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.

Objective: To understand the trends of classroom lighting and illumination of primary and secondary schools in Beijing from 2016 to 2023, so as to provide a scientific basis for targeted improvement measures. Methods: A sampling survey was conducted on the lighting and illumination indicators of 8 390 classrooms in primary and secondary schools in Beijing from 2016 to 2023. The survey included classroom daylight factor, window to floor area ratio, average illuminance and illuminance uniformity on the desks, average illuminance and illuminance uniformity on blackboards, as well as classroom lighting and blackboard illumination sources. Intergroup comparisons were performed using the Kruskal-Wallis H test and the Chi square test, and Spearman correlation analysis was used to examine the trend of classroom lighting and illumination changes. Results: Except the window to floor area ratio, the measured values and compliance rates of all lighting and illumination indicators showed an overall upward trend from 2016 to 2023 (daylight factor r = 0.27, χ 2 trend =206.80, average illuminance on the desk surface r =0.30, χ 2 trend =87.97, illuminance uniformity on the desk surface r =0.14, χ 2 trend =73.59, average illuminance on the blackboard r =0.33, χ 2 trend =477.43, illuminance uniformity on the blackboard r = 0.09, χ 2 trend =50.76) (all P ＜0.01). The lighting and illumination indicators of classrooms (included classroom daylight factor, average illuminance and illuminance uniformity on the desks, average illuminance and illuminance uniformity on blackboards) in urban schools, primary schools, and secondary schools from 2016 to 2023 showed an upward trend (urban r =0.23-0.40, χ 2 trend =88.66-392.18; primary school r =0.12-0.36, χ 2 trend =39.50-281.44; secondary schools r =0.06-0.31, χ 2 trend =11.79-213.73) (all P ＜ 0.01 ). The illuminance uniformity on the blackboard in suburban schools showed a downward trend ( r = -0.09, χ 2 trend =31.53, both P ＜0.01). The illuminance uniformity on the desk surface in suburban schools showed no significant change ( r =0.03, χ 2 trend =1.23, both P ＞0.05). The other indicators showed an upward trend (daylight factor r =0.28, χ 2 trend =40.69, average illuminance on the desk surface r =0.24, χ 2 trend =16.35, average illuminance on the blackboard r =0.25, χ 2 trend =118.05, all P ＜0.01). The trends of classroom and blackboard illumination sources were that fluorescent lamps decreased year by year and LED lamps increased by year (classroom illumination sources χ 2 trend =1 059.82, blackboard illumination sources χ 2 trend =1 070.25, both P ＜0.01). Conclusions The classroom lighting and illumination in primary and secondary schools in Beijing has shown an overall improving trend from 2016 to 2023. However, problems remain, such as limited improvement of illuminance uniformity indicators, late start and poor effect of reconstruction in suburban schools. Further improvements are still needed.

