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.

ObjectiveTo investigate the therapeutic effect of Astragali Radix-mediated changes in gut microbiota on treating type 2 diabetes （T2DM）. MethodsA 12-week randomized， placebo-controlled clinical trial enrolled eighty patients with newly diagnosed type 2 diabetes and poor glycemic control in the Qi deficiency type. All patients received insulin therapy. The observation group （40 cases） was administered with Astragali Radix Granules， while the control group （40 cases） received a placebo. Both treamtents were taken orally twice daily. Changes in gut microbiota were assessed by 16s rDNA sequencing. Serum glucagon-like peptide-1 （GLP-1） levels were measured using enzyme-linked immunosorbent assay （ELISA）. Glucose metabolism indicators including fasting blood glucose （FPG）， 2-hour postprandial blood glucose （2 h PG），glycated albumin（GA）， and glycated hemoglobin （HbA1c） were evaluated. Pancreatic function was evaluated using fasting C-peptide （FCP）， 2-hour postprandial C-peptide （2 h CP）， and C-peptide area under the curve （AUC_cp）. Traditional Chinese medicine （TCM） syndrome scores， clinical efficacy， and safety indicators were also observed. ResultsIn terms of glucose metabolism indicators， compared with the baseline， both groups exhibited significantly lower FPG， 2 h PG， GA and HbA1C （P<0.01），while FCP， 2 h CP and AUC_cp were significantly higher （P<0.01）. Compared with the control group after the treatment， the observation group showed significantly lower FPG， 2 h PG， GA and HbA1C（P<0.05， P<0.01），and significantly higher FCP， 2 h CP and AUC_cp （P<0.05， P<0.01）， indicating that Astragali Radix can improve glucose metabolism. In terms of the diversity of gut microbiota， no significant differences were detected in the Chao1， Shannon and Simpson indexes of the two groups compared with their respective baselines. However， compared with the post-treatment control group， the observation group demonstrated significant increases in the Chao1， Shannon and Simpson indexes （P<0.05， P<0.01）. The β-diversity analysis showed significant separation in gut microbiota composition before and after treatment in both groups， indicating that Astragali Radix can significantly alter the structure and improve the diversity of gut microbiota. At the phylum level， compared with the baseline， both groups showed a significant increase in the relative abundance of Bacteroidota（P<0.01）. The relative abundance of the potentially harmful phylum Proteobacteria was significantly lower in the observation Group after treatment （P<0.01）. Compared with the post-treatment control group， the observation group had a significantly higher relative abundance of Bacteroidota（P<0.01）. No significant difference was found in Firmicutes/Bacteroidota （F/B） ratio between the two groups after treatment， and other phyla showed no significant differences. At the genus level， compared with the baseline， the observation group exhibited a significant increase in Bacteroides （P<0.01） and a significant decrease in Escherichia-Shigella （P<0.01）， whereas no significant difference was seen in the control group . Compared with the control group after treatment， the observation group after treatment had a significantly higher relative abundance of Bacteroides （P<0.01）. No significant differences were seen in other genera. Linear discriminant analysis （LDA） identified potential characteristics taxa： in the observation group， Bacteroidota at the phylum level and Bacteroides and Dubosiella at the genus level， in the control group， Proteobacteria at the phylum level as well as Barnesiella and Staphylococcus at the genus level. Correlation analysis based on a heatmap revealed that GLP-1 levels were positively correlated with Firmicutes， F/B ratio and Fusobacterium， and negatively correlated with Bacteroidota， Proteobacteria， Bacteroides and Escherichia-Shigella. In terms of clinical efficacy， compared with the control group， the total effective rate of the observation group was significantly higher （P<0.05）. Compared with the baseline， the scores for shortness of breath， fatigue， weakness， spontaneous sweating and reluctance to speak significantly decreased in both groups （P<0.01）. Compared with the control group after treatment， the score for weakness was significantly lower in the observation group （P<0.01），indicating that Astragali Radix could improve clinical symptoms and alleviate weakness symptoms. In terms of safety， compared with the baseline， alanine aminotransferase （ALT） levels significantly decreased in both groups （P<0.05，P<0.01），indicating that Astragali Radix did not induce any significant abnormalities in liver and kidney functions. ConclusionAstragali Radix demonstrates the potential to significantly improve the gut microbiota environment in patients of newly diagnosed type 2 diabetes with Qi deficiency. The therapeutic effect may contribute to glycemic control， possibly mediated by an elevation in GLP-1 level. These findings may support its further clinical investigations and potential applications.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveTo investigate the expression of prefrontal cortical neurons， methyltransferase-like 3 （METTL3）， fat mass and obesity-associated gene （FTO）， and AlkB homolog 5 （ALKBH5） proteins in a mouse model of post-traumatic stress disorder （PTSD）. MethodsA PTSD mouse model was established using a single prolonged stress and foot shock stimulation （SPSS） method. The despair， anxiety， and learning and memory functions of PTSD mice were assessed through the open field test， Y-maze test， and forced swimming test. Neuronal damage was detected via HE and Nissl staining. The expression levels of METTL3， FTO， ALKBH5， and neuronal nuclear protein （NEUN） were assessed by Western blot and immunofluorescence staining. ResultsCompared to control group， PTSD mice subjected to SPSS exhibited signs of despair， anxiety， and impaired learning and memory. HE and Nissl staining results showed neuronal damage in the prefrontal cortex of PTSD mice. Western blot and immunofluorescence staining results showed that the expression of the m6A-related proteins METTL3 and FTO decreased， while the expression of ALKBH5 increased in the prefrontal cortex. Additionally， NEUN protein levels showed a declining trend. ConclusionThe pathogenesis of PTSD may be associated with neuronal damage in the prefrontal cortex and alterations in m6A methylation proteins.

