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Abstract Background Emotional eating is a prevalent maladaptive coping mechanism among college students, which is associated with mental health and sleep concerns. Though previous studies have established a link between sleep quality, depression and emotional eating, most of these have been in Western populations. In addition, few existing studies have taken physical activities into account, and the underlying mechanisms between these four variables remain to be further studied. Therefore, our study investigated the mediating role of depression and the moderating role of physical activity levels in the relationship between sleep quality and emotional eating among Chinese college students. Our study can help to understand the characteristics of this population and provide guidance on the intervention pathways for emotional eating. Methods A convenience sampling method was employed to select eligible participants for investigation. The General Information Questionnaire, the Pittsburgh Sleep Quality Index Scale, the Patient Health Questionnaire, the Dutch Eating Behavior Scale, and the International Physical Activity Questionnaire were employed to measure the general condition, sleep quality, depression, emotional eating, and physical activity. A total of 813 college students (Mage = 19.14, SD = 1.12, range = 17 ~ 25 years old, 71.1% females) completed the survey. The moderated mediation analysis was carried out using the SPSS PROCESS macro. Results After controlling for sex, age, and body mass index (BMI), sleep quality positively predicted emotional eating. Depression primarily mediated the association between them. Besides, physical activity levels moderated the relationship between sleep quality and emotional eating via depression. Depression significantly predicted emotional eating among students with low levels of physical activity; however, it was not significant among students with moderate or high levels of physical activity. Conclusions The role of depression mediates the link between sleep quality and emotional eating. Regular exercise can ease the symptoms of emotional eating through depression. This implies the importance of offering more sleep hygiene education and physical activity in university settings.

Abstract The CRISPR-Cas12a system has revolutionized nucleic acid testing (NAT) with its rapid and precise capabilities, yet it traditionally required RNA pre-amplification. Here we develop rapid fluorescence and lateral flow NAT assays utilizing a split Cas12a system (SCas12a), consisting of a Cas12a enzyme and a split crRNA. The SCas12a assay enables highly sensitive, amplification-free, and multiplexed detection of miRNAs and long RNAs without complex secondary structures. It can differentiate between mature miRNA and its precursor (pre-miRNA), a critical distinction for precise biomarker identification and cancer progression monitoring. The system’s specificity is further highlighted by its ability to detect DNA and miRNA point mutations. Notably, the SCas12a system can quantify the miR-21 biomarker in plasma from cervical cancer patients and, when combined with RPA, detect HPV at attomole levels in clinical samples. Together, our work presents a simple and cost-effective SCas12a-based NAT platform for various diagnostic settings.

Abstract Most C–H bond activations of natural gas alkanes rely on transition metal complexes. Activations by using main-group systems have been reported but required heating or photo-irradiation under high atmospheric pressure with rather low regioselectivity. Here we report that Lewis acid-carbene adducts facilely undergo oxidative additions to C–H bonds of ethane, propane and n-butane with high selectivity under room temperature and atmospheric pressure. The Lewis acids can be moved by the addition of a base and the carbene-derived products can be easily converted into aldehydes. This work offers a route for main-group element compounds to selectively functionalise C–H bonds of natural gas alkanes and other small molecules.

Guided by the intelligent construction of coal mines and integrating the concept of the Cyber-Physical System (CPS), a novel approach to a coal mine information-physical fusion system is proposed. This concept emerges from the advancement of intelligent mines and the growing need for enhanced safety in coal mine operations. From a system safety perspective, this approach aims to effectively evaluate security issues by better integrating the informational and physical layers of intelligent mines. Currently, research in areas such as power grids and water networks has widely adopted concepts of cascade failures and robustness. It is suggested that the CPS framework be adapted to the mining sector. Considering the critical role of coal mines in China's energy security and their vulnerability to cyber attacks, a mine-specific CPS system is designed. This system incorporates a model of mine information-physical fusion, including networks for mine operations, management, and control, tailored to the unique conditions of mine shafts and underground settings. Utilizing Markov process theory, the paper delves into the theoretical study of the cascade failure process under deliberate attack strategies. This analysis is essential to effectively assess the safety issues within the information-physical system, providing vital support for fault prediction and safety analysis. The model of cascading failures in the mine information-physical system is developed, and based on an analysis of resilience and robustness, the study identifies key factors influencing the security of mine information-physical systems. Critical factors affecting the reliability of these systems include the number of system nodes, node coupling, edge count, and the interconnection methods of the dual-layer dependency network. The paper concludes by discussing the challenges in analyzing the security of information-physical systems and suggesting directions for future research.

ObjectiveTo understand the relationship between kidney function trajectories and cardiovascular disease (CVD) incidence among adult rural Uyghurs in Xinjiang Uyghur Autonomous Region (Xinjiang), and to provide a reference for early detection and prevention of CVD in the population. MethodsA total of 6 417 rural Uyghur residents aged ≥ 18 years in Regiment 51, Third Division of the Xinjiang Production and Construction Corps were recruited for a baseline survey in September 2016 using typical sampling. Follow-up surveys were conducted in April 2019, June 2020, July 2021 and June 2022 among 5 585 non-frequent migrants with complete basic information and no chronic kidney disease or CVD at baseline. Kidney function trajectories were constructed using a group-based trajectory model to determine the number and trend of trajectories. The log-rank test was used to compare the cumulative incidence of CVD among residents with different renal function trajectories. The Cox proportional hazards regression model was used to analyze the relationship between renal function trajectory groups and CVD incidence, and subgroup analysis and sensitivity analysis were used to validate the results. ResultsAs of June 2022, 414 (7.41%) of the 5 585 participants were lost to follow-up; after excluding 429 participants with < 3 serum creatinine measurements, a total of 4 742 participants were finally included in the analysis, with a total follow-up of 27 018.48 person-years and a mean follow-up of 5.70 ± 0.96 person-years. A total of 563 cases of CVD were observed during the follow-up period, with a cumulative incidence of 11.87%. Based on the group-based trajectory model analysis, the 4 742 participants were classified into four groups with different kidney function trajectories: high-level stable progression of estimated glomerular filtration rate (eGFR) group (2 128 individuals, 44.88% of the participants), gradually increasing eGFR group (1207, 25.45%), gradually decreasing eGFR group (988, 20.84%), and rapidly decreasing eGFR group (419, 8.83%), respectively; the cumulative incidence of CVD observed at follow-up in these groups was 232, 87, 156, and 88, with significantly different cumulative incidence rates of 10.90%, 7.21%, 15.79%, and 21.00% (χ2 = 74.882, P < 0.001). After adjustment for sex, age, smoking status, alcohol consumption, hypertension, diabetes, overweight/obesity, dyslipidaemia/hypertension/diabetes/CVD/stroke, the Cox proportional hazards regression model analysis showed that, compared with those in the high stable eGFR group, participants in the gradually increasing eGFR group had a reduced risk of CVD incidence (hazard ratio [HR] = 0.766, 95% confidence interval [95%CI]: 0.598 – 0.983), whereas participants in the gradually decreasing eGFR group and the rapidly decreasing eGFR group had an increased risk of CVD incidence, with HR (95%CI) of 1.297 (1.059 – 1.590) and 1.865 (1.458 – 2.385), respectively; further subgroup analysis revealed HR (95%CI) of 2.577 (1.698 – 3.909), 1.629 (1.196 – 2.220), 1.729 (1.078 – 2.774), and 1.867 (1.399 – 2.492) for participants who were male, female, < 45 years of age, and ≥ 45 years of age in the rapidly declining eGFR group, respectively. Sensitivity analysis results after sequential exclusion of those with hypertension, diabetes and dyslipidaemia at baseline showed increased risks of CVD incidence in participants in the rapidly declining eGFR group, with HR (95%CI) of 1.638 (1.157 – 2.319), 1.854 (1.426 – 2.410) and 1.667 (1.227 – 2.264) compared with those in the high-grade stable eGFR group, indicating good robustness of the results. ConclusionBoth increasing and decreasing eGFR trajectories are associated with the risk of CVD incidence among rural Uyghur residents in Xinjiang; those with increasing eGFR have a decreased risk of CVD incidence, whereas those with decreasing eGFR have an increased risk of CVD incidence.