Objective To investigate the effects of long non coding RNA MAGI2 antisense chain RNA3(LncRNA MAGI2-AS3)on the migration,invasion,and epithelial mesenchymal transition(EMT)of gastric cancer(GCa)cells by regulating the miR-194-5 p/caveolin-1(CAV1)axis.Methods Fifty-two GCa patients who underwent surgical resection in our hospital from August 2022 to December 2023 were selected.Cancer and adjacent tissues were collected,and AGS,MKN45,HGC-27,and GES1 cells were cultured in vitro.The expression of MAGI2-AS3,miR-194-5p,and CAV1 in tissue samples and cell lines was analyzed.AGS cells were randomly separated into AGS group,sh-AGS group sh-MAGI2-AS3 group,miR-NC group,and in miR-194-5p group.The proliferation,apoptosis,migration,and invasion of cells in each group were compared.Immunoblotting was applied to analyze the expression of E-cadherin,CAV1,proliferating cell nuclear antigen(PCNA),N-cadherin,Bax,matrix metalloproteinase 2(MMP2),and vimentin of cells in each group.Dual luciferase assay was applied to analyze the relationship between MAGI2-AS3 and miR-194-5p,and between miR-194-5p and CAV1.Results The expression of MAGI2-AS3 mRNA,CAV1 mRNA,and positive expression rate of CAV1 protein in GCa tissue increased,while the expression of miR-194-5p mRNA decreased(P＜0.05).The expression of MAGI2-AS3 mRNA,CAV1 mRNA,and CAV1 protein in HGC-27,MKN45,and AGS cells was higher than that of GES1 cells,the expression of miR-194-5p mRNA was lower than that of GES1 cells(P＜0.05).Compared with the AGS and sh-AGS groups,the cell absorbance,number of clones,invasion and migration,expression of CAV1,PCNA,N-cadherin,MMP2,and vimentin in sh-MAGI2-AS3 group decreased,the apoptosis rate,expression of E-cadherin,and Bax increased(P＜0.05).Compared with the miR-NC group and sh-MAGI2-AS3 group,the cell absorbance,number of clones,invasion and migration,expression of CAV1,PCNA,N-cadherin,MMP2,and vimentin in in-miR-194-5p group increased,the apoptosis rate,expression of E-cadherin,and Bax reduced(P＜0.05).ENCORI database found that there were multiple binding sites between MAGI2-AS3 and miR-194-5p,and between miR-194-5p and CAV1.Compared with the WT-MAGI2-AS3+miR-NC group,the luciferase activity in the WT-MAGI2-AS3+miR-194-5p group decreased(P＜0.05),while compared with the WT-CAV1+miR-NC group,the luciferase activity in the WT-CAV1+miR-194-5p group decreased(P＜0.05).Conclusion LncRNA MAGI2-AS3 silencing can target miR-194-5p to downregulate CAV1,thereby inhibiting GCa cell migration,invasion,and EMT.

Objective To develop a combined model integrating radiomics and 3D deep learning features for improving the predictive efficacy of overall survival in non-small cell lung cancer(NSCLC)patients undergoing radiotherapy,thereby providing a foundation for optimizing individualized radiotherapy strategies.Methods A retrospective analysis was conducted on 522 NSCLC patients from 3 centers.Radiomics features were extracted from the tumor region of interest on radiotherapy planning CT scans,and a 3D-SE-ResNet was constructed to extract deep learning features.Following feature extraction,features were selected via univariate Cox analysis and Lasso-Cox regression,and a combined model was established by fusing the two feature types through principal component analysis.The discriminative ability of the model was evaluated using the concordance index(C-index)and the area under the receiver operating characteristic curve(AUC),while the risk stratification efficacy was verified by Kaplan-Meier survival analysis.Results The predictive performance of deep learning features was significantly superior to that of radiomics features(C-index:0.73 vs 0.65).The combined model achieved the highest predictive performance in the training set,internal test set,and external test set(C-index:0.74,0.69,0.72 respectively),with higher AUC values for predicting 1-year,2-year,and 3-year OS than either single model.Kaplan-Meier analysis showed significant differences in survival between the high-and low-risk groups(Log-rank test,P<0.001),and calibration curves indicated good consistency between predicted and actual survival outcomes.Conclusion The combined model integrating radiomics and 3D deep learning features can accurately predict survival outcomes in NSCLC patients undergoing radiotherapy.The multi-center validation results support its potential application in prognosis stratification for individualized radiotherapy.

