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Tae Sik Goh,1,* Mihyang Ha,2,* Jung Sub Lee,1 Dae Cheon Jeong,3 Eun Sang Jung,4 Myoung-Eun Han,2 Yun Hak Kim,5,6 Sae-Ock Oh2 1Department of Orthopaedic Surgery and Biomedical Research Institute, Pusan National University Hospital, Busan, Republic of Korea; 2Department of Anatomy, School of Medicine, Pusan National University, Yangsan, Republic of Korea; 3Deloitte Analytics Group, Deloitte Consulting LLC, Seoul, Republic of Korea; 4Department of Bioenvironmental Energy, College of Life & Resources Science, Pusan National University, Miryang, Republic of Korea; 5Department of Anatomy and Department of Biomedical Informatics, School of Medicine, Pusan National University, Yangsan, Republic of Korea; 6Biomedical Research Institute, Pusan National University, Busan, Republic of Korea *These authors contributed equally to this work Background: Advances in genomics have greatly improved the survival rate in cancer patients. However, due to genetic heterogeneity, pancreatic ductal adenocarcinoma (PDAC) is still difficult to diagnose early, and its survival rate is extremely low. Therefore, we identified biomarkers that predict the prognosis of PDAC patients using independent cohort data. Materials and methods: To develop a novel prognostic biomarker, we used the gene expression and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Kaplan–Meier survival curve using median values of genes as cutoff showed that EIF4G1 was the only statistically significant gene in the 3 cohorts. We analyzed the prognostic significance of EIF4G1 using the time-dependent area under the curve (AUC) of Uno’s C-index, the AUC value of the receiver operating characteristics (ROC) at 3 years, and multivariate Cox analysis. We also compared EIF4G1 levels between tumors and matched non-tumor tissues. Results: EIF4G1 is the only prognostic gene in patients with PDAC, which was selected by Kaplan–Meier survival analysis. The survival curve showed that high expression of EIF4G1 was associated with poor prognosis of PDAC with a good discriminative ability in 3 independent cohorts. The risk stratifying ability of EIF4G1 was demonstrated by analyzing C-indices and AUC values. Multivariate Cox regression confirmed its prognostic significance. EIF4G1 expression was significantly higher in PDAC tissues than in the matched normal tissues. Conclusion: EIF4G1 could be used as a novel prognostic marker for PDAC and to determine suitable treatment options. Keywords: EIF4GI, pancreatic ductal adenocarcinoma, prognosis, GEO, TCGA

Tae Won Kwak,1,* Hee Jae Shin,2,* Young-Il Jeong,1 Myoung-Eun Han,3 Sae-Ock Oh,3 Hyun-Jung Kim,4 Do Hyung Kim,5 Dae Hwan Kang1 1Biomedical Research Institute, Pusan National University Hospital, Busan, 2Marine Natural Products Chemistry Laboratory, Korea Institute of Ocean Science and Technology, Ansan, 3Department of Anatomy, School of Medicine, Pusan National University, Gyeongnam, 4Genewel Co Ltd. Gyeonggi-do, 5School of Medicine, Pusan National University, Yangsan, Gyeongnam, Republic of Korea *These authors contributed equally to this work Background: The aim of this study is to investigate the anticancer activity of streptochlorin, a novel antineoplastic agent, in cholangiocarcinoma. Methods: The anticancer activity of streptochlorin was evaluated in vitro in various cholangiocarcinoma cell lines for apoptosis, proliferation, invasiveness, and expression of various protein levels. A liver metastasis model was prepared by splenic injection of HuCC-T1 cholangiocarcinoma cells using a BALB/c nude mouse model to study the systemic antimetastatic efficacy of streptochlorin 5 mg/kg at 8 weeks. The antitumor efficacy of subcutaneously injected streptochlorin was also assessed using a solid tumor xenograft model of SNU478 cells for 22 days in the BALB/c nude mouse. Results: Streptochlorin inhibited growth and secretion of vascular endothelial growth factor by cholangiocarcinoma cells in a dose-dependent manner and induced apoptosis in vitro. In addition, streptochlorin effectively inhibited invasion and migration of cholangiocarcinoma cells. Secretion of vascular endothelial growth factor and activity of matrix metalloproteinase-9 in cholangiocarcinoma cells were also suppressed by treatment with streptochlorin. Streptochlorin effectively regulated metastasis of HuCC-T1 cells in a mouse model of liver metastasis. In a tumor xenograft study using SNU478 cells, streptochlorin significantly inhibited tumor growth without changes in body weight when compared with the control. Conclusion: These results reveal that streptochlorin is a promising chemotherapeutic agent to the treatment of cholangiocarcinoma. Keywords: streptochlorin, cholangiocarcinoma, chemotherapeutic agent, invasion, metastasis

This paper deals with the design and experimental evaluation of an explicit tracking control system for a hydraulic actuator. The tracking control of hydraulic system has been widely applied to many application fields. However, since the hydraulic system has inherently hard nonlinear properties in dynamics, it is difficult to precisely control the position of the hydraulic system. Therefore a robust tracking control scheme was proposed to guarantee the tracking performance in this paper. To design the robust tracking control system, backstepping with sliding mode controller was applied. In order to evaluate the performance of the proposed controller, the experimental results were conducted.

The pathogenesis of inflammatory bowel disease (IBD) is closely associated with the dysfunction of the intestinal epithelial barrier, leading to increased bacterial translocation, leukocyte infiltration, and mucosal injury, which may act as a pivotal or incipient event in the pathophysiology of the disorder. The primary objective of this study is to examine the key genes implicated in IBD and the perturbation of intestinal epithelial cell function.

Abstract Surface ozone is an important air pollutant detrimental to human health and vegetation productivity, particularly in China. However, high resolution surface ozone concentration data is still lacking, largely hindering accurate assessment of associated environmental impacts. Here, we collected hourly ground ozone observations (over 6 million records), remote sensing products, meteorological data, and social-economic information, and applied recurrent neural networks to map hourly surface ozone data (HrSOD) at a 0.1° × 0.1° resolution across China during 2015–2020. The coefficient of determination (R2) values in sample-based, site-based, and by-year cross-validations were 0.72, 0.65 and 0.71, respectively, with the root mean square error (RMSE) values being 11.71 ppb (mean = 30.89 ppb), 12.81 ppb (mean = 30.96 ppb) and 11.14 ppb (mean = 31.26 ppb). Moreover, it exhibits high spatiotemporal consistency with ground-level observations at different time scales (diurnal, seasonal, annual), and at various spatial levels (individual sites and regional scales). Meanwhile, the HrSOD provides critical information for fine-resolution assessment of surface ozone impacts on environmental and human benefits.