Objectives: Triple-negative breast cancer (TNBC) is the deadliest subtype of breast cancer (BC). Tumor-derived extracellular vesicles (EVs) trigger tumor progression by promoting M2 polarization. Some lncRNAs can be encapsulated into EVs for intercellular communication. Herein, we investigated the mechanism of TNBC-derived EV-shuttled lncRNA MALAT1 on macrophage polarization/tumorigenesis. Methods: BC-associated targeted EV-derived lncRNAs were screened. Tumor tissues/tissues adjacent to cancer of TNBC patients, and blood samples of all subjects were collected. MALAT1/POSTN mRNA levels in tumor tissues/tissues adjacent to cancer, and MALAT1 expression in EVs and its correlation with TNBC patient overall survival were assessed by RT-qPCR/Kaplan-Meier survival analysis/log-rank test. TNBC patient M2 infiltration was detected by flow cytometry. MALAT1/POSTN levels in EVs/macrophages were regulated by transfection. Hippo/YAP activation was determined by Western blot. Nude mouse xenograft model was established and metastasis was detected by H&E staining. Results: MALAT1/POSTN were up-regulated and correlated with M2 infiltration/poor prognosis in TNBC patients. TNBC-derived EVs induced M2 polarization. MALAT1 was highly expressed in TNBC-derived EVs and could be transferred to macrophages via EVs to induce M2 polarization. POSTN overexpression diminished the inhibitory effect of MALAT1 knockdown on M2 markers. EVs activated the Hippo/YAP pathway in macrophages. The Hippo/YAP pathway inhibition abrogated the effect of POSTN overexpression on M2 marker expression. TNBC-EV-derived MALAT1 facilitated M2 polarization, and thus promoting occurrence and metastasis of TNBC in vitro and in vivo. Conclusions: TNBC-EV-derived MALAT1 activated the Hippo/YAP axis by up-regulating POSTN, thereby inducing M2 polarization to promote TNBC occurrence and metastasis in vivo.

ObjectiveTo explore the association and predictive value of non-high-density lipoprotein cholesterol (Non-HDL-C), apolipoprotein B (ApoB) and low-density lipoprotein cholesterol (LDL-C) with metabolic syndrome (MS) in adult rural residents of Xinjiang Uygur Autonomous Region for facilitating early identification and prevention of MS in the residents. MethodsThe study enrolled 6 500 Uygur residents aged ≥ 18 years from 12 villages in the Kashgar region of Xinjiang Uygur Autonomous Region (Xinjiang) using a multistage random cluster sampling method. Face-to-face interviews were conducted during July-August 2017 using a self-designed questionnaire, along with physical examinations and laboratory tests. Unconditional multivariate logistic regression analysis and receiver operating characteristic (ROC) curve analysis were employed to assess the association between Non-HDL-C, ApoB, and LDL-C with MS, as well as to evaluate their predictive value for MS. ResultsThe analysis finally included a total of 5 156 participants, among whom 885 (17.2%) were identified as having MS. After adjusting for potential confounding factors including gender, age, education, smoking status, alcohol consumption, and body mass index, the results of multivariate unconditional logistic regression analysis revealed a significantly increased risk of MS among participants in the highest quartile of Non-HDL-C levels (odds ratio [OR] = 1.764; 95% confidence interval [CI]: 1.350 – 2.305). Similarly, participants in the third and highest quartiles of ApoB had a higher risk compared to those in the lowest quartile (OR = 1.372; 95%CI: 1.048 – 1.798 and OR = 1.645; 95%CI: 1.273 – 2.124 respectively). Additionally, individuals in the highest quartile of LDL-C had an elevated risk compared to those in the lowest quartile (OR = 1.403; 95%CI: 1.080 – 1.823). The receiver operating characteristic (ROC) analysis results revealed that Non-HDL-C, ApoB, and LDL-C had area under the curve (AUC) values of 0.654 (95%CI: 0.641 – 0.667), 0.608 (95%CI: 0.595 – 0.622), and 0.612 (95%CI: 0.592 – 0.633), respectively, as diagnostic indicators for metabolic syndrome in the study participants. Furthermore, Non-HDL-C demonstrated a significantly higher AUC compared to both ApoB and LDL-C (both P < 0.05). ConclusionThe prevalence of MS is relatively high among adult Uygur residents in rural Xinjiang, and Non-HDL-C demonstrates a stronger correlation and predictive value for MS compared to ApoB and LDL-C.

Seroma formation and poor wound healing are common complications of many surgeries that create anatomical dead space (i.e., mastectomy), often causing tissue infection and even necrosis. Although negative pressure drainage and tissue adhesives are investigated to alleviate fluid accumulation post-surgery, however, their therapeutic efficacy remains unsatisfactory in most cases. Herein, the catechol-rich chemically crosslinked gelatin microspheres (ca-CGMSs) have been developed as biodegradable reconstructive implants for preventing seroma formation and concurrently promoting subcutaneous wound healing. Compared with the most representative hydrogel adhesive, i.e. commercial porcine fibrin sealant (PFS), the loosely packed ca-CGMSs with diameters range from 50 to 350 μm, provide numerous cell-adhesive interfaces and interconnected macro-pores for enhanced cell adhesion, proliferation and migration. Subcutaneous embedding trials show the in situ swelling aggregation and wet tissue adhesion of ca-CGMSs as well as their capacity in recruiting autologous cells in rat mastectomy models. The trials in rabbit mastectomy models demonstrate that, compared with PFS gluing, the implanted dried ca-CGMSs not only significantly inhibit seroma formation, but also achieve enhanced wound healing by inducing the formation of vascularized neo-tissue. The ca-CGMSs show a great potential to be the next-generation of restorative materials for both preventing seroma formation and healing subcutaneous wounds.

The problem of finite-time guaranteed-cost $H_{\infty } $ control is studied for time-varying systems with actuator saturation using a memory dynamic event-triggered mechanism. By means of the dead-zone nonlinearity and the memory-based feedback controller, a guaranteed-cost function (GCF) considering actuator saturation and memory feedback data packets is constructed. A memory dynamic event-triggered mechanism is proposed, considering the historical transmitted data packets and a dynamic event-triggered threshold, and it can achieve a balance between saving network resources and maintaining the system performance. Furthermore, based on the constructed time-varying Lyapunov functional and the finite-time stability theory, sufficient conditions for guaranteeing $H_{\infty } $ finite-time boundedness of the closed-loop time-varying system are given. These conditions also provide the upper bound of the GCF. By virtue of the interpolation formula, tractable recursive linear matrix inequality (RLMI) conditions are proposed to obtain the desired memory-based controller gains and event-triggered weighting matrix. Moreover, an RLMI-based algorithm is given to obtain the optimal values of GCF’s upper bound, finite-time stability and $H_{\infty }$ performance index. Finally, the feasibility and superiority of the method are verified by a simulation example.

Abstract Background With the rapid development of China’s chemical industry, although researchers have developed many methods in the field of chemical safety, the situation of chemical safety in China is still not optimistic. How to prevent accidents has always been the focus of scholars’ attention. Methods Based on the characteristics of chemical enterprises and the Heinrich accident triangle, this paper developed the organizational-level accident triangle, which divides accidents into group-level, unit-level, and workshop-level accidents. Based on 484 accident records of a large chemical enterprise in China, the Spearman correlation coefficient was used to analyze the rationality of accident classification and the occurrence rules of accidents at different levels. In addition, this paper used TF-IDF and K-means algorithms to extract keywords and perform text clustering analysis for accidents at different levels based on accident classification. The risk factors of each accident cluster were further analyzed, and improvement measures were proposed for the sample enterprises. Results The results show that reducing unit-level accidents can prevent group-level accidents. The accidents of the sample enterprises are mainly personal injury accidents, production accidents, environmental pollution accidents, and quality accidents. The leading causes of personal injury accidents are employees’ unsafe behaviors, such as poor safety awareness, non-standard operation, illegal operation, untimely communication, etc. The leading causes of production accidents, environmental pollution accidents, and quality accidents include the unsafe state of materials, such as equipment damage, pipeline leakage, short-circuiting, excessive fluctuation of process parameters, etc. Conclusion Compared with the traditional accident classification method, the accident triangle proposed in this paper based on the organizational level dramatically reduces the differences between accidents, helps enterprises quickly identify risk factors, and prevents accidents. This method can effectively prevent accidents and provide helpful guidance for the safety management of chemical enterprises.