AIM:This study aims to investigate the regulatory effects of caffeic acid phenethyl ester(CAPE)on metabotropic glutamate receptor 5(mGluR5)and tyrosine kinase Fyn,and to explore its role in alleviating neuroinflam-mation and pathological features of Alzheimer disease(AD).METHODS:In vitro,the murine neuroblastoma N2a cell line was treated with amyloid β-protein 42 oligomers(Aβ42Os;10 nmol/L to 10 μmol/L)for 24 h.Cell viability was as-sessed by MTT assay.Western blot analyzed mGluR5 expression and Fyn phosphorylation(Tyr416).Pharmacological modulators(CHPG/MPEP)were used to evaluate mGluR5-mediated inflammatory cytokine regulation(qPCR)and Fyn ac-tivation.In vivo,wild-type(WT)and 5×FAD mice(WT,WT+CAPE,5×FAD and 5×FAD+CAPE)were analyzed for AD-related proteins,neuroinflammation(ELISA),glial activation(GFAP/Iba-1 immunofluorescence),and β-amyloid deposi-tion(thioflavin S).RESULTS:(1)Treatment with 1 μmol/L Aβ42Os increased mGluR5 expression(P<0.01)and Fyn phosphorylation(P<0.01)without affecting N2a cell viability.Intracerebral Aβ42Os injection similarly up-regulated hip-pocampal mGluR5 and Fyn(P<0.01).(2)MPEP reduced mGluR5 expression(P<0.01)and Fyn phosphorylation(P<0.01),while suppressing tumor necrosis factor-α(TNF-α)and interleukin-6(IL-6)mRNA levels(P<0.01).(3)CAPE decreased mGluR5-Fyn activation in N2a cells,neurons,and 5×FAD mice(P<0.01).(4)CAPE-treated 5×FAD mice exhibited reduced neuroinflammation markers(GFAP,Iba-1,TNF-α,IL-1β,and IL-6),Aβ plaques,and p-APP levels(P<0.01).CONCLUSION:Treatment with CAPE inhibits Aβ42Os-induced mGluR5-Fyn signaling activation,thereby attenuating neuroinflammation and the pathology associated with AD.

