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.

BackgroundPain is one of the most common physical symptoms in patients with major depressive disorder （MDD）. The high comorbidity rate of MDD and pain aggravates patients' physical and psychological distress， undermines their treatment adherence， and contributes to poor clinical outcomes， posing a critical challenge for the clinical management of MDD. Anxiety symptoms are strongly associated with the pain severity in patients with MDD， yet the underlying mechanisms of the association remain poorly elucidated. Accumulating evidence have indicated that depressive symptoms and pain vigilance and awareness are involved in the modulation of pain perception. Nevertheless， few studies have incorporated these variables into an integrated analytical framework to clarify their parallel mediating effects on the relationship between anxiety symptoms and pain severity. ObjectiveTo explore the mediating pathways linking anxiety symptoms to pain severity via depressive symptoms and pain vigilance and awareness in patients with MDD， so as to provide insights for precise intervention for MDD accompanied by pain symptoms. MethodsA total of 249 patients who met the diagnostic criteria for MDD specified in the Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5） were recruited from Beijing Huilongguan Hospital from May to September 2025. Hamilton Depression Scale-17 item （HAMD-17）， Hamilton Anxiety Scale （HAMA）， Pain Vigilance and Awareness Questionnaire （PVAQ） and Numerical Rating Scale （NRS） were used for assessment. Partial correlation analyses were performed to examine correlations among these variables. Parallel mediating effects were tested using model 4 of the Process macro for SPSS， with depressive symptoms and pain vigilance and awareness as parallel mediators linking anxiety symptoms to pain severity. ResultsA total of 135 patients （54.22%） reported pain， comprising 59 （43.70%） with mild pain， 43 （31.85%） with moderate pain， and 33 （24.45%） with severe pain. Partial correlation analyses revealed significant positive correlations among HAMD-17， HAMA， PVAQ， and NRS scores in patients with MDD （r=0.198–0.424， P<0.05 or 0.01）. Anxiety symptoms positively predicted pain severity， with a direct effect of 0.128 （95% CI： 0.065–0.190）. Both depressive symptoms and pain vigilance and awareness acted as partial mediators linking anxiety symptoms to pain severity. The indirect effects were 0.057 （95% CI： 0.029–0.089） and 0.042 （95% CI： 0.016–0.079）， accounting for 25.22% and 18.58% of the total effect， respectively. ConclusionIn patients with MDD， anxiety symptoms exert a positive predictive effect on pain severity， which is partially mediated through the parallel roles of depressive symptoms and pain vigilance and awareness.

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.

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

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.

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.

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.

Objective: To translate the Menopause Perception Scale (MPS) into Chinese, and evaluate the reliability and validity of the Chinese version of the MPS. Methods: The MPS was translated back-translated, culturally adapted and pre-tested according to the Brislin translation model to develop the Chinese version of MPS. The menopausal women from five communities were selected using simple random sampling to assess the reliability and validity of the Chinese version of MPS. Content validity was evaluated based on expert ratings, criterion-related validity was evaluated using the Chinese version of the Menopause Rating Scale (MRS) as the criterion. Structural validity was evaluated using exploratory factor analysis and confirmatory factor analysis. Internal consistency was evaluated using Cronbach's α, and split-half reliability and test-retest reliability were calculated. Results: Totally 430 questionnaires were allocated, and 414 valid questionnaires were recovered, with an effective recovery rate of 96.28%. The Chinese version of the MPS consisted of 18 items across four dimensions: acceptance, sexual perception, normalization, and support perception. The item-level content validity index ranged from 0.833 to 1.000, and the scale-level content validity index average was 0.924. The correlation coefficients between the scores of each dimension and the total scores of the Chinese version of the MPS and the Chinese version of the MRS ranged from 0.529 to 0.790 (all P<0.05). Exploratory factor analysis extracted four common factors, with a cumulative variance contribution rate of 64.502%. Confirmatory factor analysis showed good model fit, with a root mean square error of approximation of 0.052, root mean square residual of 0.053, comparative fit index of 0.958, Tucker-Lewis index of 0.950, goodness of fit index of 0.908, incremental fit index of 0.958, and relative fit index of 0.884. The Cronbach's α of the Chinese version of the MPS was 0.916, the split-half reliability coefficient was 0.845, and the test-retest reliability was 0.906. Conclusion The Chinese version of the MPS demonstrates good reliability and validity, and can be used to assess the perceptions and attitudes of menopausal women in China toward menopause.