Abstract Background Metabolic dysfunction-associated fatty liver disease (MAFLD) is the most common chronic liver disease in China. Our study aimed to evaluate the screening value of the fatty liver index (FLI), hepatic steatosis index (HSI), lipid accumulation product (LAP), visceral adiposity index (VAI), and Zhejiang University index (ZJU), as well as other single indicators for MAFLD. We aimed to find the optimal screening tool and its appropriate cut-off values for rural Uyghur adults. Methods We completed a survey of 14,321 Uyghur adults in 51 groups in Kashgar, Xinjiang, in 2016 using a typical sampling method, with 12,794 patients ultimately included in statistical analyses. Fatty liver was diagnosed using ultrasonography. Results The prevalence of fatty liver disease (FLD) and MAFLD was 16.73% and 16.55%, respectively, and the FLI, HSI, LAP, VAI, and ZJU were all independently associated with an increased risk of MAFLD. The areas under the receiver operating characteristic curves (AUCs) of the FLI for diagnosing MAFLD in men and women were 0.853 and 0.847, respectively. The AUCs of the body mass index (BMI) for diagnosing MAFLD in men and women were 0.850 and 0.852, respectively. Compared with other metabolic-related markers, FLI had the largest AUC. In men, the optimal cut-off values of FLI and BMI for diagnosing MAFLD were 45 (sensitivity 84.83%, specificity 69.57%) and 27.4 (sensitivity 78.47%, specificity 76.30%), respectively. In women, the optimal cut-off values of FLI and BMI for diagnosing MAFLD were 45 (sensitivity 80.11%, specificity 74.23%) and 28.0 (sensitivity 79.56%, specificity 75.41%), respectively. In men and women, an FLI score of

The objective of this study is to enhance the resilience of the coal-to-liquids (CTL) industrial chain and supply chain to withstand increasing shock pressures. There is an urgent need to improve the resilience of the industrial chain and supply chain. This paper identifies 21 resilience-influencing factors from 4 perspectives: absorption capacity, adaptability, recovery capacity, and self-learning capacity; it then constructs an evaluation indicator system. The Interval Type 2 Fuzzy-Decision-Making Trial and Evaluation Laboratory-Analytic Network Process (IT2F-DEMATEL-ANP) method is adopted to determine the weights of the indicator system, and a resilience evaluation is performed based on the Interval Type 2 Fuzzy-Prospect Theory-Technique for Order Preference by Similarity to an Ideal Solution (IT2F-PT-TOPSIS) method. Furthermore, in the case of the CTL industrial chain and supply chain of China Shenhua Energy Group Ningxia Coal Industry Co., Ltd. (CENC) (Ningxia, China), this study ranks the resilience level from 2018 to 2022 to identify the factors that have contributed to a reduction in resilience and to implement measures to enhance the resilience of the CTL industrial chain and supply chain. The results show that the level of the CTL industrial chain and supply chain resilience was lowest in 2020, while it was highest in 2021. Factors such as the degree of domestication of key technologies, the rationality of the CTL industry layout, and the stability of supply and demand chains are identified as significant determinants of resilience levels. This points the way to enhancing the resilience of the CTL industry and supply chain.

Systematic management of corporate safety risks in industrial parks has become a hot topic. And risk prevention and control mutual aid is a brand-new model in the risk and emergency management of the park. In the context of blockchain, how to incentivize enterprises to actively invest in safety risk prevention and control mutual aid has become a series of key issues facing government regulators. This paper innovatively combines Prospect Theory, Mental Accounting, and Evolutionary Game Theory to create a hypothetical model of limited rationality for the behavior of key stakeholders (core enterprises, supporting enterprises, and government regulatory departments) in mutual aid for safety risk prevention and control. Under the static prize punishment mechanism and dynamic punishment mechanism, the evolutionary stabilization strategy of stakeholders was analyzed, and numerical simulation analysis was performed through examples. The results show: (1) Mutual aid for risk prevention and control among park enterprises is influenced by various factors, including external and subjective elements, and evolves through complex evolutionary paths (e.g., reference points, value perception). (2) Government departments are increasingly implementing dynamic reward and punishment measures to address the shortcomings of static mechanisms. Government departments should dynamically adjust reward and punishment strategies, determine clearly the highest standards for rewards and punishments, and the combination of various incentives and penalties can significantly improve the effectiveness of investment decisions in mutual aid for safety risk prevention and control. (3) Continuously optimizing the design of reward and punishment mechanisms, integrating blockchain technology with management strategies to motivate enterprise participation, and leveraging participant feedback are strategies and recommendations that provide new insights for promoting active enterprise investment in mutual aid for safety risk prevention and control. The marginal contribution of this paper is to reveal the evolutionary pattern of mutual safety risk prevention and control behaviors of enterprises in chemical parks in the context of blockchain.

The carbon quota allocation method serves as the foundation for the design of the carbon trading mechanism, which has a significant impact on supply chain production decisions and the operational efficiency of the carbon trading market. To analyze the behavioral decision problem of supply chain members under different carbon quota allocation methods, the low-carbon reference effect is introduced to characterize the effect of consumers’ low-carbon preference on market demand. On this basis, three differential game models are constructed, namely, no emissions penalty, trading under the grandfathering principle, and trading under the benchmarking principle. The results indicate that the implementation of carbon trading policies enhances consumers’ low-carbon reference levels, the carbon emission reduction levels of manufacturers, and the low-carbon publicity levels of retailers. Moreover, the enhancement of the low-carbon reference effect becomes a positive driver of profit growth. Manufacturers are observed to make more efforts in carbon reduction under the benchmarking principle compared to the grandfathering principle. In contrast, the level of low-carbon publicity by retailers remains unchanged. The above findings can provide a scientific basis for the decision-making of emission reduction in low-carbon supply chain enterprises, which has certain theoretical significance.

Rivers in arid areas play a crucial role in sustaining the basin, regional economic, ecological security and social development. Maintaining the ecological health of the basin ecosystem is the guarantee for high-quality regional development. Developing a robust and unbiased evaluation index system is pivotal for the scientific assessment of basin health. Quantitative evaluation of the ecological health of inland river basins in arid areas under the influence of human activities is a necessary condition for basin scientific management and policy formulation. This paper presents a conceptual DPSIRM model (Driving Force - Pressure - State - Impact - Response - Management), selects 33 indicators for constructing the evaluation index system, recommends the AHP (Analytic Hierarchy Process) for subjective weight assignment, utilizes the CRITIC (Criteria Importance Through Intercriteria Correlation) method for objective weight determination, and amalgamates subjective and objective weights to establish CW (comprehensive weights). On this basis, the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method is employed to assess the relative closeness between the health degree of the Shiyang River Basin and the ideal solution from 2000 to 2020, and the alteration in the basin’s health is judged according to the relative closeness. The results showed that the health level of the Shiyang River Basin gradually increased from 0.41 to 0.61, transformed from subhealthy to healthy. Among the six subsystems, driving force, state, impact and response health were all subhealth, while stress and management health were ideal. The analysis of the index impact weights illustrated that the average annual precipitation, urbanization rate, population density, irrigation water consumption per hectare, and water consumption per 10,000 yuan of gross domestic product (GDP) with a significant influence on the ecological health of the basin. This research demonstrated a novel analytical framework for assessing the health of inland basins in dry regions. The findings may serve as a basis for management departments to develop specific basin planning and management policies.

ABSTRACTBovine enterovirus (BEV) consisting of enterovirus species E (EV-E) and F (EV-F) is the causative agent associated with respiratory and gastrointestinal diseases in cattle. Here, we reported the characterization, genetic diversity, and recombination of novel BEV strains isolated from the major cattle-raising regions in China during 2012–2018. Twenty-seven BEV strains were successfully isolated and characterized. Molecular characterization demonstrated that the majority of these novel BEV strains (24/27) were EV-E, while only few strains (3/27) were EV-F. Sequence analysis revealed the diversity of the circulating BEV strains such as species and subtypes where different species or subtype coinfections were detected in the same regions and even in the same cattle herds. For the EV-E, two novel subtypes, designated as EV-E6 and EV-E7, were revealed in addition to the currently reported EV-E1–EV-E5. Comparative genomic analysis revealed the intraspecies and interspecies genetic exchanges among BEV isolates. The representative strain HeN-B62 was probably from AN12 (EV-F7) and PS-87-Belfast (EV-F3) strains. The interspecies recombination between EV-E and EV-F was also discovered, where the EV-F7-AN12 might be from EV-E5 and EV-F1, and EV-E5-MexKSU/5 may be recombined from EV-F7 and EV-E1. The aforementioned results revealed the genetic diversity and recombination of novel BEV strains and unveiled the different BEV species or subtype infections in the same cattle herd, which will broaden the understanding of enterovirus genetic diversity, recombination, pathogenesis, and prevention of disease outbreaks.IMPORTANCEBovine enterovirus (BEV) infection is an emerging disease in China that is characterized by digestive, respiratory, and reproductive disorders. In this study, we first reported two novel EV-E subtypes detected in cattle herds in China, unveiled the coinfection of two enterovirus species (EV-E/EV-F) and different subtypes (EV-E2/EV-E7, EV-E1/EV-E7, and EV-E3/EV-E6) in the same cattle herds, and revealed the enterovirus genetic exchange in intraspecies and interspecies recombination. These results provide an important update of enterovirus prevalence and epidemiological aspects and contribute to a better understanding of enterovirus genetic diversity, evolution, and pathogenesis.

