Objective:To discuss the influencing factors of angina pectoris in the patients with diabetes mellitus(DM),to construct a Bayesian network model to explore the network relationships among the influencing factors,and to predict the risk of angina pectoris in the patients with DM.Methods:Based on the UK Biobank(UKB)database,the Logistic regression aralysis model was used to screen the influencing factors of angina pectoris in the patients with DM.The taboo search algorithm was used for structure learning,and the Bayesian parameter estimation method was used for parameter learning to construct the Bayesian network model.Results:A total of 22 712 DM patients were included.The influencing factors of angina pectoris in the patients with DM included 14 variables:gender,age,body mass index(BMI),triglycerides(TG),total cholesterol(TC),glycated hemoglobin(HbA1c),hypertension,maternal smoking around delivery,smoking status,alcohol consumption,regular exercise,insomnia,sleep duration,and childhood relative body size(P<0.05).A Bayesian network model was constructed with 15 nodes and 22 directed edges.Among them,age,HbA1c,hypertension,regular exercise,BMI,and sleep duration were directly associated with the occurrence of angina pectoris in the patients with DM,while gender,smoking status,alcohol consumption,TC,TG,insomnia,childhood relative body size,and maternal smoking around delivery were indirectly associated with the occurrence of angina pectoris in the patients with DM.Conclusion:Age,HbA1c,hypertension,regular exercise,BMI,and sleep duration are direct influencing factors of angina pectoris in the patients with DM.Controlling HbA1c,blood pressure,and BMI levels,engaging in regular exercise,and maintaining appropriate sleep duration are beneficial for reducing the risk of angina pectoris in the patients with DM.

Objective:To screen the Alzheimer's disease(AD)-related genes and construct its diagnostic model using bioinformatics technology and machine learning(ML)algorithms,to discuss the immunological characteristics of AD patients,and to provide novel biomarkers for AD diagnosis.Methods:The AD-related gene expression dataset GSE125583 was downloaded from the Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)were identified through differential analysis.Gene Ontology(GO)functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway enrichment analyses were performed to explore the biological functions and signaling pathways of DEGs.A protein-protein interaction(PPI)network was constructed,and hub genes were screened using Cytoscape software combined with three ML algorithms:Least Absolute Shrinkage and Selection Operator(LASSO),eXtreme Gradient Boosting(XGBoost),and Random Forest(RF).The screened hub genes were utilized to build an AD diagnostic model via RF,followed by feature importance ranking.The model's efficacy and key genes were evaluated using a test set.Single-sample gene set enrichment analysis(ssGSEA)was used for immune cell infiltration analysis between AD group and control group.Results:Differential analysis identified 1 287 DEGs.The GO functional enrichment analysis results revealed that DEGs were primarily involved in biological functions related to neural signaling,synapses,and vesicles.KEGG signaling pathway enrichment analysis indicated significant enrichment of DEGs in ion transport,neurotransmitter,and ligand-gated channel pathways.Nine overlapping hub genes were screened by the three ML algorithms.In the AD diagnostic model,the top four key genes with highest diagnostic performance were adenylate cyclase-activating polypeptide 1(ADCYAP1),brain-derived neurotrophic factor(BDNF),platelet-derived growth factor receptor β(PDGFRB),and C-X-C motif chemokine receptor 4(CXCR4),with corresponding area under the curve(AUC)values of 0.852,0.795,0.820,and 0.756,respectively.The model achieved an AUC of 0.828,accuracy of 81.25%,sensitivity of 84.40%,and specificity of 71.43%.The immune cell infiltration analysis results demonstrated higher infiltration of macrophages,monocytes,natural killer(NK)cells,and lymphocytes in AD tissue.Among these,NK/natural killer T(NKT)cells and plasmacytoid dendritic cells showed significant correlations with the four key genes(P<0.05).Conclusion:The feature genes screened based on bioinformatics and ML exhibit diagnostic potential for AD.Genes such as ADCYAP1 may serve as potential biomarkers for AD diagnosis,offering significant implications for early prevention and treatment.