【Objective】Coherent optical communication is a high-speed, high-quality, and highly secure communication method, and coherent detection plays an extremely important role in coherent optical communication. High sensitivity coherent detection systems can significantly increase the distance of coherent optical communication. By studying the factors that affect the sensitivity of coherent detection, targeted corrections can be made to improve the detection sensitivity.【Methods】This paper first briefly describes the principle of the coherence detection, and summarizes the research progress in this field at home and abroad. Then the paper analyzes the influence of thermal noise, shot noise, wavefront distortion, polarization loss, spot size deviation, optical axis deflection, coupling efficiency, detector performance, preamplifier and other aspects on coherence detection sensitivity of wireless optical coherence detection system.【Results】The results show that the influence of the thermal noise and shot noise of the system on the detection sensitivity can be minimized by controlling the local oscillator power. The wavefront distortion of signal light can be suppressed by adding an adaptive correction system. The polarization control compensation device can be used to compensate the polarization mismatch between signal light and local oscillator light. The deviation of spot size and optical axis deviation requires improving the processing level of hardware to reduce this error. The use of new detectors can improve the performance of detectors to a certain extent. The pre-amplifier can amplify weak signal light, which is crucial for improving detection sensitivity.【Conclusion】This article analyzes the factors that affect the sensitivity of wireless optical coherent detection, and summarizes the methods used by domestic and foreign scholars to improve detection sensitivity in recent years. It provides theoretical reference for improving the sensitivity of detection systems in practice, which has important significance for improving the performance of coherent optical communication systems.

To investigate the vaginal microbiota signature of patients with gynecologic cancer and evaluate its diagnostic biomarker potential. We incorporated vaginal 16S rRNA-seq data from 529 women and utilized VSEARCH to analyze the raw data. α-Diversity was evaluated utilizing the Chao1, Shannon, and Simpson indices, and β-diversity was evaluated through principal component analysis using Bray-Curtis distances. Linear discriminant analysis effect size (LEfSe) was utilized to determine species differences between groups. A bacterial co-abundance network was constructed utilizing Spearman correlation analysis. A random forest model of gynecologic tumor risk based on genus was constructed and validated to test its diagnostic efficacy. In gynecologic cancer patients, vaginal α-diversity was significantly greater than in controls, and vaginal β-diversity was significantly separated from that of controls; there was no correlation between these characteristics and menopause status among the subject women. Women diagnosed with gynecological cancer exhibited a reduction in the abundance of vaginal Firmicutes and Lactobacillus, while an increase was observed in the proportions of Bacteroidetes, Proteobacteria, Prevotella, Streptococcus, and Anaerococcus. A random forest model constructed based on 56 genus achieved high accuracy (area under the curve = 84.96%) in gynecological cancer risk prediction. Furthermore, there were discrepancies observed in the community complexity of co-abundance networks between gynecologic cancer patients and the control group. Our study provides evidence that women with gynecologic cancer have a unique vaginal flora structure and microorganisms may be involved in the gynecologic carcinogenesis process. A gynecological cancer risk prediction model based on characteristic genera has good diagnostic value.

Camouflage is a common technique in nature, enabling organisms to protect themselves from predators. The development of novel camouflage technologies, not only in fundamental science, but also in the fields of military and civilian applications, is of great significance. In this study, we propose a new type of deep-subwavelength four-layered meta-coating consisting of Si, Bi, Si, and Cr from top to bottom with total thickness of only ∼355 nm for visible-infrared compatible camouflage. The visible color and the infrared emission properties of the meta-coating can be independently adjusted. Colorful meta-coating for visible camouflage can be obtained by changing the thickness of top Si layer, while the selective high emissivity in non-atmospheric window for infrared camouflage remains. Due to the deep-subwavelength properties, the meta-coating shows high angle tolerance in both visible and infrared regions. The compatible camouflage capability of our proposed meta-coating in the visible-infrared region is validated under different environments. The deep-subwavelength, angular insensitivity, visible-infrared compatibility and large-area fabrication feasibility promise the meta-coating an effective solution for camouflage in various applications such as military weapons and anti-counterfeiting.

A joint policy of quality control, condition-based maintenance and spare ordering is proposed for a degradation system subject to the delay time concept. First, considering the fact that product quality is largely dependent on system state, a two-stage inspection policy is proposed, in which the system state is detected during the initial deterioration process, but the product quality is checked after the defective state is found by an inspection. Then, based on the condition inspection information, quality information and failure information, the corresponding maintenance activity is chosen. Combining the state of the spare part when the system replacement is required, all possible events during an inspection interval are discussed and then a mathematical model of average cost rate is established. Afterwards, a simulation-based optimization approach coupling discrete event simulation and response surface methodology is devised to obtain a near optimal joint policy. Finally, a numerical example is provided to demonstrate the effectiveness and applicability of the proposed policy by comparing it with the comparative policy.

ABSTRACTThe growing number of Mpox cases in China has posed a challenge to public health. The prevalence of men who have sex with men behaviors among students has been consistently increasing each year in China, accompanied by a high frequency of unprotected anal sex. As crowded places, schools are highly likely to cause an Mpox outbreak among students through long-term close contact. Understanding university students’ perceptions about Mpox and willingness to vaccinate play a vital role in implementing preventive measures in schools. This study aimed to assess knowledge, concerns, and vaccine acceptance toward Mpox among university students in North and Northeast China. A cross-sectional study was conducted among 3831 university students from seven universities in North and Northeast China between September 10 and September 25, 2023. This study found a relative insufficiency in Mpox knowledge among university students (71.60%), with less than half expressing concern about the Mpox outbreak (39.57%), and the majority exhibiting a positive attitude to vaccination (76.30%). Multivariate regression analysis revealed that a good knowledge level was associated with age, study discipline, education level, and a high level of concern about Mpox. Male, elderly, or highly educated participants had a low level of concern about Mpox. Participants with a high level of knowledge toward Mpox were more likely to have the vaccination willingness. This study might help governments and schools to understand students’ Mpox perceptions and vaccination intentions, enabling them to implement effective measures in addressing the issue of inadequate understanding regarding Mpox among university students.

In sedimentary environments, those geologically reasonable models can be built according to the characterizations and mechanisms of various sedimentary processes such as sediment transport, erosion, and deposition. In this work, a 3D modeling system, RealModel, is designed and developed to construct and predicate geologically reasonable objects (sedimentary rocks) according to the geological and geometrical information acquired from the outcrops while considering only two basic sedimentary processes (deposition and erosion). The RealModel is efficient, robust, and easy-to-use. We described RealModel regarding the software architecture, and software functionalities, and verified the accuracy by modeling an application example.