ObjectiveTo explore the prevalence and influencing factors of chronic diseases and chronic multimorbidity among Uygur rural adult residents in Xinjiang Production and Construction Corps (Xinjiang). MethodsUsing typical sampling, we recruited 14 851 Uygur rural residents aged ≥ 18 years in Xinjiang and conducted face-to-face interview with a self-designed questionnaire, physical examination, and laboratory tests among the residents during August – September 2016. Multivariate logistic regression model was used to analyze influencing factors of chronic diseases and chronic multimorbidity among the residents. ResultsOf the 12 792 eligible participants, 8 937 (69.9%) were identified as having chronic diseases and 5 770 (45.1%) having chronic multimorbidity. The three diseases most frequently identified among the participants were metabolic syndrome (identified in 33.1% of the participants), dyslipidemia (30.8%), and hypertension (29.9%); the observed top three multimorbidities of two chronic conditions were dyslipidemia and hypertension (observed in 12.2% of the participants), metabolic syndrome and fatty liver (9.7%), and dyslipidemia and fatty liver (8.8%); and the observed top three multimorbidities of three chronic conditions were metabolic syndrome, dyslipidemia and fatty liver (6.8%), metabolic syndrome, hypertension and fatty liver (6.0%), and metabolic syndrome, hypertension and musculoskeletal disorder (4.4%). The results of multivariate logistic regression analysis revealed following risk factors for chronic diseases and chronic multimorbidity: aged 40 years or older, being married or divorced or widowed, with family history of chronic diseases, being obesity or overweight, and having central obesity; while, having the education of primary school and above was a protective factor against chronic diseases and chronic multimorbidity. ConclusionThe prevalence of chronic diseases and chronic multimorbidity were high and mainly influenced by age, education, marital status, family history of chronic disease, obesity or overweight, and central obesity among Uygur rural adults in Xinjiang.

ObjectiveTo construct a metabolic syndrome (MS) factors-based model for predicting the risk of coronary heart disease (CHD) among rural residents of Xinjiang Uygur Autonomous Region (Xinjiang) for CHD prevention and treatment in the population. Methods Complete baseline information were collected through face-to-face questionnaire interview, physical examination and laboratory tests from 16 853 of 18 524 adult rural residents (aged ≥ 18 years) recruited with multistage stratified cluster random sampling at two counties of Xinjiang and a division of Xinjiang Production and Construction Corps during April 2010, December 2012 and November 2016. Subsequent follow-up surveys were carried out among the eligible participants from April 2013 to July 2021 and finally 3 647 participants with a follow-up period of five years and more (averagely 5.28 ± 1.67 years) and without CHD at the baseline survey were included in the analysis, of which, two-thirds (n = 9 155) were randomly assigned into a training set and one-third (n = 4 492) into a verification set. Factor analysis was performed base on the data of 3 206 MS sufferers identified in the participants of training set to explore potential clustering pattern of MS components and probable CHD-related factors. Multivariate Cox proportional risk regression analysis was used to construct prediction model for CHD risk and receiver operating characteristic curve (ROC) analysis was adopted to evaluate the efficiency of the prediction model constructed. ResultsThe cumulative incidence of CHD was 4.94% for all the participants and for those of training and verification set. Training set data-based factor analysis revealed potential CHD-related factors for prediction model construction: obesity, blood pressure, blood lipid/glucose, renal metabolism, blood protein, liver enzyme, myocardial enzyme, and bilirubin and the 8 factors could explain 77.905% of the cumulative variance. Cox proportional hazard regression analysis showed that being female, at older age, obesity, low bilirubin, high blood pressure, and high blood lipid and glucose were risk factors of CHD for the participants of training and verification set. The area under the ROC curve (AUC) was 70.62 (95% confidence interval [95%CI]: 0.742 – 0.782) for the prediction derived from training set data and 0.774 (95%CI: 0.742 – 0.805) for the prediction derived from validation set data. ConclusionA MS factor-based prediction model for predicting CHD risk among rural residents in Xinjiang was constructed and the model could be used in CHD risk assessment and management in local population.

Here, we report the discovery of two viruses associated with a disease characterized by severe diarrhea on a large-scale goat farm in Jilin province. Electron Microscopy observations revealed two kinds of virus particles with the sizes of 150–210 nm and 20–30 nm, respectively. Detection of 276 fecal specimens from the diseased herds showed the extensive infection of peste des petits ruminants virus (63.77%, 176/276) and caprine enterovirus (76.81%, 212/276), with a co-infection rate of 57.97% (160/276). These results were partially validated with RT-PCR, where all five PPRV-positive and CEV-positive specimens yielded the expected size of fragments, respectively, while no fragments were amplified from PPRV-negative and CEV-negative specimens. Moreover, corresponding PPRV and CEV fragments were amplified in PPRV and CEV double-positive specimens. Histopathological examinations revealed severe microscopic lesions such as degeneration, necrosis, and detachment of epithelial cells in the bronchioles and intestine. An immunohistochemistry assay detected PPRV antigens in bronchioles, cartilage tissue, intestine, and lymph nodes. Simultaneously, caprine enterovirus antigens were detected in lung, kidney, and intestinal tissues from the goats infected by the peste des petits ruminants virus. These results demonstrated the co-infection of peste des petits ruminants virus with caprine enterovirus in goats, revealing the tissue tropism for these two viruses, thus laying a basis for the future diagnosis, prevention, and epidemiological survey for these two virus infections.

Abstract Purpose With the increase in aging and cardiovascular risk factors, the morbidity and mortality of atherosclerotic cardiovascular disease (ASCVD), represented by ischemic heart disease and stroke, continue to rise in China. For better prevention and intervention, relevant guidelines recommend using predictive models for early detection of ASCVD high-risk groups. Therefore, this study aims to establish a population ASCVD prediction model in rural areas of Xinjiang using survival analysis. Methods Baseline cohort data were collected from September to December 2016 and followed up till June 2022. A total of 7975 residents (4054 males and 3920 females) aged 30–74 years were included in the analysis. The data set was divided according to different genders, and the training and test sets ratio was 7:3 for different genders. A Cox regression, Lasso-Cox regression, and random survival forest (RSF) model were established in the training set. The model parameters were determined by cross-validation and parameter tuning and then verified in the training set. Traditional ASCVD prediction models (Framingham and China-PAR models) were constructed in the test set. Different models' discrimination and calibration degrees were compared to find the optimal prediction model for this population according to different genders and further analyze the risk factors of ASCVD. Results After 5.79 years of follow-up, 873 ASCVD events with a cumulative incidence of 10.19% were found (7.57% in men and 14.44% in women). By comparing the discrimination and calibration degrees of each model, the RSF showed the best prediction performance in males and females (male: Area Under Curve (AUC) 0.791 (95%CI 0.767,0.813), C statistic 0.780 (95%CI 0.730,0.829), Brier Score (BS):0.060, female: AUC 0.759 (95%CI 0.734,0.783) C statistic was 0.737 (95%CI 0.702,0.771), BS:0.110). Age, systolic blood pressure (SBP), apolipoprotein B (APOB), Visceral Adiposity Index (VAI), hip circumference (HC), and plasma arteriosclerosis index (AIP) are important predictors of ASCVD in the rural population of Xinjiang. Conclusion The performance of the ASCVD prediction model based on the RSF algorithm is better than that based on Cox regression, Lasso-Cox, and the traditional ASCVD prediction model in the rural population of Xinjiang.

Under the dual-carbon background, coal power enterprises are required to actively fulfill their social responsibility in order to achieve energy saving and emission reduction as soon as possible. Considering the uncertainty of the external environment and the potential conflict of interest of the key stakeholders in the fulfillment of corporate social responsibility, coal power enterprises are not always positive in fulfilling their social responsibility. This paper combines prospect theory and mental account theory with evolutionary game to construct an evolutionary game model involving coal power enterprises, government regulators and the public to study the social responsibility behavior of coal power enterprises. The results of the study show that: (1) The social responsibility behavior of coal power enterprises under the dual-carbon background is a typical cost-driven behavior, and coal power enterprises are more sensitive to costs compared to benefits. (2) The formulation of regulatory policies by government regulators largely depends on the decision inertia of coal power enterprises, and the formulation of regulatory policies by government regulators will also affect the decision inertia of coal power enterprises. (3) The public's strategic choices do not entirely depend on the strategic choices of coal and power enterprises and government regulators, and are more closely related to the setting of the reference point. (4) In addition to the realistic factors, the subjective factors of decision makers are also important factors affecting the fulfillment of social responsibility of coal and power enterprises. Based on the results of the study, this paper proposes countermeasures to enhance the internal driving force of coal power enterprises to fulfill their social responsibility behaviors from the aspects of establishing a communication mechanism, improving the reward and punishment system, and strengthening risk management.

