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 situ bioimaging is a powerful tool for directly observing the localization, expression, and interactions of nucleic acids or protein targets within cells, providing essential insights into cell function and disease mechanisms. In recent years, the CRISPR/Cas9 system, a revolutionary gene-editing tool, has been applied to develop efficient in situ imaging techniques. This paper reviews recent CRISPR/Cas9-based imaging methods utilizing Cas9 protein, engineered single-guide RNA (sgRNA), and coupled fluorescent tags, and compares their application in living and fixed cells. It focuses on the specificity, signal amplification efficiency, and multi-modal imaging capabilities of these methods, with further discussion based on current research, aiming to offer a comprehensive overview of CRISPR/Cas9-based in situ bioimaging techniques, with some valuable reference and guidance for research in related fields.

Objective:To investigate the effect of nuclear receptor subfamily 2 group F member 2(NR2F2)on the biological behaviors of human ovarian cancer SKOV3 cells,and to clarify its molecular mechauism and provide the new idea for treatment of ovarian cancer.Methods:Gene Expression Profiling Interactive Analysis(GEPIA)Database analyse the expression level of NR2F2 gene in ovarian tissue,and analyse its correlation with clinical prognosis of ovarian cancer patients.The human ovarian cancer SKOV3 cells were divided into control group and NR2F2 over-expression(NR2F2 OE)group,which were transfected with mCherry control virus and NR2F2 OE over-expression virus,respectively,when the cell deusity reached 70％,and the stable transfection SKOV3 cell lines were screened with puromycin(puro)48h lafter.Real-time fluorescence quantitative PCR(RT-qPCR)and Western blotting methods were used to detect the transfection efficiencies of the cells;RT-qPCR method was used to detect the expression levels of NR2F2 and sex-determining region Y-box 2(SOX2)mRNA in the cells in two groups;Western blotting method was used to detect the expression levels of NR2F2,ATP-binding cassette superfamily G member 2(ABCG2),and programmed cell death 1-ligand 1(PD-L1)protcins in the cells in two groups.CCK-8 assay was used to detect the proliferation activities of the cells in two groups;Wound assay was used to detect the migration rates of the cells in two groups;Transwell chamber assay was used to detect the number of transmembrane cells;Spheroidization assay was used to detect the numbers of spheroids in the cells;peripheral blood mononuclear cells(PBMCs)-mediated tumor cell killing assay was used to detect the relative densities of surviving tumor cells;CCK-8 assay was used to detect the half maximal inhibitory concentration(IC50)of paclitaxel(PTX)and carboplatin(CBP).Results:Compared with normal ovarian tissue,the expression level of NR2F2 gene in ovarian tumor tissue was decreased(P＜0.05),and decreased with the improvement of clinical pathological grading of ovarian tumor.The patients with higher expression level of NR2F2 gene had better clincal prognosis.The SKOV3 cells with NR2F2 over-expresson were successfully constructed,and the expression levels of NR2F2 mRNA and protein in the cells in NR2F2 OE group were increased compared with control group(P＜0.001).The CCK-8 assay results showed that compared with control group,the proliferation activities of the cells in NR2F2 OE group were decreased at different time points(1,2,3,and 4 d)(P＜0.05 or P＜0.01).The cell wound assay results showed that compared with control group,the migration rate of the cells in NR2F2 OE group was decreased(P＜0.001).The Transwell assay results showed that compared with control group,the number of transmembrane cells in NR2F2 OE group was decreased(P＜0.01).Compared with control group,the number of the spheroids in NR2F2 OE group was decreased(P＜0.05),and the expression levels of SOX2 mRNA(P＜0.01)and protein(P＜0.001)were increased.Compared with control group,the relative density of surviving tumor cells in NR2F2 OE group was decreased,but the difference was not significant(P＜0.05),and the expression level of PD-L1 protein was decreased(P＜0.05).Compared with control group,the proliferation activities of cells in NR2F2 OE group were decreased(P＜0.05),and the drug sensitivities of the cells to PTX and CBP were enhanced(P＜0.05);the IC50 of PTX was significantly reduced,while the IC50of CBP could not be calculated due to excessively high drug concentration;the expression level of ABCG2 protein was decreased(P＜0.05).Conclusion:The over-expression of NR2F2 may inhibit the proliferation,migration,and invasion of the human ovarian cancer SKOV3 cells,decrease the expression levels of SOX2,PD-L1 and ABCG2 proteins,suppress the stemness and immune evasion ability of the SKOV3 cells,and enhance the sensitivities of the SKOV3 cells to PTX and CBP.

The Hedgehog(HH)signaling pathway is involved in various developmental processes of vertebrates and invertebrates,including embryogenesis,stem cell renewal,tissue regeneration,the occurrence and development of tumor and chemotherapy resistance.Overactivation and abnormal expression of key components in the HH signaling pathway are associated with the development of various malignant tumors.Phosphorylation plays an important role in regulating the activity and function of proteins in normal cells,and the disorder of phosphorylation-dephosphorylation cascade is closely related to tumorigenesis.The abnormal activation of this signaling pathway is also related to protein phosphorylation,while its complex underlying mechanism needs to be further explored.This article reviewed the research progress of the HH signaling pathway and protein phosphorylation modification in malignant tumors,focusing on the regulatory effect of phosphorylation modification on the activity of HH signaling pathway and its effect on the occurrence and development of malignant tumors,in order to provide a theoretical basis for the in-depth development and clinical application of targeted drugs for phosphatase/dephosphatase.

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.

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.

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.

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 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.