overlapping, moving and morphing of bar components provide the ability to generate flexible structural shapes at the macro level. Using the inspiration of the turtle shell (carapace), the sphere components are designed to move, overlap, and resize inside the bar to sufficiently mimic both the regular and irregular porous features. Classical beam designs, lattice structure designs and unit cell designs are illustrated as numerical examples to demonstrate the functionalities and correctness of the proposed method. As a result, the stochastic pores distribution and porosity control can be validated. The abilities of optimising lattice structure at truss-level and single unit cell level are demonstrated. Moreover, the samples are fabricated by selective laser melting (SLM) technology and then scanned with the X-ray micro-computed tomography (micro-CT) technique to further examine the manufacturability.

Systemic infection with Cryptococcus neoformans, a dangerous and contagious pathogen found throughout the world, frequently results in lethal cryptococcal pneumonia and meningoencephalitis, and no effective treatments and vaccination of cryptococcosis are available. Here, we describe Prm1, a novel regulator of C. neoformans virulence. C. neoformans prm1Δ cells exhibit extreme sensitivity to various environmental stress conditions. Furthermore, prm1Δ cells show deficiencies in the biosynthesis of chitosan and mannoprotein, which in turn result in impairment of cell wall integrity. Treatment of mice with heat-killed prm1Δ cells was found to facilitate the host immunological defence against infection with wild-type C. neoformans. Further investigation demonstrated that prm1Δ cells strongly promote pulmonary production of interferon-γ, leading to activation of macrophage M1 differentiation and inhibition of M2 polarization. Therefore, our findings suggest that C. neoformans Prm1 may be a viable target for the development of anti-cryptococcosis medications and, cells lacking Prm1 represent a promising candidate for a vaccine.

Bisphenol compounds (BPs) are one of the most significant raw materials, used in synthesizing high polymer materials. At present, common BPs mainly include bisphenol A, bisphenol B, bisphenol F, bisphenol AF and so on. Nowadays, BPs are principally applied in plastic products, the food packaging, drinking water additives, seafood and other fields. A large number of studies have found that BPs penetrate into human beings and animals by physical migration, chemical migration, biological migration and it even have been detected in deep-sea mammals, affecting the mechanisms of the reproductive system, central nervous system, digestive system, cardiovascular system, behavior, development, and metabolic diseases. Therefore, BPs have been attracting more attention. In the review, the classification, invasive pathway to foods of BPs, and its implication on human beings and animals are systematically reviewed, hoping to provide reference for the safety and toxicological evaluation of BPs.