BackgroundThis study aimed to assess the association of baseline insulin resistance (IR) surrogates and their longitudinal trajectories with cardiovascular diseases (CVD) to provide a useful reference for preventing CVD.MethodsThis study was a prospective cohort study conducted in the 51st Regiment of the Third Division of Xinjiang Corps. A total of 6362 participants were recruited in 2016 to conduct the baseline survey, and the follow-up surveys in 2019, 2020, 2021, and 2022. The Kaplan–Meier method was used to estimate the cumulative incidence of CVD according to the baseline IR surrogates of metabolic insulin resistance score (METS-IR) and triglyceride-glucose (TyG) index. Cox regression models were used to assess the association between the baseline IR surrogates and CVD. The impact of the longitudinal trajectories of the IR surrogates on CVD was analyzed after excluding those with IR surrogate data measured ≤2 times. Based on the group-based trajectory model (GBTM), the trajectory patterns of IR surrogates were determined. The Kaplan-Meier method was used to estimate the cumulative incidence of CVD in each trajectory group of METS-IR and TyG index. Cox regression models were used to analyze the association between different trajectory groups of each index and CVD. In addition, the Framingham model was utilized to evaluate whether the addition of the baseline IR surrogates increased the predictive potential of the model.ResultsBaseline data analysis included 4712 participants. During a median follow-up of 5.66 years, 572 CVD events were recorded (mean age, 39.42 ± 13.67 years; males, 42.9%). The cumulative CVD incidence increased with the ascending baseline METS-IR and TyG index quartiles (Q1–Q4). The hazard ratio and 95% confidence interval for CVD risk in Q4 of the METS-IR and TyG index were 1.79 (1.25, 2.58) and 1.66 (1.28, 2.17), respectively, when compared with Q1. 4343 participants were included in the trajectory analysis, based on the longitudinal change patterns of the METS-IR and TyG index, the following three trajectory groups were identified: low-increasing, moderate-stable, and elevated-increasing groups. Multivariate Cox regression revealed that the hazard ratio (95% confidence interval) for CVD risk in the elevated-increasing trajectory group of the METS-IR and TyG index was 2.13 (1.48, 3.06) and 2.63 (1.68, 4.13), respectively, when compared with the low-rising group. The C-index, integrated discrimination improvement value, and net reclassification improvement value were enhanced after adding the baseline METS-IR and TyG index values to the Framingham model (P

At present, people use a large amount of coal, oil and other energy while causing a series of environmental pollution problems. In response to the national 3060 policy, improving the utilization of solar energy is imminent. Solar photovoltaic air collector can not only collect heat efficiently but also reduce the surface temperature of solar cells to improve the photoelectric conversion efficiency. The research progress of solar photovoltaic air collector system improvement and application scenarios are reviewed. The theoretical and experimental research of solar photovoltaic air collector in improving photoelectric/photothermal conversion efficiency is analyzed, the current application scenarios and advantages of solar photovoltaic air collector are discussed, and the research direction of solar photovoltaic air collector is prospected.

Poly(ionic liquid)s (PILs) are promising candidates used as solid electrolytes because of their excellent electrochemical properties and improved processability. Introducing light-sensitive groups to PILs appears as an attractive strategy for developing novel smart PIL-based electronic devices. In this work, a new photoresponsive PIL-based solid electrolyte was prepared by blending PILs containing coumarin groups (COU-PILs) with polyvinylidene fluoride hexafluoropropylene. It was found that the ionic conductivity of COU-PIL solid electrolytes (COU-PIL SEs) can be reversibly modulated upon alternative 365 and 254 nm light irradiation. In particular, the COU-PIL SEs exhibit a highly reversible and repeatable manipulation of ionic conductivity with a maximum conductivity modulation of 95%. This reversible control over ionic conductivity is attributed to the photodimerization/photocleavage behavior of the coumarin groups.

Carbon attainment and carbon neutrality are inherent requirements for promoting high-quality development, and the carbon emission efficiency of cities in the Yellow River Basin(YRB) directly affects the high-quality development of the Yellow River Basin. In this paper,we measures the carbon emission efficiency of 61 cities in the YRB from 2004 to 2018 using the super-efficiency Slack-Based Measure model (super-efficient SBM model), and explores the spatial and temporal heterogeneity and spillover effects of the new carbon emission efficiency values by combining empirical orthogonal functions and spatial autoregressive models. The results show that: (1) The spatial pattern of cities in the YRB has changed from “pretty high in the centre and low in the surroundings” to “agglomeration in high-value zones as well as dispersion in low-value zones”. (2) GDP per capita and government involvement are positively related to carbon emission efficiency, while GDP per capita squared, energy intensity and industrial structure are negatively correlated with carbon emission efficiency. (3) Reducing the proportion of fossil energy consumption, strengthening government regulation and optimising​ industrial structure are effective ways to improving the efficiency of carbon emissions in the YRB.

Ensuring safety is crucial for promoting the sustainable growth of the construction industry. Assessing safety efficiency is of significant importance for optimizing safety management processes and improving the safety environment. However, the current mainstream methods for evaluating safety efficiency have limitations such as ignoring non-desired outputs and slack variables, the efficiency values being limited to the (0, 1) range, and a narrow perspective. To address these shortcomings, this study focuses on the characteristics of the construction industry and introduces the Super-SBM model and Malmquist index into the assessment of safety efficiency in the construction industry. The study analyzes the evolution characteristics of safety efficiency from both static and dynamic perspectives. Furthermore, using panel quantile regression models, the study identifies the factors influencing safety efficiency and analyzes their heterogeneity. Analyzing panel data from 30 provinces in China from 2015 to 2021, the results show that the overall safety efficiency of the construction industry in China is relatively low, with noticeable spatial clustering characteristics. Provinces in the eastern and central regions exhibit higher levels of construction safety efficiency. The Malmquist index demonstrates a declining trend, with technical efficiency being the primary factor limiting the improvement of safety efficiency in construction. Factors such as per capita GDP, urbanization rate, committed contract amounts, and the number of professionals engaged in survey and design, as well as engineering supervision, have an impact on construction safety efficiency, and the effects of these variables vary across different quantile levels of safety efficiency. This research can assist decision-makers in gaining a better understanding of the safety conditions in different regions of the construction industry. It can also assist in developing customized policies to enhance the health and safety environment, thereby promoting the stable development of the construction industry.

Abstract The human reliability of intelligent coal mine hoist operation system is affected by many factors, in order to reduce the occurrence of human error in the hoist system and improve the reliability of the system. The characteristics of phased-mission task operation of hoists is combined, the phase dependence of human cognitive errors is considered and, a new human reliability evaluation method is proposed with the help of Bayesian network (BN) model in this paper. Firstly, the phase dependence of human cognitive errors was analyzed based on the cognitive behavior model. Then the human error analysis in the hoist system was carried out, and several main performance shaping factors are selected. Secondly, BN was used to build the human reliability model of the hoist system at each stage. Finally, it is found that the phase dependence of cognitive errors has a negative impact on the human reliability of the hoist system through the case analysis. At the same time, several main performance shaping factors (PSFs)were quantitatively analyzed by using the reverse reasoning ability of BN, which proves the effectiveness of the proposed method, and provides a scientific and reasonable theoretical basis for the development of effective human error prevention measures for the operation of intelligent coal mine hoists.

Dietary assessments hold significant importance within the field of public health. However, the current methods employed for dietary assessments face certain limitations and challenges that necessitate improvement. The aim of our study was to develop a reliable and practical dietary assessment tool known as photo-assisted dietary intake assessment (PAD). In order to evaluate its validity, we conducted an analysis on a sample of 71 college students’ dinners at a buffet in a canteen. We compared estimates of food weights obtained through the 24-h recall (24 HR) or PAD method with those obtained through the weighing method; we also evaluated the feasibility of PAD for recording dinner intakes among a sample of college students (n = 76) and elderly individuals (n = 121). In addition, we successfully identified the dietary factors that have a significant impact on the bias observed in weight estimation. The findings of the study indicated that the PAD method exhibited a higher level of consistency with the weighing method compared to the 24 HR method. The discrepancy in D% values between cereals (14.28% vs. 40.59%, P < 0.05), vegetables (17.67% vs. 44.44%, P < 0.05), and meats (14.29% vs. 33.33%, P < 0.05) was clearly apparent. Moreover, a significant proportion of the food mass value acquired through the PAD method fell within the limits of agreement (LOAs), in closer proximity to the central horizontal line. Furthermore, vegetables, cereals, eggs, and meats, for which the primary importance lies in accuracy, exhibited a considerably higher bias with the 24 HR method compared to the PAD method (P < 0.05), implying that the PAD method has the potential to mitigate the quality bias associated with these food items in the 24 HR method. Additionally, the PAD method was well received and easily implemented by the college students and elderly individuals. In conclusion, the PAD method demonstrates a considerable level of accuracy and feasibility as a dietary assessment method that can be effectively employed across diverse populations.