Objective To conduct a bibliometric analysis of domestic and international literature on the research of Sijunzi Decoction over the past 20 years,and to explore the research status,hotspots,and development trends of Sijunzi Decoction.Methods This article retrieved journal articles related to the research of Sijunzi Decoction from 2004 to 2024 in the CNKI,Wanfang,VIP,and Web of Science databases.Microsoft Excel was used for publication volume analysis,while CiteSpace software was employed for keyword co-occurrence,clustering,and burst analysis,and then the analysis results were visualized.Results After literature retrieval and screening,3 573 Chinese articles and 113 English articles were included.Over the past two decades,the publication volume showed a trend of steadily increasing.The most frequent keywords in Chinese and English literature on the research of Sijunzi Decoction were spleen deficiency syndrome and gene expression,while the keywords with strongest burst were experimental research and data mining.Conclusion The research of Sijunzi Decoction in the last 20 years was mainly through animal experiments and clinical applications,and the research hotspots focus on the treatment of diseases of spleen deficiency syndrome and on the improvement of immune function of cancer patients.The extraction and identification of active components in Sijunzi Decoction and the study on the therapeutic mechanism in diseases of spleen deficiency syndrome are probably the future research trends.

Objective To explore the correlation between central venous oxygen saturation(ScvO2),blood lactate(Lac),arterial oxygen saturation(SaO2)and mechanical ventilation time in infants with congenital heart disease(CHD).Methods Eighty-four CHD children treated in the First People's Hospital of Zunyi were enrolled between January 2020 and December 2024.According to postoperative mechanical ventilation time,they were divided into prolongation group(28 cases,mechanical ventilation time≥72 h)and non-prolongation group(56 cases,mechanical ventilation time<72 h).The clinical data,score of risk adjustment for congenital heart surgery(RACHS-1),levels of ScvO2,and Lac and SaO2 in the two groups were compared.The risk factors of postoperative mechanical ventilation time were analyzed by multivariate logistic regression analysis,and predictive value of ScvO2,Lac and SaO2 for prolonged mechanical ventilation time was analyzed by ROC curves.The clinical outcomes in the two groups were recorded.Results There were significant differences in age,preoperative pneumonia,RACHS-1 grading,and levels of ScvO2,Lac and SaO2 among children with different mechanical ventilation time(P<0.05).Multivariate logistic regression analysis showed that ScvO2,Lac and SaO2 were independent influencing factors of postoperative mechanical ventilation time(P<0.05).ROC curves analysis showed that area under the curve(AUC)values of ScvO2,Lac,SaO2 and combined detection for predicting prolonged postoperative mechanical ventilation were 0.846,0.863,0.839 and 0.917,and the best cut-off values were 67.64％,1.51mmol/L and 96.06％,respec-tively(P<0.05).The failure rate of weaning in the prolongation group was higher,and stay time in PICU and actual length of hospital stay were longer than those in non-prolongation group(P<0.05).Conclusion The levels of ScvO2,Lac and SaO2 are related to mechanical ventilation time in CHD infants.They are all independent risk factors affecting prolonged mechanical ventilation and can be applied as auxiliary detection indexes to predict the prolonga-tion of mechanical ventilation in clinical practice.

