Autophagy protects against palmitate-induced apoptosis in hepatocytes

BACKGROUND: Non-alcoholic fatty liver disease, one of the most common liver diseases, has obtained increasing attention. Palmitate (PA)-induced liver injury is considered a risk factor for the development of non-alcoholic fatty liver disease. Autophagy, a cellular degradative pathway, is an important self-defense mechanism in response to various stresses. In this study, we investigated whether autophagy plays a protective role in the progression of PA-induced hepatocytes injury. RESULTS: Annexin V-FITC/PI staining by FCM analysis, TUNEL assay and the detection of PARP and cleaved caspase3 expression levels demonstrated that PA treatment prominently induced the apoptosis of hepatocytes. Meanwhile, treatment of PA strongly induced the formation of GFP-LC3 dots, the conversion from LC3I to LC3II, the decrease of p62 protein levels and the increase of autophagosomes. These results indicated that PA also induced autophagy activation. Autophagy inhibition through chloroquine pretreatment or Atg5shRNA infection led to the increase of cell apoptosis after PA treatment. Moreover, induction of autophagy by pretreatment with rapamycin resulted in distinct decrease of PA-induced apoptosis. Therefore, autophagy can prevent hepatocytes from PA-induced apoptosis. In the further study, we explored pathway of autophagy activation in PA-treated hepatocytes. We found that PA activated PKCα in hepatocytes, and had no influence on mammalian target of rapamycin and endoplasmic reticulum stress pathways. CONCLUSIONS: These results demonstrated that autophagy plays a protective role in PA-induced hepatocytes apoptosis. And PA might induce autophagy through activating PKCα pathway in hepatocytes

The relationship of intimate partner violence on depression: the mediating role of perceived social support and the moderating role of the Big Five personality

IntroductionThis study aimed to explore the influence of Intimate Partner Violence (IPV) on depression, the mediating role of social support, and the moderating role of the Big Five personality traits in the relationship between social support and depression.MethodsParticipants were recruited from Mainland China, using a stratified random sampling and quota sampling method. From June to August 2022, a diverse group of 21,916 participants (ranging from 12 to 100 years old) completed the Intimate Partner Violence Scale, Patient Health Questionnaire, Perceived Social Support Scale, and Big Five Inventory-Short Version.ResultsIPV was significantly positively correlated with depression and significantly negatively correlated with perceived social support. Perceived social support plays a mediating role in the link between IPV and depression.DiscussionHealthcare workers should assess social support and provide adequate care or recommendations for increasing social support when patients with IPV report depressive symptoms. Patients can be coached by professionals to improve their resiliency by developing or nurturing more optimistic personality traits

Identification of Sensitive Parameters for Deformation of Asphalt Concrete Face Rockfill Dam of Pumped Storage Power Station

Pumped storage power station (PSPS) is an important clean energy project that plays an important role in ensuring the economical, safe, and stable operation of power systems and alleviating the contradiction of peak load regulation. Deformation analysis of the built and under construction PSPS dam was an important process of dam design and operation, which was of great significance to ensure the safe operation of hydraulic structures in the reservoir site. Nevertheless, there were many parameters involved in the model for analyzing dam deformation, which brings a large workload to the inversion and application of model parameters. In this study, the asphalt concrete face rockfill dam (ACFRD) of a PSPS in Ningxia, China, was taken as an example, a dam deformation 3D finite element analysis model based on the Duncan–Chang E-B model was constructed, and the orthogonal test method was used. The model parameters of the main rockfill zone, secondary rockfill zone, and reservoir bottom backfill zone were taken as factors for the sensitivity analysis of horizontal displacement of dam H, vertical displacement u, and asphalt concrete face tensile strain ε. The results showed that initial bulk modulus base Kb, damage ratio Rf, and initial elastic modulus base K had a relatively higher sensitivity and had significant impacts on the calculation results, while internal friction angle φ, fraction angle reduction φ, bulk modulus index m, and elastic modulus index n had a relatively lower sensitivity, which had no significant impact on the calculation results. Therefore, when using the Duncan–Chang E-B model to analyze the deformations of a PSPS dam and asphalt concrete face, Kb, Rf, and K should be the focus. Parameters with a low sensitivity could be determined by engineering analogy so as to achieve the purpose of improving calculation efficiency under the premise of ensuring calculation accuracy. Meanwhile, these parameters should also be strictly controlled during construction. The results of this study could provide a reference for the design and safety assessment of ACFRD in PSPS

Identification of Sensitive Parameters for Deformation of Asphalt Concrete Face Rockfill Dam of Pumped Storage Power Station

