Objective: To investigate the prevalence and associated factors of depressive symptoms among junior and senior high school students in Beijing from 2019 to 2023, in order to provide a scientific basis for interventions targeting high risk groups. Methods: From 2019 to 2023, a stratified cluster random sampling method was used to select 88 927 junior and senior high school students from 16 districts in Beijing. The Center for Epidemiologic Studies Depression Scale(CES-D) was conducted to assess depressive symptoms. The Chi square test was used to compare the detection rates of depressive symptoms among different student groups, and the trend Chi square test was employed for trend analysis of detection rates across the years. Multivariate Logistic regression analysis was applied to examine the association between the detection of depressive symptoms and related factors among junior and senior high school students. Results: From 2019 to 2023, the prevalence rates of depressive symptoms among junior and senior high school students in Beijing were 20.45%, 18.19%, 16.64%, 17.89% and 18.17%, respectively, with an overall downward trend ( χ 2 trend =27.51, P <0.01). Multivariate Logistic regression analysis revealed that after adjusting for gender, monitoring year, educational stage,family structure,boarding status and has taken a medical leave of absence in the past year unhealthy dietary behaviors ( OR=1.80, 95%CI =1.73-1.87), physical inactivity ( OR=1.24, 95%CI =1.19-1.29), try smoking ( OR=1.46, 95%CI =1.35-1.58), try alcohol( OR=1.96, 95%CI =1.88-2.05), Internet addiction ( OR=3.88, 95%CI =3.57-4.22), and adverse ear related behavior ( OR=1.82, 95%CI =1.71-1.93) were all associated with an increased risk of depressive symptoms among junior and senior high school students (all P <0.05). Conclusions The prevalence depression symptoms among middle school students in Beijing showed a fluctuating downward trend from 2019 to 2023. Targeted interventions should be adopted to reduce the occurrence of depression symptoms among junior and senior high school students.

In order to solve the problems of difficult test, high cost and long cycle in the development of large-scale airborne negative pressure isolation system, the simulation analysis of negative pressure response characteristics is carried out around various aviation conditions such as aircraft ascending, leveling and descending, especially rapid decompression, based on the computational fluid dynamics (CFD) method. The results showed that the isolation cabin could achieve -50 Pa pressure difference environment and form a certain pressure gradient. The exhaust air volume reached the maximum value in the early stage of the aircraft's ascent, and gradually decreased with the increase of altitude until it was level flying. In the process of aircraft descent, the exhaust fan could theoretically maintain a pressure difference far below -50 Pa without working; Under the special condition of rapid pressure loss, it was difficult to deal with the rapid change of low pressure only by the exhaust fan, so it was necessary to design safety valve and other anti-leakage measures in the isolation cabin structure. Therefore, the initial stage of aircraft ascent is the key stage for the adjustment and control of the negative pressure isolation system. By controlling the exhaust air volume and adjusting parameters, it can adapt to the change of low pressure under normal flight conditions, form a relatively stable negative pressure environment, and meet the needs of biological control, isolation and transport.
Aircraft ; Computer Simulation ; Aviation/instrumentation* ; Humans ; Hydrodynamics ; Air Pressure ; Equipment Design ; Pressure