The polymer/substrate interface plays a significant role in the dynamics of nanoconfined polymers because of its suppression on polymer mobility and its long-range propagation feature, while the molecular origin of the long-range substrate effect in unentangled polymer material is still ambiguous. Herein, we investigated the propagation distances of the substrate effect (h*) by a fluorinated tracer-labeled method of two unentangled polymer films supported on silicon substrates: linear and ring poly(methyl methacrylate) films with relatively low molecular weights. The results indicate that the value of h* has a molecular weight dependence of h*∝N (N is the degree of polymerization) in the unentangled polymer films, while h*∝N1/2 was presented as previously reported in the entangled films. A theoretical model, depending on the polymer/polymer intermolecular interaction, was proposed to describe the above long-range propagation behavior of the substrate effect and agrees with our experiment results very well. From the model, it revealed that the intermolecular friction determines the long-range propagation of the substrate effect in the unentangled system, but the intermolecular entanglement is the dominant role in entangled system. These results give us a deeper understanding of the long-range substrate effect.

Salix psammophila, classified under the Salicaceae family, is a deciduous, densely branched, and erect shrub. As a leading pioneer tree species in windbreak and sand stabilization, it has played a crucial role in combating desertification in northwestern China. However, different genetic sources of Salix psammophila exhibit significant variations in their effectiveness for windbreak and sand stabilization. Therefore, it is essential to establish a rapid and reliable method for identifying different Salix psammophila varieties. Visible and near-infrared (Vis-NIR) spectroscopy is currently a reliable non-destructive solution for origin traceability. This study introduced a novel feature selection strategy, called qualitative percentile weighted sampling (QPWS), based on the principle of the long tail effect for Vis-NIR spectroscopy. The core idea of QPWS combines weighted sampling and percentage wavelength selection to identify key wavelengths. By employing a multi-threaded parallel execution of multiple QPWS instances, we aimed to search for the optimal feature bands to address the instability issues that can arise during the feature selection process. To address the problem of reduced prediction performance in one-dimensional convolutional neural network (1D-CNN) models after feature selection, we have introduced convolutional autoencoders (CAEs) to reduce the dimensions of wavelengths that are discarded during feature selection. Subsequently, these reduced dimensions are fused with the selected wavelengths, thereby enhancing the model’s performance. With our completed model, we selected outstanding models for model fusion and established a decision system for Salix psammophila. It is worth noting that all 1D-CNN models in this study were developed using Bayesian optimization methods. In comparison with principal component analysis (PCA) and full spectrum methods, QPWS exhibits superior predictive performance in the field of machine learning. In the realm of deep learning, the fusion of data combining QPWS with CAE demonstrated even greater potential with an improvement of average accuracy of approximately 2.13% when compared to QPWS alone and a 228% increase in operational speed compared to a model with full spectra. These results indicated that the combination of CAE with QPWS can be an effective tool for identifying the origin of Salix psammophila.

Abstract Background Hereditary spastic paraplegia 49 (HSP49) is an autosomal recessive genetic disease first discovered in 2012; and which the mutation primarily affects Bukharian Jewish patients. Case presentation The present case reports the first instance of HSP49 detected in China. The patient had normal mental development and good athletic ability before 10 years old and presented with instable temperature, mental retardation, spastic ataxia, and paroxysmal convulsions. Genetic diagnosis was based on detection of whole exons and two heterozygous variants in the exon region of the TECPR2 gene: c.1729C > T and c.4189G > A. Mutations at these two sites have not been previously reported. Conclusions This case expands the gene mutation spectrum and clinical phenotypic characteristics of autosomal recessive HSP in China; moreover, it indicates differences in the clinical phenotype of HSP49 in different ethnicities. In addition, this reported provides further evidence regarding the effectiveness of targeted next-generation sequencing technology in improving the efficiency and diagnostic rate of genetic diagnosis of HSP.

BackgroundHysterectomy is a widely used surgical approach for benign gynecological conditions, although recently there have been differences in the surgical route selected in different regions.AimsTo estimate recent temporal trends, this study collected data on surgical approaches and adnexal surgeries during hysterectomies for benign diseases at a single institute from 2015 to 2021.Materials and methodsWe retrospectively analyzed data from Xiangyang No.1 People's Hospital, Hubei University of Medicine in Xiangyang, China, and identified 1828 women who underwent hysterectomies for benign gynecologic conditions performed with or without bilateral salpingectomy (BS) or bilateral salpingo-oophorectomy (BSO) between January 2015 and December 2021.ResultsThere was an upward trend in the performance of hysterectomy and hysterectomy with BS, and there was a difference in the trends of concomitant adnexal surgery between AH, TLH, and VH, especially in TLH with BS. Patient characteristics data demonstrated that the most frequent indication for hysterectomy was leiomyoma, especially in women aged 45 to 65. Compared to AH, TLH, and VH, the operative bleeding, duration of surgery, and length of hospital stays of patients undergoing TLH with BS and BSO was the lowest. The surgical approach to benign diseases has changed dramatically due to a growing proportion of patients choosing minimally invasive procedures. The laparoscopic approach is becoming popular due to its capacity to decrease intraoperative blood loss and reduce hospitalization.ConclusionsWe should put more emphasis on surgical training for the TLH approach and help gynecologic surgeons provide the proposed added benefit of BS to their patients.

Abstract As fish is a perishable food item, multiple storage approaches need be considered to extend its shelf‐life, safety, and quality. Despite advancements in modern frozen storage techniques, chilling and freezing remain the most frequently employed preservation practices onboard. The purpose of this review is to outline ways of increasing the shelf‐life of fresh and frozen fish by assessing different conventional chilling and freezing conditions. Although there are additional elements that determine fish shelf‐life, such as the fish species, harvesting method, stress experienced after being captured, amount of ice, frozen storage temperature, and time are some of the most important factors. Furthermore, the way that fish is stored (whole, filleted, or gutted) influences the final product quality. Most studies show that the entire chilled or frozen fish has a longer shelf life as compared to the gutted and filleted fish. But other facts about the species, the way it is caught, and how it gets to preparedness at industries must be taken into account if the shelf life is to be extended. Meanwhile, this review could be helpful for the prolonged shelf‐life and quality at the industrial scale and household storage.

Background and aimsExponential population aging has led to an increased prevalence of cognitive impairment worldwide. Hand grip strength, which may be associated with physical activity, could be a useful predictor of cognitive impairment. However, few studies have reported the association, if any, between hand grip strength and cognitive function.MethodsWe used data obtained from the National Health and Nutrition Examination Survey between 2011–2012 and 2013–2014 to investigate the association between hand grip strength and cognitive impairment. Cognitive impairment was assessed using the Consortium to Establish a Registry for Alzheimer's Disease (CERAD), animal fluency (AF), and digit symbol substitution test (DSST) scores. Cutoff values of CERAD < 5, AF < 14, and DSST < 34 were used to define cognitive impairment. In this cross-sectional study, we used odds ratios to determine the potential usefulness of hand grip strength for the prediction of cognitive impairment.ResultsThis study included 2,623 participants aged ≥60 years. The DSST results showed that hand grip strength was associated with a low risk of cognitive impairment and that subgroup analysis showed that male sex, 60–69 years of age, and the Non-Hispanic (NH)-White, NH Black, and Asian were associated with a significantly low risk of cognitive impairment. The CERAD test results showed that 70–79 years of age and the NH White were significantly associated with a low risk of cognitive impairment. By following full adjustment, we did not observe statistically significant differences between hand grip strength and cognitive impairment based on the CERAD test. The AF test results showed that >80 years of age, female sex, and the NH White were associated with a significantly low risk of cognitive impairment. The most important finding is that a linear association lies between grip strength and cognitive impairment, as well as a sex-based linear association. Machine learning of the XGBoost model suggests that grip strength is one of the top two most important negative predictor variables.ConclusionWe observed an inverse relationship between hand grip strength and cognitive impairment, which might suggest a shared underlying mechanism that needs to be further investigated using a large-scale prospective clinical trial to validate our findings.