Objective:To evaluate the long-term protective efficacy of the recombinant Chinese hamster ovary cell-derived hepatitis B vaccine（CHO-HepB）26 years post-vaccination in the rural China.Methods:Zhengding county，Hebei province was designated as a rural monitoring site for CHO-HepB efficacy. Study participants included individuals born between 1997 and 1999 who had completed the three-dose CHO-HepB primary series without booster doses. A cross-sectional survey was conducted in late 2024 using random sampling. Demographic and vaccination history data were collected via questionnaires，and hepatitis B virus（HBV）serological markers were detected using chemiluminescence. Historical surveillance data were integrated to infer infection statuses of HBsAg-positive individuals and evaluate longitudinal trends in anti-HBs seropositivity and antibody titers.Results:Among 178 participants（mean time since vaccination：26.2 years），the seroprevalence rates were 0.6% for HBsAg（95% CI：0.0%-1.6%），64.6% for anti-HBs（95% CI：57.6%-71.6%），and 1.1% for anti-HBc（95% CI：0.0%-2.7%）. Compared to the pre-vaccination baseline HBsAg positivity of 11.3% in children under 10 years of age，the estimated vaccine protection rate was 95%. Two notable cases were identified：one with concurrent HBsAg and anti-HBc positivity and one with anti-HBs and anti-HBc positivity，suggestive of transient HBV exposure（1999—2009）without chronicity. Natural immune boosting was inferred for the latter case based on anti-HBs titer dynamics. Longitudinal analysis of four prior cross-sectional surveys（2005，2009，2013，and 2017）revealed no significant upward trends in HBsAg and anti-HBc positivity（both P>0.05）over 26 years，while anti-HBs seropositivity declined significantly（ P<0.05）from 6 to 26 years post-vaccination. Conclusion:The CHO-HepB vaccine demonstrates sustained immunological persistence and robust long-term protection up to 26 years post-immunization. Continued emphasis on rigorous implementation of mother-to-child transmission prevention strategies is critical for future hepatitis B control.

Objective:To explore the clinical application value of serum N-glycan profiles for evaluating the severity of liver tissue inflammation in patients with chronic hepatitis B (CHB).Methods:A total of 221 CHB patients who underwent liver biopsy at Mengchao Hepatobiliary Hospital of Fujian Medical University from January 2018 to December 2020 were retrospectively enrolled. The Scheuer scoring system was used to assess the histological inflammation grade of the liver tissue. Serum N-glycan levels were measured using DNA sequencer-assisted N-glycan fingerprinting (NGFP). Using the upper limit of the alanine aminotransferase (ALT) reference value (40 U/L) as a cutoff, logistic regression models were developed to construct diagnostic models under two scenarios: normal ALT or abnormal ALT. Models based on serum N-glycan levels and serum N-glycan levels combined with routine laboratory indicators, were used to non-invasively evaluation of various pathological grades of liver tissue inflammation in CHB patients. The DeLong test was used to compare the diagnostic efficacy of the models by analyzing the areas under the receiver operating characteristic curve (AUC). Glycosylation-related gene expression differences associated with varying degrees of liver inflammation were analyzed using the Gene Expression Omnibus (GEO) database.Results:In CHB patients with normal ALT level, the relative abundances of N-glycan structure peak 1 (NGA2F) and peak 2 (NGA2FB) increased with higher liver inflammation grades, while the relative abundance of peak 5 (NA2) decreased ( P<0.05). The AUCs of the HIS-G model (HIS-G A) and its enhanced version (HIS-G A Plus) for identifying significant inflammation and necrosis (≥G2, indicating the initiation of antiviral therapy) were 0.805 (95% CI 0.690-0.899) and 0.904 (95% CI 0.821-0.960), respectively. In CHB patients with ALT>40 U/L, the relative abundances of peaks 1 (NGA2F), 2 (NGA2FB), and 3 (NG1A2F) increased with higher liver inflammation grades, while the relative abundances of peaks 8 (NA3) and 11 (NA4) decreased ( P<0.05). The AUCs of the HIS-G model (HIS-G B) and its enhanced version (HIS-G B Plus) for identifying significant inflammation (≥G2) were 0.810 (95% CI 0.727-0.889) and 0.838 (95% CI 0.754-0.901), respectively. With increasing liver inflammation grades, the expression levels of four glycosyltransferase genes (CHST4, FUT8, SLC51B, and ST8SIA4) were significantly upregulated ( P<0.05). Conclusions:Serum N-glycan biomarker models can be used to assist in evaluating the severity of liver tissue inflammation in CHB patients with both normal and abnormal ALT levels.