Summary: Ferroptosis and ferritinophagy play critical roles in various disease contexts. Herein, we observed that ferroptosis and ferritinophagy were induced both in the brains of mice with diabetes mellitus (DM) and neuronal cells after high glucose (HG) treatment, as evidenced by decreases in GPX4, SLC7A11, and ferritin levels, but increases in NCOA4 levels. Interestingly, melatonin administration ameliorated neuronal damage by inhibiting ferroptosis and ferritinophagy both in vivo and in vitro. At the molecular level, we found that not only the ferroptosis inducer p53 but also the ferritinophagy mediator NCOA4 was the potential target of miR-214-3p, which was downregulated by DM status or HG insult, but was increased after melatonin treatment. However, the inhibitory effects of melatonin on ferroptosis and ferritinophagy were blocked by miR-214-3p downregulation. These findings suggest that melatonin is a potential drug for improving diabetic brain damage by inhibiting p53-mediated ferroptosis and NCOA4-mediated ferritinophagy through regulating miR-214-3p in neurons.

Objective To evaluate the impact of the 'point to downstream hospital multi-department' emergency medical consortium model between Peking Union Medical College Hospital (PUMCH) and Beijing Longfu Hospital on the treatment of critically ill patients. Methods Clinical data of ICU patients at Beijing Longfu Hospital from December 2018 to November 2020 were retrospectively collected. The patients were categorized into two groups based on whether the emergency medical consortium was established: the pre-establishment group (December 2018 to November 2019) and the post-establishment group (December 2019 to November 2020). Clinical data, disease spectrum, examination/treatment utilization, and in-hospital mortality were compared between the two groups. Results A total of 350 ICU patients meeting the inclusion and exclusion criteria were included in this study. The pre-establishment group comprised 126 patients, while the post-establishment group had 224 patients(including 162 transferred via the consortium). In the pre-establishment group, the disease spectrum primarily consisted of common critical illnesses, with the top three diseases being acute cardiovascular diseases (34.1%), severe pneumonia (25.4%), and post-surgical cases (19.0%). In the post-establishment group, there was a greater diversity in the disease spectrum, with the top three diseases being severe pneumonia (31.2%), renal dysfunction (13.8%), and acute cerebrovascular disease (9.8%). Compared to the pre-establishment group, the post-establishment group had a lower average age [68.50(57.00, 79.00) years vs. 78.00(68.25, 84.00) years, P < 0.001], higher acute physiology and chronic health evaluation Ⅱ score [18.00(14.00, 24.00) points vs. 15.00(12.00, 22.75) points, P=0.005] and sequential organ failure assessment (SOFA) score [5.00(3.00, 7.25) points vs. 3.00(2.00, 6.00) points, P < 0.001], higher rates of central venous catheterization (52.7% vs. 20.6%, P < 0.001), continuous renal replacement therapy(22.3% vs. 4.0%, P < 0.001), vasoactive drug use (21.4% vs. 11.9%, P=0.037), and epinephrine usage (17.0% vs. 7.1%, P=0.015), and hospital stay [(11.61±9.41)days vs. (10.06±7.63)days, P=0.260], hospital costs [(18 982.35(9251.80, 51 677.59) CNY vs. 39 113.11(19 500.03, 68 981.90) CNY, P=0.067], and in-hospital mortality (12.1% vs. 10.3%, P=0.753) showed no significant changes. Furthermore, after the establishment of the emergency medical consortium, the ICU of Beijing Longfu Hospital admitted and treated 25 cases of difficult-to-treat patients (no difficult-to-treat patients were seen before the establishment of the emergency medical consortium) and used a number of new technologies, including bedside bronchoscopy in 9 cases and bedside ultrasound examination in 105 cases. Multivariable Logistic regression analysis results indicated that after adjusting for factors such as age and SOFA score, the establishment of the emergency medical consortium had no significant impact on in-hospital mortality among ICU patients (OR=0.994, 95% CI: 0.401-2.464, P=0.990). Conclusions After the establishment of the 'point to downstream hospital multi-department' emergency medical consortium between PUMCH and Beijing Longfu Hospital, the complexity and severity of diseases treated in Beijing Longfu Hospital's ICU increased, but the in-hospital mortality rate did not significantly rise. The emergency medical consortium model may contribute to enhancing the capacity for treating critically ill patients in downstream hospitals.

Abstract Background Patients with pancreatic ductal adenocarcinoma (PDAC) who undergo surgical resection and receive effective chemotherapy have the best chance for long‐term survival. Unfortunately, because of the heterogeneity of pancreatic cancer, it is difficult to find a personalized treatment strategy for patients. Organoids are ideal preclinical models for personalized medicine. Therefore, we explore the cultivation conditions and construction methods of PDAC organoid models to screen the individualized therapy strategy. Methods Fresh PDAC tissues from surgical resection were collected and digested with digestive enzymes; then the tumor cells were embedded in Matrigel with a suitable medium to establish the PDAC organoid models. The genetic stability of the organoids was analyzed using whole exon sequencing; hematoxylin and eosin staining and immunohistochemistry of organoids were performed to analyze their consistency with the pathological morphology of the patient's tumor tissue; After 2 days of organoid culture, we selected four commonly used clinical chemotherapy drugs for single or combined treatment to analyze drug sensitivity. Results Two cases of PDAC organoid models were successfully established, and the results of their pathological characteristics and exome sequencing were consistent with those of the patient's tumor tissue. Both PDAC organoids showed more sensitivity to gemcitabine and cisplatin, and the combined treatment was more effective than monotherapy. Conclusion Both organoids better retained the pathological characteristics, genomic stability, and heterogeneity with the original tumor. Individual PDAC organoids exhibited different sensitivities to the same drugs. Thus, this study provided ideal experimental models for screening individualized therapy strategy for patients with PDAC.

Abstract Vessel Traffic Service (VTS) significantly improves the navigation efficiency of ports. This paper proposes a model called Joint Extraction of Triples from the VHF Speech (JER‐VHF) to ensure the efficiency of the VTS. Numerous texts are extracted from the Very High Frequency (VHF) speech communication contents and these texts are organized into a dataset named VHFDT. The proposed model's transforming task transforms the voice communication contents of this dataset into a triple representation. VHFDT has a large number of overlapping triples. Therefore, this paper proposes a combined model with three categories to model the entity relations in VHF sentences, including pre‐training Chinese language model for initializing embedding from VHFDT, BiLSTM for rich features, and Multi‐head Attention for focusing on triples. In experimental part, this study uses Precision(P), Recall(R), and F1 to evaluate the accuracy and effectiveness of the proposed method and baseline models. According to experimental results, the proposed model efficiently extracts the key information from complex language environment and achieves better work on relational triple extraction than other baseline models. The model achieved an F1‐score of 83.2% on the overlapping testing data, which is an improvement of 1.8% compared to the second‐best baseline model.