Caprine/ovine enterovirus (CEV/OEV) infection is an emerging disease and remains largely unknown for its infection distribution, epidemic pattern, and the underlying contribution factors. Here, we report the investigation on CEV/OEV infection pattern and the underlying contribution factors by employing a sandwich ELISA kit for detection of CEV/OEV antigen. Epidemiological investigation revealed a wide range of infection rates of CEV/OEV from 19.80%−39.00% on goat/sheep farms in the major goat/sheep-raising provinces as such Henan, Shandong, Ningxia, Jilin, Inner Mongolia autonomous region, and Xinjiang autonomous region in China. Epidemic patterns and infection rates for CEV/OEV were affected by the breeds, raising mode, regions, and seasons. CEV/OEV infection rates were varied in different regions in China and significantly higher in the diarrheal herds (40.30%) than these in non-diarrheal herds (13.83%). Moreover, infection rate was higher in sheep (24.59%) than that in goats (9.84%), even dramatic difference among different breeds of goat or sheep. Out of different breeds of goat, Boer (20.13%) had the highest infection rate, followed by local breed (5.62%) and Saanen (2.61%). Among these breeds of sheep, higher infection rates were detected in local breed sheep (42.86%) and small-tailed Han sheep (35.91%) than these of Hu sheep (13.41%) and Dorper sheep (16.34%). Furthermore, raising modes were showed to contribute to the infection rate, where higher rates were detected among goats/sheep in captivity (27.10%) than these in free-range (12.27%) and semi-free range (19.24%). Additionally, CEV/OEV infection rate had obvious seasonality, while they increased from year 2015 to 2019. In summary, we investigated the CEV/OEV infection among the goat/sheep herds from different regions in China, revealed the epidemic pattern and the contribution factors to the infection, which provided the epidemiological data for future prevention and control of this emerging infection.

Abstract Rational design of nanostructures with excellent activity and stability for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) to realize efficient hydrogen production is essential for renewable energy development and conversion. Here, we have designed a special pyrolysis reduction method for the synthesis of CoPt3 nanoparticles (NPs) embedded in N‐doped carbon nanospheres (CoPt3@NC). In this process, a facile impregnation combined with pyrolysis reduction strategy is carried out to produce well‐dispersed CoPt3 nanoparticles within the N‐doped carbon, and the resulting CoPt3@NC nanospheres with trace Pt content exhibit superior HER and OER activity to pure Pt@NC, which needs an ultralow overpotential of 65 mV and 360 mV to drive 10 mA/cm2 in 1.0 M KOH, respectively, and also with excellent long‐term durability. The excellent HER and OER activities of CoPt3@NC nanospheres are mainly ascribed to the high surface area, N‐doping, and synergistic effect between catalyst and carrier. This work provides a feasible strategy to design carbon‐based heterostructures with high catalytic activity and stable properties.

The migration and transformation of the petroleum hydrocarbons from sediments into water columns is an important basis for assessing the impact on marine environment. In this paper, a static release experiment of crude oils from the Bohai Sea was carried out to evaluate the temporal and spatial variation of petroleum hydrocarbons and microbial communities. The results showed C1 phenanthrene (C1-P) can be used as an evaluation index of different crude oils during static release of oil pollution sediments and their trends of the static release were similar. The crude oil with higher C1-P content released C1-P into the water body significantly higher. After 72 hours, the C1-P release degree of crude oil with a smaller viscosity was more obvious. In the crude oil with the smallest viscosity and the higher viscosity, the bacterial phyla abundance increase was greater. And more importantly, the top 10 abundance of the microbial communities in the water columns and sediments appeared partial (3 species) replacement phenomenon. The research results can deep understanding the migration and transformation of the petroleum hydrocarbons from oil pollution sediments and understanding of the interaction between extreme weather events and human activities by incorporating an eco-evolutionary perspective.

BackgroundCardiovascular diseases (CVD) are currently the leading cause of premature death worldwide. Model-based early detection of high-risk populations for CVD is the key to CVD prevention. Thus, this research aimed to use machine learning (ML) algorithms to establish a CVD prediction model based on routine physical examination indicators suitable for the Xinjiang rural population.MethodThe research cohort data collection was divided into two stages. The first stage involved a baseline survey from 2010 to 2012, with follow-up ending in December 2017. The second-phase baseline survey was conducted from September to December 2016, and follow-up ended in August 2021. A total of 12,692 participants (10,407 Uyghur and 2,285 Kazak) were included in the study. Screening predictors and establishing variable subsets were based on least absolute shrinkage and selection operator (Lasso) regression, logistic regression forward partial likelihood estimation (FLR), random forest (RF) feature importance, and RF variable importance. The selected subset of variables was compared with L1 regularized logistic regression (L1-LR), RF, support vector machine (SVM), and AdaBoost algorithm to establish a CVD prediction model suitable for this population. The incidence of CVD in this population was then analyzed.ResultAfter 4.94 years of follow-up, a total of 1,176 people were diagnosed with CVD (cumulative incidence: 9.27%). In the comparison of discrimination and calibration, the prediction performance of the subset of variables selected based on FLR was better than that of other models. Combining the results of discrimination, calibration, and clinical validity, the prediction model based on L1-LR had the best prediction performance. Age, systolic blood pressure, low-density lipoprotein-L/high-density lipoproteins-C, triglyceride blood glucose index, body mass index, and body adiposity index were all important predictors of the onset of CVD in the Xinjiang rural population.ConclusionIn the Xinjiang rural population, the prediction model based on L1-LR had the best prediction performance.

Gravel mulching is a characteristic agricultural technique that has been used for hundreds of years in the north-western Loess Plateau of China. However, the effects of the gravel-sand mulch on the processes of the runoff, soil erosion, and nutrient losses are neither fully distinguished nor even known in many parts of the world. This study investigated how different gravel particle sizes in the mulch affected the runoff, erosion as well as the extent of the nutrient losses in the surface runoff. The laboratory experiments were conducted using a rainfall simulator with three gravel mulch treatments: (1) fine gravel mulch (FG); (2) medium gravel mulch (MG); (3) coarse gravel mulch (CG) and a control group, bare soil (BS). The results of these rainfall simulation experiments gave estimates on how the grain size influences the runoff and losses of the soil and its nutrients. Applying the gravel mulch significantly delayed the runoff's starting time when compared with the bare soil. Both the total runoff and soil loss increased with the grain size of the gravel mulch. Compared with the bare soil, the lowest surface runoff and soil loss was observed from the fine gravel treatment. These results clearly show that gravel mulch plays an important role in the runoff and sediment generation processes, and that it significantly reduces the surface runoff and soil loss. The losses of the total nitrogen (TN), total phosphorus (TP), and total organic carbon (TOC) from the bare soil were much higher than those under the gravel mulching. The fluctuations in these nutrient-loss processes were the most intense in the CG treatment, while the TC content, in initial runoff, was significantly higher in the FG than the other treatments. Our findings suggest gravel mulch is a useful water and soil conservation technique in the loess area of north-western China, and these results can inform one on the theoretical principles for properly utilising gravel-mulched fields.

Lined seahorse, Hippocampus erectus, is an important aquatic animal due to its medicinal and ornamental purposes. However, our understanding of the viral spectrum in H. erectus is still limited. Here, we studied the viruses in H. erectus using meta-transcriptomic sequencing. A total of 213,770,166 reads were generated and assembled de novo into 539 virus-associated contigs. Three novel RNA viruses from the Astroviridae, Paramyxoviridae, and Picornaviridae families were finally identified. In addition, we identified a strain of nervous necrosis virus from H. erectus. In particular, the unhealthy group showed a higher viral diversity and abundance than the normal group. These results revealed the diversity and cross-species transmission of viruses in H. erectus and highlighted the threat of viral infections to H. erectus.

There are several commercial chromatographic systems for protein purification; however, development of cost-effective 3H-grade (high yield, high purity, and high activity) purification approaches is highly demanded. Here, we establish a methodology for encapsulating the IM7-displaying yeast cells in calcium alginate beads. Taking advantage of this biomaterial-based affinity chromatography, rapid and cost-effective purification of proteins with over 90% purity in a single step is achieved. Moreover, our system enables coating the multienzyme complex to produce reusable immobilized cells for efficient cascade biotransformation. Together, the present method has great application potentials not only in the laboratory but also in the industry for production of protein products as well as biocatalysis.

Abstract Background To externally validate the Prediction for ASCVD Risk in China (PAR) risk equation for predicting the 5-year atherosclerotic cardiovascular disease (ASCVD) risk in the Uyghur and Kazakh populations from rural areas in northwestern China and compare its performance with those of the pooled cohort equations (PCE) and Framingham risk score (FRS). Methods The final analysis included 3347 subjects aged 40–74 years without CVD at baseline. The 5-year ASCVD risk was calculated using the PAR, PCE, and FRS. Discrimination, calibration, and clinical usefulness of the three equations in predicting the 5-year ASCVD risk were assessed before and after recalibration. Results Of 3347 included subjects, 1839 were female. We observed 286 ASCVD events in within 5-year follow-up. All three risk equations had moderate discrimination in both men and women. C-indices of PAR, PCE, and FRS were 0.727 (95% CI, 0.725–0.729), 0.727 (95% CI, 0.725–0.729), and 0.740 (95% CI, 0.738–0.742), respectively, in men; the corresponding C-indices were 0.738 (95% CI, 0.737–0.739), 0.731 (95% CI, 0.730–0.732), and 0.761 (95% CI, 0.760–0.762), respectively, in women. PCE, PAR and FRS substantially underestimated the 5-year ASCVD risk in women by 70, 23 and 51%, respectively. However, PAR and FRS fairly predicted the risk in men and PAR was well calibrated. The calibrations of the three risk equations could be changed by recalibration. The decision curve analyses demonstrated that at the threshold risk of 5%, PCE was the most clinically useful in both men and women after recalibration. Conclusions All three risk equations underestimated the 5-year ASCVD risk in women, while PAR and FRS fairly predicted that in men. However, the results of predictive performances for three risk equations are inconsistent, more accurate risk equations are required in the primary prevention of ASCVD aiming to this Uyghur and Kazakh populations.