Objective: To identify influencing factors associated with the prognosis of sepsis patients receiving blood component transfusion, and to provide a more rational and scientific transfusion strategy for clinical management. Methods: Clinical data of 232 patients with sepsis treated at the Second Xiangya Hospital of Central South University between January 2022 and December 2023 were retrospectively analyzed. These patients were categorized into the transfusion group (n=64) and the non-transfusion group (n=168) based on whether they received transfusions, and the patients in the transfusion group were further divided into non-survivor group (n=26) and survivor group (n=38) based on their survival outcome. Baseline characteristics and clinical characteristics were compared between two groups. Factors impacting the prognosis of sepsis patients undergoing blood component transfusion were identified using logistic regression. Results: Compared to the non-transfusion group, the transfusion group showed significantly higher levels of coagulation indicators (prothrombin time, activated partial thromboplastin time, international normalized ratio, D-dimer) and inflammatory markers (C-reactive protein, procalcitonin, interleukin-6), while the level of hemoglobin, platelet, lymphocyte, fibrinogen, albumin, blood glucose, and oxygen saturation were significantly lower (P<0.05). The [M(P , P )] for C-reactive protein (mg/L), hemoglobin (g/L), and platelet count (×10 /L) in the transfusion vs non-transfusion groups were 178.0(156.1-178) vs 102.7(74.0-119.6), 88.5(72.3-113.0) vs 110.5(101-121.8), and 63.0(26.5-156.5) vs 202.5(108.3-286.8), respectively (all P<0.05). Logistic regression analysis revealed that hemoglobin level, platelet count, lactate concentration, and the storage duration of transfused red blood cells were independent risk factors affecting the survival outcomes of sepsis patients receiving transfusions (P<0.05). In septic transfusion patients, the [M(P , P )] lactate concentration (mmol/L) and RBC storage time (d) in the non-survivor vs survivor groups were 3.5(1.9-7.7) vs 2.1(1.3-3.5), 18.0 (13.0-18.0) vs 12.0(9.0-14.0), respectively (both P<0.05). Conclusion: Compared to non-transfused sepsis patients, those receiving transfusions exhibited poorer baseline conditions, more severe infections, and worse survival outcomes. More importantly, the study found that the timing of transfusion decisions and the quality control of blood products (such as storage duration) may directly impact patient prognosis, providing critical evidence for optimizing transfusion strategies in septicemia patients.

The continuous emergence of SARS-CoV-2 variants as well as other potential future coronavirus has challenged the effectiveness of current COVID-19 vaccines. Therefore, there remains a need for alternative antivirals that target processes less susceptible to mutations, such as the formation of six-helix bundle (6-HB) during the viral fusion step of host cell entry. In this study, a novel high-throughput screening (HTS) assay employing a yeast-two-hybrid (Y2H) system was established to identify inhibitors of HR1/HR2 interaction. The compound IMB-9C, which achieved single-digit micromolar inhibition of SARS-CoV-2 and its Omicron variants with low cytotoxicity, was selected. IMB-9C effectively blocks the HR1/HR2 interaction in vitro and inhibits SARS-CoV-2-S-mediated cell-cell fusion. It binds to both HR1 and HR2 through non-covalent interaction and influences the secondary structure of HR1/HR2 complex. In addition, virtual docking and site-mutagenesis results suggest that amino acid residues A930, I931, K933, T941, and L945 are critical for IMB-9C binding to HR1. Collectively, in this study, we have developed a novel screening method for HR1/HR2 interaction inhibitors and identified IMB-9C as a potential antiviral small molecule against COVID-19 and its variants.

Objective To evaluate the effect of sodium hypochlorite and Ultra Clean on root canal cleaning and dentin structure.Methods A total of 129 single canal isolated teeth were collected and root canal was prepared to M # with Waveone Gold nickel titani-um file.After preparation,they were divided into 3 groups by random number table according to irrigant:group A sodium hypochlorite+normal saline,group B sodium hypochlorite+EDTA,and group C sodium hypochlorite+Ultra Clean.The dye was stained with 1％methylene blue solution,and the penetration depth and range of the dye solution were observed under a type microscope.The removal of debris and stain layer in the root canal was observed by digital camera and scanning electron microscope.The change of dentin micro-structure was analyzed by Fourier infrared spectrometer.Results In the upper middle part of the root canal,the penetration depth and range of group C were greater than those of groups A and B(P＜0.05);the percentage of debris in group C was lower than that of groups A and B(P＜0.05),and the stain layer score in groups B and C was lower than that of group A(P＜0.05).In the lower root ca-nal segment,groups B and C were superior to group A in the evaluation of permeability,debris and stain removal(P＜0.05).The demineralization ability and exposure of dentin collagen fiber in group C were higher than those in group A and blank group(P＜0.05).Conclusion Sodium hypochlorite combined with Ultra Clean is considered to have good cleaning effect and strong demineralization ability,but it may slightly increase the exposure of organic matter such as collagen fiber.