Objective To explore the correlation between central venous oxygen saturation(ScvO2),blood lactate(Lac),arterial oxygen saturation(SaO2)and mechanical ventilation time in infants with congenital heart disease(CHD).Methods Eighty-four CHD children treated in the First People's Hospital of Zunyi were enrolled between January 2020 and December 2024.According to postoperative mechanical ventilation time,they were divided into prolongation group(28 cases,mechanical ventilation time≥72 h)and non-prolongation group(56 cases,mechanical ventilation time<72 h).The clinical data,score of risk adjustment for congenital heart surgery(RACHS-1),levels of ScvO2,and Lac and SaO2 in the two groups were compared.The risk factors of postoperative mechanical ventilation time were analyzed by multivariate logistic regression analysis,and predictive value of ScvO2,Lac and SaO2 for prolonged mechanical ventilation time was analyzed by ROC curves.The clinical outcomes in the two groups were recorded.Results There were significant differences in age,preoperative pneumonia,RACHS-1 grading,and levels of ScvO2,Lac and SaO2 among children with different mechanical ventilation time(P<0.05).Multivariate logistic regression analysis showed that ScvO2,Lac and SaO2 were independent influencing factors of postoperative mechanical ventilation time(P<0.05).ROC curves analysis showed that area under the curve(AUC)values of ScvO2,Lac,SaO2 and combined detection for predicting prolonged postoperative mechanical ventilation were 0.846,0.863,0.839 and 0.917,and the best cut-off values were 67.64％,1.51mmol/L and 96.06％,respec-tively(P<0.05).The failure rate of weaning in the prolongation group was higher,and stay time in PICU and actual length of hospital stay were longer than those in non-prolongation group(P<0.05).Conclusion The levels of ScvO2,Lac and SaO2 are related to mechanical ventilation time in CHD infants.They are all independent risk factors affecting prolonged mechanical ventilation and can be applied as auxiliary detection indexes to predict the prolonga-tion of mechanical ventilation in clinical practice.

Objective:Hepatocellular carcinoma(HCC)is the most common primary malignant tumor of the liver.The diagnosis rate of early HCC is low,and most patients are diagnosed at the late stage and have a very poor prognosis.Therefore,it is urgent to explore effective early diagnosis markers and intervention targets for HCC.Cancer/testicular antigen 1A(CTAG1A)is abnormally expressed and highly immunogenic in a variety of tumors,but its expression characteristics and immunogenicity in HCC remain unclear.The aim of this study is to identify the expression and immunogenicity of CTAG1A in HCC tissues and cells,providing a new biomarker for the early diagnosis of HCC and a new potential target for clinical immunotherapy.Methods:This study screened the differentially expressed gene profiles between 10 pairs of very early HCC(BCLC stage 0 HCC)tumors and paracancerous tissues using a transcriptome microarray.The expression of CTAG1A was verified by RT-qPCR in an independent large sample(BCLC stage 0,A,B,C HCC tissues and adjacent non-tumor tissues,n=149)and various hepatocellular carcinoma cell lines.Bioinformatics tools(TepiTool of IEDB database and Swiss Model)were used to predict the MHC-Ⅰ and MHC-Ⅱ epitopes of CTAG1A.The candidate peptides were synthesized by solid-phase polypeptide synthesis method.After purification by HPLC and verification by mass spectrometry assay,the specific T cell responses of peripheral blood mononuclear cells(PBMC)of 9 HCC patients to all peptides were detected by IFN-γ enzyme-linked immunospot assay(ELISpot).The clinical samples were collected from HCC patients admitted to the Third Affiliated Hospital of Naval Medical University(Eastern Hepatobiliary Surgery Hospital)from 2015 to 2022.The collection and usage of all samples were carried out with the consent of the patients,and with the approval of the Ethics Committee of Eastern Hepatobiliary Surgery Hospital(EHBHKY2015-01-017)and in strict accordance with relevant requirements and ethical regulations.Statistical analysis was performed using SPSS 30.0 software,and the diagnostic efficiency was evaluated by ROC curve.Results:Transcriptome chip screening results showed that CTAG1A expression was significantly up-regulated in the very early-stage HCC(BCLC stage 0 HCC)(|FC|=99.16,P<0.0001).The verification using the clinical independent samples showed its high expression in all stages of HCC and better diagnostic efficacy in early-stage HCC(BCLC stage 0 HCC AUC=0.6893,sensitivity=85.71%;BCLC stage A HCC AUC=0.8229,sensitivity=83.33%).Furthermore,the expression of CTAG1A was significantly higher in multiple liver cancer cell lines than in relatively normal liver cell lines(P<0.001).Compared with alpha-fetoprotein(AFP),CTAG1A showed better diagnostic efficacy in BCLC stage 0 and stage A HCC(ROC curve analysis of AFP showed no significant difference in early HCC,P>0.05).Bioinformatics tools predicted that CTAG1A contained 8 MHC-type I and 4 MHC-type II epitopes.The IFN-γ ELISpot assay showed that 12 synthetic peptides could induce PBMC specific T cell response in HCC patients to varying degrees.Conclusion:CTAG1A is significantly overexpressed in early-stage HCC and has multi-epitope immunogenicity,which may activate CD8? and CD4? T cells,suggesting its potential as a target for HCC immunotherapy.It may provide a new direction for developing combined immunotherapy strategies based on mRNA vaccines or adoptive cell therapy.Compared with AFP,CTAG1A exhibits better diagnostic efficacy in early-stage HCC,suggesting its potential as a marker for early diagnosis of HCC.