Structural planes are one of the key factors controlling the stability of rock masses. A comprehensive understanding of the spatial distribution characteristics of structural planes is essential for accurately identifying key blocks, analyzing rock mass stability, and addressing various rock engineering challenges. This study compares the effectiveness of four stochastic structural plane generation methods—the Monte Carlo method, the Copula-based method, generative adversarial networks (GAN), and denoised diffusion models (DDPM)—in generating stochastic structural planes and capturing potential correlations between structural plane parameters. The Monte Carlo method employs the mean and variance of three parameters of the measured factual structural planes to generate data that follow the same distributions. The other three methods take the entire set of measured factual structural planes as the overall input to generate structural planes that exhibit the same probability distributions. Five sets of structural planes on four rock slopes in Norway are examined as an example. The validation and analysis were performed using histogram comparison, data feature comparison, scatter plot comparison, and linear regression analysis. The results show that the Monte Carlo method fails to capture the potential correlation between the dip direction and dip angle despite the best fit to the measured factual structural planes. The Copula-based method performs better with smaller datasets, and GAN and DDPM are better at capturing the correlation of measured factual structural planes in the case of large datasets. Therefore, in the case of a limited number of measured structural planes, it is advisable to employ the Copula-based method. In scenarios where the dataset is extensive, the deep generative model is recommended due to its ability to capture complex data structures. The results of this study can be utilized as a valuable point of reference for the accurate generation of stochastic structural planes within rock masses.

The combination of machine learning and optimization algorithms has been widely applied in the recognition of mine water inrush sources. However, the data of water inrush samples is stochastic and the optimization algorithm is prone to getting stuck in local optima. Further research is needed to improve the model's generalization capability and jump out of local optima. In order to solve the above problems, an improved sparrow search algorithm (SSA) is proposed to optimize the BP neural network model for quantitative recognition of mine water inrush sources. Taking Yangcheng Coal Mine of Luneng Coal and Electricity Co., Ltd. as the research object, the hydrochemical characteristics of the coal mine water sample are analyzed through conventional ion concentration analysis and Piper three line diagram. It is preliminarily determined that the mine water comes from the Ordovician limestone aquifer and the three limestone aquifers. The Na++K+ concentration, Ca2+ concentration, Mg2+ concentration, \begin{document}${\mathrm{HCO}}_3^- $\end{document} concentration, \begin{document}${\mathrm{SO}}^{2-}_4 $\end{document} concentration, Cl− concentration, mineralization degree, total hardness, and pH value are determined as the recognition indicators for water inrush source. The mine water inrush source recognition model is established based on an improved SSA-BP neural network. Firstly, the SSA parameters are set. Sine chaotic mapping is introduced to evenly distribute the sparrow population. Secondly, the sparrow population is updated by calculating fitness values, and a random walk strategy is introduced to perturb the current optimal individual. If the termination condition is met, the optimal BP neural network weight and threshold are obtained. Finally, based on the constructed BP neural network, the recognition results are output. The research results indicate the following points. ① The improved SSA-BP model has an recognition accuracy of 95.6% in the training set and 100% in the testing set. ② The comparison results of the improved SSA-BP neural network model with the BP neural network model and SSA-BP neural network model show that the BP neural network model has a misjudgment rate of 5/18, the SSA-BP neural network model has a misjudgment rate of 2/18, and the improved SSA-BP neural network model has a misjudgment rate of 0. After 10 iterations, it tends to stabilize and has the smallest error difference from the set target. The initial fitness value is the best, and the recognition results have high credibility. ③ Five sets of mine water samples from Yangcheng Coal Mine are inputted into the trained model as input layer data. The main sources of mine water samples are the Ordovician limestone aquifer, the three limestone aquifers, and the Shanxi formation aquifer. The results of model recognition are mutually confirmed with the conclusions of hydrochemical characteristic analysis, and precise segmentation is achieved.

IntroductionObstructive sleep apnea (OSA) is a common sleep-related breathing disorder, and has become a serious threat to public health. Intermittent hypoxia caused by OSA results in a low-grade inflammatory response that leads to impaired mucosal barrier function. Claudin (CLDN) molecules are important for the permeability of the mucosal epithelium. This study aimed to explore whether CLDN molecules can be a potential biomarker of OSA.MethodsA total of 37 healthy controls and 40 OSA patients underwent a physical assessment for OSA and filled out the STOP-Bang Questionnaire (SBQ) and Epworth Sleepiness Scale (ESS). Clinical specimens of plasma and urine were obtained to observe the difference between OSA patients and healthy controls and diagnostic accuracy of CLDN molecules for OSA.ResultsCLDN1, CLDN2, and CLDN3 molecules in plasma and urine decreased in OSA patients (both p < 0.05). The areas under the receiver operating characteristic curve (AUCs) of urinary CLDN1, plasma CLDN1, urinary CLDN2, plasma CLDN2, urinary CLDN3, and plasma CLDN3 were 0.887, 0.724, 0.779, 0.676, 0.828, and 0.665, respectively. The AUC of urinary CLDN1 + CLDN2 + CLDN3 was 0.906 (95% confidence interval (CI), 0.831–0.981). The AUC of plasma CLDN1 + CLDN2 + CLDN3 was 0.776 (95% CI, 0.645–0.878). The AUC of urinary CLDN3 + SBQ was 0.899 (95% CI, 0.832–0.967). The AUC of urinary CLDN3 + ESS was 0.896 (95% CI, 0.826–0.966). In addition, Urinary CLDN-3 was negative associated with the severity of OSA.ConclusionCLDN molecules are promising as useful biomarkers for OSA, which may be related to the impaired barrier function related to OSA.

Under the wave of digital technology, the integration of industry and education is increasingly becoming the direction of teaching construction in higher vocational colleges and universities. As the foundation of cultivating skilled talents, the construction of a financial industry college in higher vocational colleges is particularly important. Under the perspective of industry-teaching integration, the study combines the triple helix theory to carry out the high-quality construction of finance and economics colleges in higher vocational colleges, analyzes the influencing factors of the high-quality construction of finance and economics colleges in higher vocational colleges by using the DEMATEL algorithm and ISM algorithm, and explores the high-quality construction and development paths of finance and economics colleges by using the Fuzzy Set Qualitative Comparative Analysis (fsQCA) method. The results show that the top 6 influencing factors of high-quality construction of financial and industrial colleges in higher vocational institutions are infrastructure, public services, campus supervision, campus governance, safeguards, and teaching management, and their cause degrees are all greater than 0.5. The overall coverage of innovative development paths of financial and industrial colleges in higher vocational institutions is 0.692. The overall consistency is 0.925, and a total of 3 model paths have been explored, i.e., There are supply-based paths (H1, H3), environment-based paths (H2, H5), and supply-environment synergy paths (H4).