Stable diradicals are generally based on two s/p-localized or π-delocalized unpaired electrons (radicals). Here, the authors report a dication diradical that is based on two Se∴Se three-electron σ-bonds.

Abstract Background Low high-density lipoprotein cholesterol (HDL-C) disease with unknown etiology has a high prevalence in the Xinjiang Kazak population. In this study, long noncoding RNAs (lncRNAs) that might play a role in low HDL-C disease were identified. Methods Plasma samples from 10 eligible individuals with low HDL disease and 10 individuals with normal HDL-C levels were collected. The lncRNA profiles for 20 Xinjiang Kazak individuals were measured using microarray analysis. Results Differentially expressed lncRNAs and mRNAs with fold-change values not less than 1.5 and FDR-adjusted P-values less than 0.05 were screened. Bioinformatic analyses, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and network analyses, were used to determine relevant signaling pathways and predict potential target genes. In total, 381 lncRNAs and 370 mRNAs were differentially expressed based on microarray analysis. Compared with those in healthy individuals, several lncRNAs were upregulated or downregulated in patients with low HDL-C disease, among which TCONS_00006679 was most significantly upregulated and TCONS_00011823 was most significantly downregulated. GO and KEGG pathway analyses as well as co-expression networks of lncRNAs and mRNAs revealed that the platelet activation pathway and cardiovascular disease were associated with low HDL-C disease. Conclusions Potential target genes integrin beta-3 (ITGB3) and thromboxane A2 receptor (TBXA2R) were regulated by the lncRNAs AP001033.3–201 and AC068234.2–202, respectively. Both genes were associated with cardiovascular disease and were involved in the platelet activation pathway. AP001033.3–201 and AC068234.2–202 were associated with low HDL-C disease and could play a role in platelet activation in cardiovascular disease. These results reveal the potential etiology of dyslipidemia in the Xinjiang Kazakh population and lay the foundation for further validation using large sample sizes.

Abstract Backgrounds Engineering yeast as a consolidated bioprocessing (CBP) microorganism by surface assembly of cellulosomes has been aggressively utilized for cellulosic ethanol production. However, most of the previous studies focused on Saccharomyces cerevisiae, achieving efficient conversion of phosphoric acid-swollen cellulose (PASC) or microcrystalline cellulose (Avicel) but not carboxymethyl cellulose (CMC) to ethanol, with an average titer below 2 g/L. Results Harnessing an ultra-high-affinity IM7/CL7 protein pair, here we describe a method to engineer Pichia pastoris with minicellulosomes by in vitro assembly of three recombinant cellulases including an endoglucanase (EG), an exoglucanase (CBH) and a β-glucosidase (BGL), as well as a carbohydrate-binding module (CBM) on the cell surface. For the first time, the engineered yeasts enable efficient and direct conversion of CMC to bioethanol, observing an impressive ethanol titer of 5.1 g/L. Conclusions The research promotes the application of P. pastoris as a CBP cell factory in cellulosic ethanol production and provides a promising platform for screening the cellulases from different species to construct surface-assembly celluosome.

Abstract Background Metabolic syndrome is diagnosed by a cluster of risk factors that associated with an increased risk of coronary heart disease (CHD). We aimed to explore the impact of and interactions between individual metabolic syndrome components on the risk of CHD in Xinjiang. Methods The baseline population included 7635 participants. The degree to which the components increase the risk of CHD and the multiplicative interactions between them were assessed using hazard ratios (HRs) and 95% confidence intervals (CIs). Additive interactions were appraised by the relative excess risk due to interaction, synergy index (SI), and attributable proportion of interaction. Results A total of 304 CHD patients were enrolled from rural residents of Xinjiang. Elevated blood pressure (HR 1.81; 95% CI 1.35–2.44) and elevated fasting blood glucose (FBG) (HR 1.82; 95% CI 1.38–2.38) increased the risk of CHD after adjustment for confounding factors. We found a positive additive interaction (SI 1.14; 95% CI 0.51–2.51) between elevated blood pressure and elevated FBG, but none were significant. As the number of components increased, the risk of CHD increased. The combinations of [high triglycerides (TG) + low high-density lipoprotein cholesterol (HDL-C) + elevated FBG + large waistline] (HR 4.26; 95% CI 1.43–12.73) and [elevated blood pressure + elevated FBG + low HDL-C + large waistline] (HR 1.82; 95% CI 1.38–2.38) increased the risk of CHD. Conclusions We provide evidence that elevated blood pressure and elevated FBG are independent risk factors for CHD and it might be necessary to maintain the normal waistline for preventing CHD.

Abstract Background The process of bone repair is heavily dependent on the ability of human bone marrow mesenchymal stem cells (hMSCs) to undergo osteogenic differentiation. MicroRNAs have been shown to regulate this osteogenic process. This study aimed to investigate the role of miR-765 in the osteogenic differentiation of hMSCs. Methods We transfected hMSCs with lentiviral constructs to knock down or overexpress this miRNA, allowing us to assess its role in osteogenesis via assessing the expression of the relevant markers alkaline phosphatase (ALP), runt-related gene-2 (RUNX-2), and osteocalcin (OCN), with further functional measurements made via quantifying ALP activity and conducting Alizarin Red S staining. The targeting of the 3′-untranslated region (UTR) of BMP6 by miR-765 was examined via luciferase assay. We used hMSCs with altered miR-765 expression to assess p-Smad1/5/9 levels via Western blotting over the course of osteogenic differentiation. We also assessed the osteogenic differentiation of hMSCs in which miR-765 was knocked down and at the same time as a BMP/Smad signaling inhibitor was added to disrupt Smad1/5/9 phosphorylation. Results We found miR-765 overexpression to inhibit osteogenesis-associated gene upregulation during osteogenic differentiation of hMSCs, whereas knockdown of this miRNA was associated with increased expression of these genes. Using luciferase reporter assays, we confirmed direct miR-765 binding to the 3′-untranslated region (UTR) of BMP6. We also found that miR-765 overexpression reduced Smad1/5/9 phosphorylation, and knockdown of this miRNA enhanced this phosphorylation on BMP6/Smad1/5/9 signaling. The osteogenic differentiation of hMSCs in which miR-765 had been knocked down was further weakened upon the addition of a BMP/Smad signaling inhibitor relative to miR-765 knockdown alone. Conclusions Together, these results thus suggest that miR-765 is able to inhibit hMSC osteogenic differentiation by targeting BMP6 via regulation of the BMP6/Smad1/5/9 signaling pathway. Our findings may offer molecular insights of value for the development of novel therapeutic treatments for bone diseases including osteoporosis.

Weather risk causes uncertain crop yield and price and further influences the willingness of farmers to participate in contract farming and honour the contract. In this study, we investigate the optimal decisions for contract farming between a profit-maximizing manufacturer and multiple identical farmers under weather risk, using a game-theoretical approach. We discuss two different cases. In the first case, the manufacturer sets a contract price to ensure farmers to honour the contract under any weather condition. While in the second case, the manufacturer sets a lower contract price only to guarantee that farmers will not renege under certain weather condition but has a second chance to purchase products from the reneged farmers at a renegotiated price. We derive the optimal decisions of the manufacturer in both cases and show that the manufacturer gains much more profits in the second case, and therefore, the decisions in the second case are optimal. Moreover, we numerically investigate the sensitivity of the effectiveness of contract farming and the manufacturer’s optimal decisions to model parameters and get more managerial implications.

Matching the detection speed and accuracy in practical applications is considered to improve the speed of video object detection in front of trains. Lightweight convolutional neural network MobileNet and clustering ideas are combined to improve the object detection algorithm, and the MYOLO-lite model object detection algorithm is designed. The self-made object dataset of a forward-moving train is combined with the K-means clustering idea. The transcendental frame is redesigned to enhance scale adaptability. The nonmaximum suppression and loss function improvement methods of the MYOLO-lite network model are proposed for occluded tracks in front of the train, obstruction of trains, low detection accuracy of large object coincidence, and uneven distribution of positive and negative samples. The mean average precision value of the experimentally designed MYOLO-lite model object detection algorithm reaches 95.74%, with 42.04 frames per second. Detecting a picture only takes 0.024 s.