Objective:To investigate the diagnosis of dual-energy X-ray absorptiometry(DXA)for osteoporosis(OP)of postmenopausal patients with rheumatoid arthritis(RA)in Qinghai region and the risk factors of them.Methods:A total of 200 postmenopausal female RA patients who admitted to Qinghai Hospital of Traditional Chinese Medicine from May 2022 to April 2023 were selected.All patients were tested for bone mineral density(BMD)after admission,and lumbar spines L1-L4,whole lumbar,large trochanter,Ward's triangle area,whole body and whole forearm were measured by DXA.According to the results of BMD test,patients whose BMD T values of all body parts-2.5 SD were less or equal to-2.5 were included in the OP group(121 cases),and patients whose BMD T value of all body parts were larger than-2.5 SD were included in the non-OP group(79 cases).The BMD T value of different body parts between two groups of RA patients were compared and analyzed.The area under curve(AUC)of receiver operating characteristic(ROC)curve was used to analyze the diagnostic efficiency of BMD T value for OP.The logistic regression method was adopted to analyze the risk factors that postmenopausal RA patients of Qinghai region occurred OP.Results:The BMD T values of L1,L2,L3,L4,whole lumbar,large trochanter,Ward's triangular area,whole body and whole forearm of OP group were obviously lower than those of the non-OP group.In analysis of ROC curve,the sensitivities of BMD T values of L1,L2,L3,L4,whole lumbar,large trochanter,Ward's triangle area,whole body and forearm were respectively 96.20%,95.22%,90.16%,96.03%,92.01%,89.36%,99.26%,90.02% and 96.03% in diagnosing OP,and the specificities of them were respectively 81.00%,82.19%,85.22%,83.06%,83.06%,90.22%,80.06%,86.23%,83.09%,and the AUC values of them were respectively 0.908,0.905,0.896,0.906,0.903,0.879,0.918,0.901 and 0.906.The results of the logistic-regression analysis showed that advanced age,long disease course,rheumatic activity scores of 28 joints,erythrocyte sedimentation rate and Calcium supplementation were the risk factors of occurring OP in postmenopausal RA patients in Qinghai region.Conclusion:The DXA method that detects BMD of RA patients who occur OP can be used as gold standard to assess OP,and there are many risk factors that affect the occurrence of OP in postmenopausal RA patients of Qinghai region.The clinical work should combine with relative factors to formulate reasonable measure so as to reduce the incidence of OP.