Substation network security is the key to maintaining the stable operation of power systems. In the face of growing threats of network attacks, traditional security protection measures have been brutal to meet the needs of modern power systems. Research on substation network security, situational awareness strategies, and remote operation and maintenance of equipment is essential to improve network defense capability and ensure the continuity and reliability of power supply. This study explores effective security situational awareness methods and remote operation and maintenance techniques to provide new solutions for substation network security. This paper builds an efficient network attack detection model by introducing linear discriminant analysis (LDA) and radial basis function (RBF) neural networks. The experiment uses the KDD Cup99 dataset, which is preprocessed to provide the model training and testing data. The LDA-RBF model in this paper outperforms the traditional RNF neural and BP neural networks regarding recognition rate. Specifically, the recognition rate reaches 90.2% for the Smurf attack and 100% for the Ipsweep attack. The proposed model of the study also performs well in terms of leakage and false alarm rates, with an overall recognition rate of 97.00%. This study proposes a network security situational awareness strategy and equipment remote operation and maintenance method that can effectively enhance substation networks’ security and operation and maintenance efficiency.

Microplastics (MPs) are carbon-rich polymers that are ubiquitous in the environment. With the increase of plastic production, microplastic pollution may be exacerbated and result in significant changes in microbial communities and biogeochemical processes such as carbon cycling, eventually impacting greenhouse gas emission and carbon storage in terrestrial ecosystems. However, current research on the effect of MPs on soil carbon cycling is still limited, and there is a lack of systematic review of the scattered information obtained from previous studies. Accordingly, this review provides a systematic overview of the current knowledge on the effects of MPs on soil carbon cycling and gives future research suggestions. Emerging evidence indicates that MPs could affect soil carbon stability and CO2 and CH4 emission by modifying soil physicochemical and microbiological properties; though biodegradable MPs often exhibit a greater effect than nonbiodegradable ones, the specific effects are highly dependent on plastic type, size and concentration. The specific mechanisms of MPs’ impact on soil carbon cycles remain elusive, which are discussed mainly from the perspective of microbial changes, including microbial biomass, microbial community composition, and key enzymes and functional genes associated with carbon metabolism. Further research is needed to elucidate whether MPs have a positive priming effect on soil carbon decomposition and the biotic and abiotic mechanisms involved. This review paper helps researchers gain a clearer picture of how and through which way MPs impact carbon cycling in soil ecosystems.

This paper combines the LDA theme mining model with social network algorithms to construct an objective evaluation model for the imagery of cherry blossoms in Japanese literature and culture. To determine the number of topics, one needs to observe the change in perplexity degree for various numbers of topics. The degree of influence of surrounding nodes on this node is measured using in-degree and out-degree, and the degree of closeness between users in social networks is measured using the clustering coefficient. Based on the network data, we analyzed Japanese literary works related to cherry blossoms and readers’ comments on related literary review websites, followed by analyzing the rate of microblog retweets when a hot literary work was published to determine the theme density. In the beginning, Topic 1, which represents positivity, has the highest theme intensity of 0.2581, indicating that the imagery of cherry blossoms is skewed toward the positive in the minds of readers and netizens. Following the emergence of hot literature, the spread of Topic2, which is associated with negativity, reached its peak, with a density that reached as high as 2235721 times. At this time, the highest high-frequency words are death 5827 times, and poignant 5748 times, all of which are negative meanings, and the theme intensity of Topic 2 is 0.2992. The impression of people can be negatively impacted by cherry blossoms. By constructing a model for literary analysis of imagery, this paper serves as a reference and presents a new direction for textual research.

Background: Mpox, one of the most serious threats to global health, is now being seen in small but rising numbers in Beijing, China. Our study aimed to investigate healthcare workers’ (HCWs) knowledge of Mpox and to explore reasons associated with their hesitancy to vaccinate against Mpox in Beijing, China. Methods: A cross-sectional study was conducted among HCWs in Beijing from July 24 to August 2, 2023, through an online questionnaire. Participants answered questions about sociodemographic characteristics, Mpox information sources, Mpox knowledge, perception of vaccines, and attitudes toward Mpox vaccination. We used Chi-squared test to compare difference in Mpox vaccination hesitancy between different groups. Multivariable logistic regression models were applied to analyze correlates of vaccination hesitancy among HCWs. Results: A total of 2331 HCWs completed the questionnaire, with an effective response rate of 92.45 % (2155/2331). Most of the HCWs in this study worked at tertiary hospitals (89.65 %), with a mean age of 36.69 ± 9.08 years. Among the 2155 participants, 52.99 % had over ten years of working experience, and 16.66 % were from high-risk departments relevant to Mpox treatment. Approximately 84.41 % knew about Mpox before this study, 80.79 % exhibited a high level of knowledge about Mpox, whereas 42.37 % were hesitant to be vaccinated against Mpox. Moreover, the hesitancy rate of HCWs in high-risk departments (47.91 %) was higher than in lower-risk departments (41.26 %). Higher educational level (aOR = 1.75, 95 %CI: 1.17–2.62), longer working years (1.71, 1.32–2.22), working at high-risk departments (1.34, 1.05–1.71), and lower level of knowledge about Mpox (1.78, 1.13–2.85) appeared as the most significant determinants of Mpox vaccination hesitancy among HCWs who knew about Mpox. For the HCWs who did not know about Mpox, longer working years (1.96, 1.02–3.78) were significant factors associated with their hesitancy. The predominant reason for hesitancy toward Mpox vaccination among HCWs encompassed apprehensions about vaccine side effects. Conclusion: HCWs had good knowledge of Mpox, whereas their Mpox vaccination hesitancy was also relatively high in Beijing, China. Increasing HCWs’ vaccination confidence and knowledge level about Mpox, especially for those working in high-risk departments, may be an essential way of reducing their hesitancy.

Shipping canals have supported maritime traffic and port development for many centuries. Radical transformations of these shipping landscapes through land reclamation, diking, and canalization were celebrated as Herculean works of progress and modernity. Today, shipping canals are the sites of increasing tension between economic growth and associated infrastructural interventions focused on the quality, sustainability, and resilience of natural systems and spatial settlement patterns. Shifting approaches to land/water relations must now be understood in longer political histories in which pre-existing alliances influence changes in infrastructure planning. On the occasion of the 150th Anniversary of the New Waterway (Nieuwe Waterweg), the Leiden-Delft-Erasmus universities PortCityFutures Center hosted an international symposium in October 2022 to explore the past, present, and future of this channel that links Rotterdam to the North Sea. Symposium participants addressed issues of shipping, dredging, and planning within in the Dutch delta, and linked them to contemporary debates on the environmental, spatial, and societal conditions of shipping canals internationally. The thematic issue builds on symposium conversations, and highlights the importance of spatial, economic, and political linkages in port and urban development. These spatial approaches contribute to more dynamic, responsive strategies for shipping canals through water management and planning.