Pumped storage power station (PSPS) is an important clean energy project that plays an important role in ensuring the economical, safe, and stable operation of power systems and alleviating the contradiction of peak load regulation. Deformation analysis of the built and under construction PSPS dam was an important process of dam design and operation, which was of great significance to ensure the safe operation of hydraulic structures in the reservoir site. Nevertheless, there were many parameters involved in the model for analyzing dam deformation, which brings a large workload to the inversion and application of model parameters. In this study, the asphalt concrete face rockfill dam (ACFRD) of a PSPS in Ningxia, China, was taken as an example, a dam deformation 3D finite element analysis model based on the Duncan–Chang E-B model was constructed, and the orthogonal test method was used. The model parameters of the main rockfill zone, secondary rockfill zone, and reservoir bottom backfill zone were taken as factors for the sensitivity analysis of horizontal displacement of dam H, vertical displacement u, and asphalt concrete face tensile strain ε. The results showed that initial bulk modulus base Kb, damage ratio Rf, and initial elastic modulus base K had a relatively higher sensitivity and had significant impacts on the calculation results, while internal friction angle φ, fraction angle reduction φ, bulk modulus index m, and elastic modulus index n had a relatively lower sensitivity, which had no significant impact on the calculation results. Therefore, when using the Duncan–Chang E-B model to analyze the deformations of a PSPS dam and asphalt concrete face, Kb, Rf, and K should be the focus. Parameters with a low sensitivity could be determined by engineering analogy so as to achieve the purpose of improving calculation efficiency under the premise of ensuring calculation accuracy. Meanwhile, these parameters should also be strictly controlled during construction. The results of this study could provide a reference for the design and safety assessment of ACFRD in PSPS

Hierarchically structured semiconductor@noble-metal@MOF for high-performance selective photocatalytic CO2 reduction

Photocatalytic CO2 reduction to convert solar energy to clean energy remains a critical challenge in exploring efficient catalysts. Herein, a hierarchical structured BiVO4@Au@UiO-66-NH2 with high photocatalytic activity was fabricated. The theoretical calculations revealed that the metal–organic framework (MOF) with relative higher conduction band (CB) and UiO-66-NH2 with relative lower valence band (VB) could absorb full light spectrum, combining Au nanoparticle with suitable Fermi level into a particulate tandem heterojunction. This configuration can not only lower the activation barrier of CO2 reduction using the rich active site of MOF, but also improve the selectivity toward CO by optimizing the reaction pathway. Notably, the experimental evaluation proved that BiVO4@Au@UiO-66-NH2 displays a producing rate of 232.7 μmol h−1 g−1 for CO and a selectivity of 97.2%. The investigation reveals that elaborately integrating multiple functional components into such a hierarchical structure enables optimizing crucial processes in photocatalytic CO2 conversion and enhancing selectivity via synergistic catalysis

Risk profiles for smoke behavior in COVID-19: a classification and regression tree analysis approach

Abstract Background COVID-19 pandemic emerged worldwide at the end of 2019, causing a severe global public health threat, and smoking is closely related to COVID-19. Previous studies have reported changes in smoking behavior and influencing factors during the COVID-19 period, but none of them explored the main influencing factor and high-risk populations for smoking behavior during this period. Methods We conducted a nationwide survey and obtained 21,916 valid data. Logistic regression was used to examine the relationships between each potential influencing factor (sociodemographic characteristics, perceived social support, depression, anxiety, and self-efficacy) and smoking outcomes. Then, variables related to smoking behavior were included based on the results of the multiple logistic regression, and the classification and regression tree (CART) method was used to determine the high-risk population for increased smoking behavior during COVID-19 and the most profound influencing factors on smoking increase. Finally, we used accuracy to evaluated the performance of the tree. Results The strongest predictor of smoking behavior during the COVID-19 period is acceptance degree of passive smoking. The subgroup with a high acceptation degree of passive smoking, have no smokers smoked around, and a length of smoking of ≥ 30 years is identified as the highest smoking risk (34%). The accuracy of classification and regression tree is 87%. Conclusion The main influencing factor is acceptance degree of passive smoking. More knowledge about the harm of secondhand smoke should be promoted. For high-risk population who smoke, the “mask protection” effect during the COVID-19 pandemic should be fully utilized to encourage smoking cessation

Design of Fast Acquisition System and Analysis of Geometric Feature for Highway Tunnel Lining Cracks Based on Machine Vision

Under the dual effects of the rapid growth of tunnel mileage and operating years, the application and research of tunnel crack identification based on machine vision are increasing with the vigorous development of machine vision. However, due to the complex environment in tunnels, it is difficult to quickly obtain tunnel lining cracks via computer visions in the tunnel. Therefore, this paper presents the design of a fast acquisition system with the geometric feature analysis for tunnel lining cracks, which has been integrated into a tunnel fast inspection vehicle with a machine vision module. Through the research on the image acquisition system of the tunnel lining, the parameter selection of the crack shooting hardware system is determined, and the fast calculation method of shooting parameters is proposed. The geometric characteristic analysis of the tunnel lining crack image is employed to calculate crack width and determine the optimal gray value of crack extraction. Field tests have been conducted in the highway tunnels in Zhejiang and Yunnan provinces in China and the result indicates that the proposed approach yields much better performance in the detection efficiency, whose time of detection is only 1%, and the number of personnel required is only 40% of the traditional pure manual method. Compared with similar systems, it also has significant advantages in crack resolution and detection speed. This research provides a means of rapid acquisition of tunnel cracks and laying a foundation for the evaluation of the service performance of the tunnel

Optimal Model of Investment Decision for Distribution Network Construction Project

In order to meet the requirements of precise investment in the distribution network under the new power reform, this paper proposes an optimization model for the investment decision of the distribution network. With the largest net present value rate and the smallest comprehensive cost of grid operation as the optimization goal, and certain capital constraints as constraints, a distribution network 0-1 programming model is established and solved by LINGO software; the analysis of an example shows that this model can ensure the safety of investment in the distribution network and the precise investment allocation in the distribution network under certain financial constraints