Objective To develop a combined model integrating radiomics and 3D deep learning features for improving the predictive efficacy of overall survival in non-small cell lung cancer(NSCLC)patients undergoing radiotherapy,thereby providing a foundation for optimizing individualized radiotherapy strategies.Methods A retrospective analysis was conducted on 522 NSCLC patients from 3 centers.Radiomics features were extracted from the tumor region of interest on radiotherapy planning CT scans,and a 3D-SE-ResNet was constructed to extract deep learning features.Following feature extraction,features were selected via univariate Cox analysis and Lasso-Cox regression,and a combined model was established by fusing the two feature types through principal component analysis.The discriminative ability of the model was evaluated using the concordance index(C-index)and the area under the receiver operating characteristic curve(AUC),while the risk stratification efficacy was verified by Kaplan-Meier survival analysis.Results The predictive performance of deep learning features was significantly superior to that of radiomics features(C-index:0.73 vs 0.65).The combined model achieved the highest predictive performance in the training set,internal test set,and external test set(C-index:0.74,0.69,0.72 respectively),with higher AUC values for predicting 1-year,2-year,and 3-year OS than either single model.Kaplan-Meier analysis showed significant differences in survival between the high-and low-risk groups(Log-rank test,P<0.001),and calibration curves indicated good consistency between predicted and actual survival outcomes.Conclusion The combined model integrating radiomics and 3D deep learning features can accurately predict survival outcomes in NSCLC patients undergoing radiotherapy.The multi-center validation results support its potential application in prognosis stratification for individualized radiotherapy.

Objective:To explore the influencing factors of self-management of first-treatment pulmonary tuberculosis patients based on the random forest model, and to provide a theoretical basis for clinical staff to improve the self-management of pulmonary tuberculosis patients by providing efficient, high-quality, and individualized interventions.Methods:A cross-sectional study was used to select pulmonary tuberculosis patients who were hospitalized in the Department of Respiratory Medicine of the Fourth People′s Hospital of the Ningxia Hui Autonomous Region and who met the inclusion and exclusion criteria from December 2023 to February 2024 by using the convenience sampling method as the study subjects. General information questionnaire, Chronic Disease Patients′ Self-health Management Ability Assessment Scale, Perceived Social Support Scale, Hospital Anxiety and Depression Scale, and a tuberculosis prevention and treatment knowledge questionnaire were used to conduct the survey, and Spearman′s correlation was used to analyze the correlation between variables, and multivariate linear regression and a random forest model were used to analyze the influencing factors of self-management.Results:A total of 204 first-treatment pulmonary tuberculosis patients, 111 males and 93 females, 64 patients aged 18-44 years, 59 patients aged 45-59 years, and 81 patients ≥60 years were finally investigated. The total self-management score of tuberculosis patients was 162.00 (148.00, 176.75), and the total self-management score was positively correlated with the total perceived social support score, family support, friend support, and other support, respectively ( r values were 0.307-0.400, all P<0.01), negatively correlated with the anxiety and depression scores, respectively ( r=-0.195, -0.313, both P<0.01), and positively correlated with the total score of knowledge of tuberculosis control ( r=0.257, P<0.01); the results of multiple linear stepwise regression analysis showed that literacy, family support, other support, anxiety, and knowledge of tuberculosis control were the influencing factors of self-management ability ( t values were -2.89-2.98, all P<0.05), which explained a total of 23.1% of the total variance; and the random forest model ranked the importance of the influencing factors in the order of high to low were other support, family support, knowledge of tuberculosis control, literacy, and anxiety. Conclusions:The self-management of first-treatment pulmonary tuberculosis patients is at an intermediate level, In order to improve the self-management ability of first-treatment pulmonary tuberculosis patients, clinical personnel should establish a "patient-centered" self-management education concept, pay attention to the construction of their social support system, provide adequate, continuous, individualized knowledge education and information support, promote their psychological health, and reduce their negative emotions.

Infancy is a critical period for children's growth and development. During this period，the reasonable increase of fat mass percentage and fat mass index is very important for children's healthy growth. However，excessive increases in fat mass percentage and fat mass index may increase the risk of metabolic related diseases. In China，the research field of body composition in infants is still in the development stage，and the relevant research results and literature are relatively few. This article summarizes the domestic and foreign research on infant body composition，including application techniques，influencing factors and application significance，so as to provide reference for the formulation of domestic infant body composition reference standards and related clinical and scientific research work.