The effect of secondary γ' phase evolution on the creep properties of single crystal superalloy DD6 was investigated at 760℃/785 MPa and 980℃/250 MPa by FESEM and TEM. The results indicate that the secondary γ' phases in DD6 alloy with standard heat treatment are precipitated in the matrix channel after exposure at 1120℃/4 h/AC. Since the secondary γ' phases in the matrix prevent the a/2〈011〉 dislocation gliding in the matrix channel and promote the {111}〈112〉 slip operated in the primary γ' phases at the beginning of creep at 760℃/785 MPa, the secondary γ' phases in the matrix channel decrease the incubation period and significantly improve the primary strain and creep rate. The secondary γ' phases in the matrix will dissolve rapidly at the beginning of creep at 980℃/250 MPa, therefore, the secondary γ' phases have no influence on the creep behaviour of 980℃/250 MPa.

Gut microbiota are closely related to health, and the β2-adrenergic receptor gene (ADRB2) is associated with gastrointestinal diseases. In the present study, we aimed to explore the relationship between ADRB2 gene polymorphisms and gut microbiota in Chinese Han adolescents. The relative abundance, diversity, and PICRUSt function predictions of male and female gut microbiomes differ significantly and that ADRB2 gene polymorphisms were associated with gut microbiome abundance in Chinese Han adolescents.

The stochastic structural plane of a rock mass is the key factor controlling the stability of rock mass. Obtaining the distribution of stochastic structural planes within a rock mass is crucial for analyzing rock mass stability and supporting rock slopes effectively. The conventional Monte Carlo method generates each parameter of stochastic structural planes separately without considering the correlation between the parameters. To address the above problem, this study novelly uses the denoising diffusion probabilistic model (DDPM) to generate stochastic structural planes. DDPM belongs to the deep generative model, which can generate stochastic structural planes without assuming the probability distribution of stochastic structural planes in advance. It takes structural plane parameters as an integral input into the model and can automatically capture the correlations between structural plane parameters during generation. This idea has been used for stochastic structural plane generation of the Oernlia slope in the eastern part of Straumsvatnet Lake, Nordland County, north-central Norway. The accuracy was verified by descriptive statistics (i.e., histogram, box plot, cumulative distribution curve), similarity measures (i.e., mean square error, KL divergence, JS divergence, Wasserstein distance, Euclidean distance), error analysis, and the linear regression plot. Moreover, the linear regression plots between the dip direction and the dip angle verified that DDPM can effectively and automatically capture the correlation between parameters.

BackgroundAngular leaf spot disease caused by plant pathogenic bacterium Xanthomonas fragariae seriously threatens strawberry crop production globally.MethodsIn this study, we sequenced the whole genome of X. fragariae YM2, isolated from Yunnan Province, China. In addition, we performed a comparative genome analysis of X. fragariae YM2 with two existing strains of X. fragariae YL19 and SHQP01 isolated from Liaoning and Shanghai, respectively.ResultsThe results of Nanopore sequencing showed that X. fragariae YM2 comprises one single chromosome with a contig size of 4,263,697 bp, one plasmid contig size of 0.39 Mb, a GC content ratio of 62.27%, and 3,958 predicted coding genes. The genome of YM2 comprises gum, hrp, rpf, and xps gene clusters and lipopolysaccharide (LPS), which are typical virulence factors in Xanthomonas species. By performing a comparative genomic analysis between X. fragariae strains YM2, YL19, and SHQP01, we found that strain YM2 is similar to YL19 and SHQP01 regarding genome size and GC contents. However, there are minor differences in the composition of major virulence factors and homologous gene clusters. Furthermore, the results of collinearity analysis demonstrated that YM2 has lower similarity and longer evolutionary distance with YL19 and SHQP01, but YL19 is more closely related to SHQP01.ConclusionsThe availability of this high-quality genetic resource will serve as a basic tool for investigating the biology, molecular pathogenesis, and virulence of X. fragariae YM2. In addition, unraveling the potential vulnerabilities in its genetic makeup will aid in developing more effective disease suppression control measures.

Development corridors are linear programmes of infrastructure and agriculture aiming to facilitate rapid socio-economic development. In Africa, they are a major development activity, with 88 underway or planned corridors. Drawing from extensive literature and insights gleaned from a 4 year research programme, this review scrutinizes the impacts of development corridors on people, wildlife and ecosystems in Kenya and Tanzania, proposing solutions to achieve better outcomes. The overarching goal was to discern the principle challenges emerging from the practical execution of the prevailing corridor model. The holistic approach taken, assessing the development corridors paradigm through an integrated ecological, social, and economic lens, provides novel insights that have not been possible using more traditional—siloed—research approaches. Eight key challenge areas are identified: impact assessments processes; coherence across international, national and local planning; governance; inclusivity; equality; impacts on biodiversity and ecosystem services; incorporation of future climate risks; and integrated water resource management. Poorly planned and implemented corridors detrimentally impact livelihoods and ecosystems. They lack a sustainable development vision, detailed social, environmental or climate risk assessments, and develop incrementally in policy and corporate spaces. There is also often a disconnect between investors and recipient governments, with some investors funding what governments request without applying internationally-recognised safeguards, and governments lacking capacity and resources to enforce regulations. We make recommendations for addressing these challenge areas. These aim to enhance impact assessment efficacy; integrate local perspectives into effective and inclusive corridor planning; overcome siloed project development and implementation; anticipate future development projections; and prioritise landscape preservation for enhanced ecosystem services and climate resilience.

During development, apoptosis removes redundant cells and ensures proper organ morphogenesis. Necrosis is long known as an adult-bound inflammatory and pathologic cell death. Whether there exists physiological necrosis during early development has been speculated but yet clearly demonstrated. Here, we report evidence of necroptosis, a type of programmed necrosis, specifically in perivascular cells of cerebral cortex and skin at the early stage of development. Phosphorylated Mixed Lineage Kinase Domain-Like protein (MLKL), a key molecule in executing necroptosis, co-expressed with blood endothelial marker CD31 and venous-lymphatic progenitor marker Sox18. Depletion of Mlkl did not affect the formation of blood vessel network but increased the differentiation of venous-lymphatic lineage cells in postnatal cerebral cortex and skin. Consistently, significant enhancement of cerebrospinal fluid diffusion and lymphatic drainage was found in brain and skin of Mlkl-deficient mice. Under hypobaric hypoxia induced cerebral edema and inflammation induced skin edema, Mlkl mutation significantly attenuated brain-blood-barrier damage and edema formation. Our data, for the first time, demonstrated the presence of physiological vascular-associated necroptosis and its potential involvement in the development of venous-lymphatic vessels.