Objective To study the intervention effect of nursing staff's participation in antimicrobial stewardship(AMS)on the rational use of antimicrobial agents,and explore its role in constructing a scientific healthcare-associa-ted infection(HAI)control management.Methods The data on perioperative prophylactic use of antimicrobial agents,surgical-related HAI control,and pathogen detection before therapeutic use of antimicrobial agents among hospitalized patients in a hospital from January 2016 to December 2024 were collected.Relevant evaluation indica-tors before and after nursing staff participating in AMS were compared.2016-2018,2019-2021,and 2022-2024 were stages before intervention,during intervention,and after intervention,respectively.Results After nursing staff participated in AMS,the use rate of prophylactic antimicrobial agents 0.5-1 hour before surgery and discon-tinuation rate of antimicrobial agents within 24 hours after class Ⅰ incision surgery increased from 64.54％and 81.41％before intervention to 75.31％and 84.56％after intervention,respectively.Incidences of surgical-related HAI and surgical site infection in patients decreased from 3.11％and 0.96％before intervention to 1.37％and 0.17％after intervention,respectively.Pathogen detection rates before restricted-and special-grade antimicrobial agents treatment increased from 50.80％and 68.70％before intervention to 55.19％and 80.53％after interven-tion,respectively.Proportion of blood specimen from which coagulase-negative Staphylococcus was detected de-creased from 29.30％before intervention to 21.26％after intervention.Proportion of respiratory specimen from which Haemophilus influenzae was detected increased from 2.00％to 3.98％.Differences were all statistically sig-nificant(all P＜0.05).Conclusion As important members of the AMS team,nursing staff can effectively reduce irrational antimicrobial use,optimize medication timing and duration,and have a positive effect on ensuring patient safety through participating in the use and management of antimicrobial agents in hospitalized patients.

In order to effectively prevent and control the occurrence of catheter-associated urinary tract infection and ensure the safety of both patients and medical personnel,the National Health Commission of the People's Re-public of China officially released the recommended health industry standard"Standard for prevention and control of catheter-associated urinary tract infection"(WS/T862-2025)in Aug.2025.This paper provides an interpreta-tion of the standard,covering its drafting background,basis and content,to assist relevant medical personnel in healthcare institutions in enhancing their understanding and recognition of the standard,and to further promote its implementation and enforcement.

AIM:This study aims to investigate the expression and prognostic value of ubiquitin-conjugating enzyme E2C(UBE2C)in hepatocellular carcinoma(HCC),and to explore its impact on cancer stemness and the regulato-ry mechanisms.METHODS:(1)The TCGA and GEO databases were used to analyze UBE2C mRNA expression levels in HCC tissues and their correlation with prognosis using bioinformatics techniques,and these findings were further vali-dated in postoperative specimens from 107 HCC patients.The GEPIA database was used to analyze the correlation be-tween UBE2C and steroid receptor coactivator(SRC).(2)The CCK8,colony formation,wound healing,and spheroid formation assays were used to assess the effects of UBE2C on HCC cell proliferation,migration,and stemness.The inter-action between UBE2C and signal transducer and activator of transcription 3(STAT3),as well as its regulatory mecha-nism,was examined by Western blot and co-immunoprecipitation assays.(3)The subcutaneous xenograft model in nude mice was employed to validate the role of UBE2C in tumor growth in vivo.RESULTS:(1)Bioinformatics analysis re-vealed that UBE2C expression was significantly up-regulated in HCC tissues compared with adjacent normal tissues(P<0.05 in TCGA,and P<0.01 in GEO).Consistently,analysis of HCC specimens confirmed that high UBE2C expression was associated with shortened overall survival and disease-free survival of HCC patients(P<0.05).Furthermore,analysis using the GEPIA database revealed a positive correlation between UBE2C and SRC(P<0.01).(2)In vitro experiments demonstrated that UBE2C significantly promotes the proliferation and migration of HCC cells.Based on these findings,we presumed that UBE2C may regulate the phosphorylation of STAT3 at the Y705 site by modulating SRC activity,thereby in-fluencing the stemness characteristics of tumor cells.(3)In vivo experiments further confirmed that UBE2C inhibition sig-nificantly suppressed tumor growth.CONCLUSION:The UBE2C promoted proliferation and migration of HCC cells and regulated the stemness of HCC cells by interacting with STAT3.