This study aims to screen the diagnostic biomarkers for fecal antigen of Echinococcus granulosus(E.granulosus)in dogs with high specificity and sensitivity.The sheep-derived EgPSC artificially infected dogs were collected,and the negative and positive fecal samples of dogs with E.granulosus were prepared by arecoline hydrobromide leakage method.Polyclonal antibody,negative fecal antigen-polyclonal antibody conjugates and positive fecal antigen-polyclonal antibody conju-gates were purified by ammonium sulfate precipitation and affinity chromatography,three groups of samples were detected by ELISA and Western blot,LC-MS/MS and bioinformatics analysis were performed on the three groups of samples.The positive fecal antigen-polyclonal antibody con-jugate was used as the treatment group,the polyclonal antibody and the negative fecal antigen-polyclonal antibody conjugates were used as the control groups to screen the unique peptides of the treatment group.ELISA and Western blot showed that only the positive fecal antigen-polyclonal antibody conjugates were positive.According to LC-MS/MS and bioinformatics analysis,11 unique peptides were screened out only in the treatment group.Among them,3 proteins were related to E.granulosus,namely dysferlin,integrator complex 9 and diagnostic antigen gp50,which were mem-brane-associated proteins,INT complex components and diagnostic antigens.This study has pre-liminarily screened out three candidate canine E.granulosus fecal antigen diagnostic markers,pro-viding a reference for further exploration of diagnostic standards for E.granulosus,screening of echinococcosis target genes,and vaccine development.

Objective To investigate the expression of ferritinophagy-related gene ELAV-like RNA binding protein 1(ELAVL1)in multiple myeloma(MM)and elucidate its diagnostic and prognostic value for MM.Methods First,we analyzed ELAVL1 expression level in healthy controls and MM patients using data from the GEO and TCGA databases.Subsequently,bone marrow specimens were collected from 28 newly diagnosed MM patients and 20 healthy controls,and qRT-PCR was employed to validate ELAVL1 expression.The diagnostic and prognostic potential of ELAVL1 was assessed using ROC curve analysis and Kaplan-Meier survival curves.Additionally,univariate and multivariate COX regression analyses were performed to identify independent risk factors for MM prognosis.Finally,KEGG and GO enrichment analyses were performed using the DAVID online platform.Results The level of ELAVL1 expression was significantly higher in newly diagnosed MM patients and refractory/relapsed MM patients than in the healthy controls(P＜0.001).Moreover,ELAVL1 expression was positively correlated with the International Staging System(ISS)stage of MM(P＜0.01).Furthermore,qRT-PCR validation confirmed that ELAVL1 expression was elevated in the 28 newly diagnosed MM patients compared to the 20 healthy controls(P＜0.001).ROC curve analysis demonstrated that ELAVL1 could effectively differentiate between newly diagnosed MM patients,healthy controls,and MGUS patients(P＜0.001 and P=0.000 2,respectively).Survival analysis revealed that high ELAVL1 expression was associated with shorter progression-free survival(P=0.0141)and overall survival(P=0.008 0).Univariate and multivariate COX regression analyses identified high ELAVL1 expression as an independent risk factor for poor MM prognosis(P=0.005 0).KEGG analysis suggested that ELAVL1 might be involved in the Hippo and MAPK signaling pathways.Conclusion High ELAVL1 expression in MM may serve as a biomarker for diagnosis and poor prognosis.ELAVL1 may promote MM initiation and progression via the Hippo and MAPK signaling pathways.

Objective:From the dual perspectives of time and space,a quantitative evaluation of the policies for special outpatient chronic diseases in 31 cities in China over the years is carried out,so as to provide targeted suggestions for relevant departments in the design of medical insurance policies for chronic disease prevention and control.Methods:Combining the relevant literature and the content of the policy text,the policy consistency index model is constructed and quantitative evaluation is carried out based on the results.Results:Of the 421 policies,176 were"Narrowly covered"(41.81%),113 were"Meets expectations"(26.84%),109 were"Focused"(25.89%),and 23 were"Reasonably complete"(5.46%);while 30 cities were"qualified"or above in policy content(χ1),20 cities were"qualified"or above in policy audience(χ2),26 cities were"qualified"or above in policy inclination(χ3),4 cities were"qualified"or above in policy cohesion(χ4),and 24 cities were"qualified"or above in policy objective(χ5).Conclusion:The policies for special outpatient chronic diseases in 31 cities in China are characterized by rich content,wide audience coverage,and diverse policy linkages.To further enhance the security capabilities,it is recommended that sustained efforts be made to consolidate the foundation by standardizing the scope of disease types,strengthening the management of medical treatment in other places and optimizing the interface with other policies.