Needle-punched (NP) carbon/carbon composites (CCCs) are widely used in structures re-entering the atmosphere of aerospace, thanks to their excellent mechanical properties. They are easily oxidized at high temperatures with atmospheric oxygen. The oxidation behavior is influenced by the process of heat conduction. In this study, longitudinal and transverse heat conduction in micro- and mesoscale models of CCCs was investigated. It was established that the heat transfer interface of a fiber bundle demonstrated peak-like morphology, while the punching structures of composites slowed down the process of heat conduction. Oxidation behavior of NP CCCs was predicted with a fractional Brownian motion strategy. It was found that the oxidized fiber bundles formed “bamboo shoots” morphology due to different oxidation rates of the matrix and fibers. Stochastic oxidation behavior was successfully described with this fractal strategy.

To further improve the prediction accuracy under the realization of rolling peak load prediction scenarios for the coming month, an aggregated hybrid two-phase decomposition with two-layer prediction model architecture (ICEEMDAN-SE-VMD-SSA-XBoost-MLR) is proposed in this paper. First, a fully integrated empirical modal decomposition with improved adaptive noise (ICEEMDAN) is used to initially decompose the historical peak load time series, which leads to several eigenmodal functions (IMFs), and by calculating the sample entropy (SE) of each IMF, the IMFs with similar SEs are aggregated and reconstructed into load components representing different time scales. Then, the variational modal decomposition (VMD) is introduced to quadratically decompose the less regular parts of the load components to fully weaken their non-smooth characteristics. Then, extreme gradient boosting (XGBoost) is used to assist in establishing the feature engineering, combining each load component to form the data set required for the prediction model, and using the sparrow search algorithm (SSA) optimized XGBoost with multiple linear regression (MLR) to construct the first layer prediction model for each component, and the prediction results of each component are superimposed to obtain the preliminary prediction results. Finally, inspired by the idea of integrated learning, an error correction link is proposed in this paper to make a secondary prediction of the preliminary prediction results by XGBoost, to better track the fluctuation of load details, realize the error correction of the preliminary prediction results and improve the prediction accuracy.

Primary hepatic carcinoma is a common malignant tumor. The classic molecular targeted drug sorafenib is costly and is only effective for some patients. Therefore, it is of great clinical significance to search for new molecular targeted drugs. Eupalinolide B (EB) from Eupatorium lindleyanum DC. is used to treat chronic tracheitis in clinical practice. However, the role of EB in hepatic carcinoma is unknown. In this study, we first measure the effect of EB on tumor growth in a xenograft model and PDX model. The cell proliferation and migration are also detected in human hepatocarcinoma cell lines (SMMC-7721 and HCCLM3). Then, we investigate cell cycle, cell apoptosis, cell necrosis, cell autophagy, and ferroptosis by flow cytometry, western blot analysis and electron microscopy. The results demonstrate that EB exerts anti-proliferative activity in hepatic carcinoma by blocking cell cycle arrest at S phase and inducing ferroptosis mediated by endoplasmic reticulum (ER) stress, as well as HO-1 activation. When HO-1 is inhibited, EB-induced cell death and ER protein expression are rescued. The migration-related mechanism consists of activation of the ROS-ER-JNK signaling pathway and is not connected to ferroptosis. In summary, we first discover that EB inhibits cell proliferation and migration in hepatic carcinoma, and thus EB is a promising anti-tumor compound that can be used for hepatic carcinoma.

Abstract Social dysfunction is the core syndrome of autism spectrum disorder (ASD) and lacks effective medicine. Although numerous risk genes and relevant environmental factors have been identified, the convergent molecular mechanism underlying ASD‐associated social dysfunction remains largely elusive. Here, we report aberrant activation of canonical Wnt signaling and increased glycolysis in the anterior cingulate cortex (ACC, a key brain region of social function) of two ASD mouse models (Shank3−/− and valproic acid‐treated mice) and their corresponding human neurons. Overexpressing β‐catenin in the ACC of wild‐type mice induces both glycolysis and social deficits. Suppressing glycolysis in ASD mice partially rescued synaptic and social phenotype. Axin2, a key inhibitory molecule in Wnt signaling, interacts with the glycolytic enzyme enolase 1 (ENO1) in ASD neurons. Surprisingly, an Axin2 stabilizer, XAV939, effectively blocked Axin2/ENO1 interaction, switched glycolysis/oxidative phosphorylation balance, promoted synaptic maturation, and rescued social function. These data revealed excessive neuronal Wnt‐glycolysis signaling as an important underlying mechanism for ASD synaptic deficiency, indicating Axin2 as a potential therapeutic target for social dysfunction.

Background Malaysia is strongly supported by the agriculture sector as the backbone to drive the economy. However, COVID-19 has significantly affected agriculture across the production, supply, and marketing chains. It also disturbs the balance of food supply and demand in Malaysia. COVID-19 was an unexpected pandemic that resulted in shock and panic and caused a huge global impact. However, the impacts of this pandemic on the agriculture sector in Malaysia, particularly in the production and supply chains, are still unclear and scarce. This review offers insights into the challenges, particularly in sustaining agri-food production and supply chains. It also highlights the opportunity and relevant measures towards sustainability in agriculture to avoid agri-food disasters in the future. Methods This study was carried out through a desk review of the secondary source of information covering the impact of COVID-19 in Malaysia particularly in the agri-food aspect, and a wide range of strategies and initiatives as the effective measures to overcome the crisis of this pandemic. Online desk research of the government published data and customer desk research were utilized to complete this study. Search engines such as Google Scholar and the statistical data from the official websites including the Department of Statistics Malaysia (DOSM) and the Food and Fertilizer Technology Center for the Asian and Pacific Region (FFTC-AP), were utilized. Keywords such as impact of COVID-19, pandemic, and agri-food supply chain were used to conduct the searches. The articles identified to be related to the study’s objective were then downloaded and included in the study. Descriptive methods were used as the primary analysis technique following the descriptive analysis and visual data analysis in performing the sources obtained. Results This devastating impact damages the lives by causing 4.3 million confirmed infections and more than 290,000 deaths. This disease presents an unprecedented challenge to the public health. The lockdown restriction under the movement control order (MCO), for more than of the world’s population in the year 2020 to control the virus from spreading, has disrupted most of the economic sectors. The agriculture industry was seen as one of the essential industries and allowed to operate under strict standard operating procedures (SOP). Working under strict regulations came with a huge price paid for almost all industries. Conclusion This pandemic has affected the national agri-food availability and accessibility in Malaysia. This outbreak created a reflection of opportunity for sharing a more flexible approaches in handling emergencies on agricultural food production and supply chains. Therefore, the government should be ready with the roadmap and enforce the measures to control the pandemic without disrupting the agri-food supply chain in the near future.