Objective:To explore the correlation between serum hepcidin antimicrobial peptide (HAMP), secreted phosphoprotein 1 (SPP1), and regulator of G protein signaling 2 (RGS2) levels and the clinical pathological characteristics of gastric cancer patients, and their predictive value for postoperative recurrence or metastasis.Methods:A total of 92 gastric cancer patients treated at Handan First Hospital from March 2021 to March 2023 were selected as the gastric cancer group, and 92 healthy individuals who underwent physical examinations during the same period were selected as the control group. The serum levels of HAMP, SPP1 and RGS2 were compared between the two groups. According to the mean levels of HAMP, SPP1, and RGS2 in the serum of gastric cancer patients, they were divided into HAMP high level group and HAMP low level group, SPP1 high level group and SPP1 low level group, RGS2 high level group and RGS2 low level group. The clinicopathological characteristics of gastric cancer patients with different levels of HAMP, SPP1 and RGS2 were compared respectively. After a median follow-up of 18 months, gastric cancer patients were divided into a non-recurrence or metastasis group ( n=59) and a recurrence and metastasis group ( n=33) based on whether the tumor recurred or metastasized. The serum levels of HAMP, SPP1, and RGS2 were compared between the two groups of patients. The predictive value of HAMP, SPP1 and RGS2 for postoperative recurrence or metastasis in patients with gastric cancer was analyzed by using the receiver operator characteristic (ROC) curve. Results:Compared with the control group, the gastric cancer group had higher levels of serum HAMP [ (52.28±5.44) ng/ml vs. (31.22±4.18) ng/ml] and SPP1 [ (55.96±6.43) ng/ml vs. (36.99±5.25) ng/ml] ( t=29.44, P<0.001; t=21.92, P<0.001), and lower level of RGS2 [ (3.72±0.66) mg/L vs. (5.11±0.87) mg/L) ] ( t=12.21, P<0.001). There were statistically significant differences in maximum tumor diameter ( χ2=13.07, P<0.001; χ2=6.71, P=0.010; χ2=10.56, P=0.001), TNM staging ( χ2=7.42, P=0.006; χ2=6.36, P=0.012; χ2=5.39, P=0.020), lymph node metastasis ( χ2=23.41, P<0.001; χ2=6.52, P=0.011; χ2=13.11, P<0.001), and differentiation degree ( χ2=9.01, P=0.003; χ2=7.97, P=0.005; χ2=15.29, P<0.001) between the gastric cancer patients in the HAMP high level group ( n=44) and the HAMP low level group ( n=48), the SPP1 high level group ( n=43) and the SPP1 low level group ( n=49), and the RGS2 high level group ( n=50) and the RGS2 low level group ( n=42). Compared with the non-recurrence or metastatic group, the recurrence and metastatic group had higher levels of serum HAMP [ (59.26±5.66) ng/ml vs. (48.37±4.28) ng/ml] and SPP1 [ (62.85±6.36) ng/ml vs. (52.11±5.38) ng/ml] level ( t=10.40, P<0.001; t=8.60, P<0.001), and lower level of RGS2 [ (3.01±0.48) mg/L vs. (4.12±0.69) mg/L] ( t=8.19, P<0.001). ROC curve analysis showed that the area under the curve (AUC) values of serum HAMP, SPP1, and RGS2 levels alone for predicting postoperative recurrence or metastasis in gastric cancer patients were 0.777, 0.813, and 0.778, respectively. The AUC value of the combination of the three indicators for predicting postoperative recurrence or metastasis in gastric cancer patients was 0.871. The predictive efficacy of the combination of the three indicators for predicting postoperative recurrence or metastasis in gastric cancer patients was better than that alone ( Z=2.51, P=0.035; Z=2.61, P=0.032; Z=2.71, P=0.029) . Conclusions:The levels of HAMP and SPP1 in the serum of gastric cancer patients increase, while the level of RGS2 decreases, and the levels of the three are related to the maximum tumor diameter, TNM staging, lymph node metastasis and differentiation degree, and their combined detection has higher predictive value for postoperative recurrence or metastasis in gastric cancer patients.