ObjectiveThis study aims to develop a prediction model for the compatibility of Chinese medicinal pairs based on Graph Convolutional Networks （GCN）， named HC-GCN. The model integrates the properties of herbs with modern pharmacological mechanisms to predict pairs with specific therapeutic effects. It serves as a demonstration by applying the model to predict and validate the efficacy of blood-activating herb pairs. MethodsThe training dataset for herb pair prediction was constructed by systematically collecting commonly used herb pairs along with their characteristic data， including Qi， flavor， meridian tropism， and target genes. Integrating traditional characteristics of herb with modern bioinformatics， we developed an efficacy-oriented herb pair compatibility prediction model （HC-GCN） using graph convolutional networks （GCN）. This model leverages machine learning to capture the complex relationships in herb pair compatibility， weighted by efficacy features. The performance of the HC-GCN model was evaluated using accuracy （ACC）， recall， precision， F1 score （F1）， and area under the ROC curve （AUC）. Its predictive effectiveness was then compared to five other machine learning models： eXtreme Gradient Boosting （XGBoost）， logistic regression （LR）， Naive Bayes， K-nearest neighbor （KNN）， and support vector machine （SVM）. ResultsUsing herb pairs with blood-activating effects as a demonstration， a prediction model was constructed based on a foundational dataset of 46 blood-activating herb pairs， incorporating their Qi， flavor， meridian tropism， and target gene characteristics. The HC-GCN model outperforms other commonly used machine learning models in key performance metrics， including ACC， recall， precision， F1 score， and AUC. Through the predictive analysis of the HC-GCN model， 60 herb pairs with blood-activating effects were successfully identified. Among of these potential herb pairs， 44 include at least one herb with blood-activating effects. ConclusionIn this study， we established an efficacy-oriented compatibility prediction model for herb pairs based on GCN by integrating the unique characteristics of traditional herbs with modern pharmacological mechanisms. This model demonstrated high predictive performance， offering a novel approach for the intelligent screening and optimization of traditional Chinese medicine prescriptions， as well as their clinical applications.

Objective: To identify influencing factors associated with the prognosis of sepsis patients receiving blood component transfusion, and to provide a more rational and scientific transfusion strategy for clinical management. Methods: Clinical data of 232 patients with sepsis treated at the Second Xiangya Hospital of Central South University between January 2022 and December 2023 were retrospectively analyzed. These patients were categorized into the transfusion group (n=64) and the non-transfusion group (n=168) based on whether they received transfusions, and the patients in the transfusion group were further divided into non-survivor group (n=26) and survivor group (n=38) based on their survival outcome. Baseline characteristics and clinical characteristics were compared between two groups. Factors impacting the prognosis of sepsis patients undergoing blood component transfusion were identified using logistic regression. Results: Compared to the non-transfusion group, the transfusion group showed significantly higher levels of coagulation indicators (prothrombin time, activated partial thromboplastin time, international normalized ratio, D-dimer) and inflammatory markers (C-reactive protein, procalcitonin, interleukin-6), while the level of hemoglobin, platelet, lymphocyte, fibrinogen, albumin, blood glucose, and oxygen saturation were significantly lower (P<0.05). The [M(P , P )] for C-reactive protein (mg/L), hemoglobin (g/L), and platelet count (×10 /L) in the transfusion vs non-transfusion groups were 178.0(156.1-178) vs 102.7(74.0-119.6), 88.5(72.3-113.0) vs 110.5(101-121.8), and 63.0(26.5-156.5) vs 202.5(108.3-286.8), respectively (all P<0.05). Logistic regression analysis revealed that hemoglobin level, platelet count, lactate concentration, and the storage duration of transfused red blood cells were independent risk factors affecting the survival outcomes of sepsis patients receiving transfusions (P<0.05). In septic transfusion patients, the [M(P , P )] lactate concentration (mmol/L) and RBC storage time (d) in the non-survivor vs survivor groups were 3.5(1.9-7.7) vs 2.1(1.3-3.5), 18.0 (13.0-18.0) vs 12.0(9.0-14.0), respectively (both P<0.05). Conclusion: Compared to non-transfused sepsis patients, those receiving transfusions exhibited poorer baseline conditions, more severe infections, and worse survival outcomes. More importantly, the study found that the timing of transfusion decisions and the quality control of blood products (such as storage duration) may directly impact patient prognosis, providing critical evidence for optimizing transfusion strategies in septicemia patients.