Objective temperature forecast products can achieve better forecast quality by using one-dimensional regression correction directly based on the present model temperature forecast product, and the forecast accuracy can be further improved by adding appropriate auxiliary factors. In this paper, ECMWF forecast products and ground observation data from Fujian are used to revise the surface temperature at 2 m by introducing a cloud cover forecast factor based on the model temperature forecast correction method. Analysis shows that the forecast deviation of daily maximum and minimum temperature after the revision of a single-factor forecast is obviously correlated with cloud cover. A variety of prediction schemes are designed, and the final scheme is determined through comparative testing. The following conclusions are drawn: all schemes based on cloud cover grouping can improve forecast performance, and the total cloud cover scheme is generally better than the low cloud cover scheme. There is a good positive correlation between the forecast deviation of maximum temperature and the mean total cloud cover; that is, the more cloud cover, the bigger the deviation. The minimum temperature is negatively correlated with cloud cover when the cloud cover is less than 40% and positively correlated for the rest. The absolute forecast deviations of the maximum and minimum temperatures are larger when the total cloud cover is less. Whether for Tmax or Tmin forecast, the binary regression scheme after grouping consistently showed the best performance, with the lowest MAE. The final scheme was used to forecast the maximum and minimum temperature in 2021, and most verification indicators showed improvement in most forecast periods. The forecast accuracy for the 36-h daily maximum and minimum temperature is 81.312% and 91.480%, respectively, which is 2.4%–2.6% higher than the single-factor regression scheme. The forecast skill scores (FSS) reach 0.065 and 0.086, indicating that the method can effectively improve forecast quality in a stable manner and can be used for practical forecasting.

The survey of fish diversity is an important part of the protection of the ecological health of rivers and lakes. Environmental DNA technology is a new tool to improve the accuracy of traditional morphological surveys of biodiversity and to monitor the amount of diversity. At present, there are few studies on monitoring fish diversity in lake inlets using eDNA technology. In this study, we used various types of estuaries in the Dianchi basin as the research object, used environmental DNA technology to monitor the fish diversity in typical estuaries, and analyzed the temporal and spatial changes and the relationship between environmental factors and fish diversity. In the Dianchi basin, we identified a total of 63 fish species belonging to 8 different orders, 21 families, and 51 genera across two seasons. The Carpidae family had the highest number of species, with Carassius auratus being the most prevalent species. The Shannon index analysis yielded a p-value of 0.0018 (Carassius auratus, Cyprinus carpio, Rhodeus sinensis, Acheilognathus chankaensis, and Coilia nasus all occurring at various points. The agricultural estuary differed substantially from the urban, suburban, and lake areas. Redundancy analysis revealed that the fish community structure during the dry period was primarily influenced by total phosphorus, pH, total nitrogen (TN), and chlorophyll. Conversely, during the rich period, the fish community structure was mainly influenced by dissolved oxygen and TN. This study demonstrated the utilization of environmental DNA technology in assessing the ecological health of rivers and lakes, specifically highlighting its effectiveness in exposing the ecological condition of a representative Dianchi estuary.

This study investigates the interplay between physical literacy, resilience, and burnout among researchers who experienced strict home quarantine during the COVID-19 pandemic in China, with a particular focus on the mediating role of resilience. Employing a two-stage sampling procedure, a total of 363 researchers from diverse disciplines, notably social science and natural science, were enlisted and administered a series of validated scales, including the Perceived Physical Literacy Scale (PPL), the 10-item Connor–Davidson Resilience Scale (CD-RISC-10), and the Chinese version of the Oldenburg Burnout Inventory (OLBL), via an anonymous online platform. The findings revealed substantial differences in physical literacy, resilience, and burnout across disciplines. Resilience partially mediated the relationship between physical literacy and burnout. Upon a closer examination of the sub-dimensions, resilience was found to fully mediate between factors of motivation, exhaustion, and disengagement. Moreover, one aspect of physical literacy—interaction with the environment—exhibited weaker correlations with both resilience and burnout compared to other dimensions of physical literacy. Overall, the study confirms the significant correlation between physical literacy and psychological parameters, establishing that elevated levels of both physical literacy and resilience serve as key factors in mitigating burnout during the pandemic.

Objective To analyze the relationship between the preoperative relative blood glucose ratio and the safety of cerebrovascular bypass of ischemic moyamoya disease (MMD) patients. Methods A total of 178 patients with ischemic MMD who were hospitalized in Department of Neurosurgery of Qilu Hospital of Shandong University from December 2016 to December 2019. A total of 186 cases underwent superficial temporal artery⁃middle cerebral artery (STA⁃MCA) bypass. The fasting blood glucose and glycated albumin of all patients at admission were recorded to calculate the relative blood glucose ratio. After STA⁃MCA bypass, the incidence of postoperative complications was counted. Univariate and multivariate Logistic regression were used to analyze the risk factors of postoperative complications of ischemic MMD. Results 186 cases were divided into 4 groups based on relative blood glucose ratio, Q1＜0.404, Q2 0.404-, Q3 0.456-, Q4≥0.534. The proportion of right surgery side in Q1 group was higher than that in Q3 group (χ2=4.762, P=0.029) and Q4 group (χ2=22.087, P=0.000), while the proportion of right surgery side in Q2 group (χ2=16.331, P=0.000) and Q3 group (χ2=7.355, P=0.007) was higher than that in Q4 group. The incidence of mild complications in Q1 group (χ2=6.389, P=0.011) and Q2 group (χ2=4.040, P=0.044) was higher than that in Q4 group. The incidence of postoperative complications was 28.49% (53/186), of which 8.60% (16/186) were severe type and 19.89% (37/186) were mild type, including transient neurological dysfunction 97.30% (36/37), subdural hemorrhage 2.70% (1/37). Logistic regression analysis showed that the relative blood glucose ratio increased (OR=1.484, 95%CI: 1.071-2.058; P=0.018), hypertension (OR=3.696, 95%CI: 1.805-7.569; P=0.000), operative interval＜2 months (OR=2.186, 95%CI: 1.041-4.590; P=0.039) was risk factors for postoperative complications. Conclusions In order to reduce the incidence of postoperative complications in patients with ischemic MMD, the operation interval after infarction can be extended to 2 months, and the preoperative relative blood glucose ratio should be closely monitored and the perioperative blood pressure should be controlled.

In order to study the interaction between zebra anthrax and scavenger jackals rabies, a deterministic infectious disease model was established. By using the basic theorem of differential equation, the nonnegativity and boundedness of the solution of the model were proved, the sufficient conditions for the existence of the equilibria given, three kinds of reproduction numbers of the model defined, and the stability of the equilibria was analyzed by linearization method and numerical simulation method. The effects of model parameters on the number of infected carcasses and infected jackals in equilibrium were studied by numerical simulation, and the interaction between anthrax and rabies was studied. The results show that anthrax and rabies can aggravate the transmission of each other.