OBJECTIVE To investigate the preventive effect of cucurbitacin B （CB） on sepsis-induced acute lung injury （ALI） and its mechanism. METHODS The mice were divided into control group， model group， dexamethasone group （positive control， 2 mg/kg）， CB low-dose and high-dose groups （25， 50 mg/kg）. Each group was given relevant medicine intraperitoneally， once a day， for 3 consecutive days. Twenty-four hours after the last administration， those groups were given lipopolysaccharide （10 mg/kg） intraperitoneally to establish sepsis-induced ALI model （finally， 8 mice per group were included in the experiment）， except for control group. Twenty-four hours after medication， blood routine indicators （total white blood cell count， neutrophils count， lymphocytes count）， lung function indicators （total lung resistance， pulmonary outflow resistance， lung dynamic compliance， peak expiratory flow rate， and maximum ventilation volume）， dry wet ratio of lung tissue were measured in each group. The lung tissue level of myeloperoxidase （MPO）， and the serum levels of tumor necrosis factor-α （TNF-α）， interleukin 1β （IL-1β）， IL-6， superoxide dismutase （SOD） and malondialdehyde （MDA） were all detected. The pathological changes of lung tissue were observed； immunohistochemistry was used to detect the positive expression of phosphorylation signal transducer and activator of transcription 3 （p-STAT3） in the lung tissue. Western blot assay was used to detect the expressions of proteins related to IL-6/JAK2/ STAT3 signaling pathway in the lung tissue. RESULTS Compared with control group， total pulmonary resistance， pulmonary flow resistance， dry wet ratio of lung tissue， the total white blood cell count， neutrophils count， lymphocytes count of whole blood， the lung tissue level of MPO and serum levels of MDA， IL-6， IL-1β and TNF-α， the p-STAT3 protein optical density value， the protein expressions of IL-6 and IL-6 receptor， and the phosphorylation levels of JAK2 and STAT3 protein were increased significantly in the model group （P＜0.01）， while lung dynamic compliance， peak expiratory flow rate， maximum ventilation volume and serum level of SOD were decreased significantly （P＜0.05 or P＜0.01）. Pulmonary tissue showed alveolar collapse and infiltration of inflammatory cells. Compared with the model group， the above indexes of mice were reversed significantly in dexamethasone group and CB groups （P＜0.05 or P＜0.01）， the pathological damage of lung tissue was reduced. CONCLUSIONS CB can prevent sepsis-induced ALI by inhibiting the activity of Δ 基金项目遵义市科技计划项目（No.202252） IL-6/JAK2/STAT3 signaling pathway and relieving ＊第一作者主治医师。研究方向：重症医学。E-mail：fjuanxui@ 163.com inflammatory reactions. # 通信作者 主任医师。研究方向：儿童呼吸系统疾病诊断与治

ObjectiveTo analyze the antidepressant quality markers（Q-Marker） of Bupleuri Radix（BP） before and after vinegar-processing by ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS）， multivariate statistical analysis and network pharmacology. MethodUPLC-Q-TOF-MS was used to analyze the chemical basis of raw and vinegar-processed products of BP， and principal component analysis（PCA） orthogonal partial least squares-discriminant analysis（OPLS-DA） were used to identify the differential components in BP that changed significantly before and after vinegar-processing， which were regarded as candidate quality markers（Q-Marker）. Then the disease-drug-component-target network related to antidepressant effect of BP was constructed by network pharmacology， and the antidepressant Q-Marker of raw and vinegar-processed products of BP was determined. Rats were randomly divided into blank group， model group， fluoxetine group（2.67 mg·kg^-1） and total saponin group（0.72 mg·kg^-1）， except the blank group， rats in the other groups were subjected to chronic unpredictable mild stress（CUMS）. Three weeks after the start of modeling， rats in each administration group were given the corresponding dose of drugs once a day for 4 weeks， and rats in the blank and model groups were given normal saline with dose of 10 mL·kg^-1. At 1 day before modeling， 21 days and 28 days after administration， body mass weighing， sucrose preference test and open field test were performed on each group . After 28 days of administration， real-time fluorescence quantitative polymerase chain reaction（Real-time PCR） was used to detect the mRNA expression levels of phosphatidylinositol 3-kinase（PI3K）， protein kinase B（Akt）， mammalian target of rapamycin（mTOR）， glycogen synthase kinase-3β（GSK-3β）， forkhead box transcription factor O3a（FoxO3a） and β-catenin in hippocampal tissues of rats in each group， while protein expression levels of PI3K， Akt， mTOR and FoxO3a in hippocampal tissues of rats in each group were detected by Western blot. ResultThere were 19 components in BP showed significant changes before and after vinegar-processing， and 9 components such as saikosaponin A， saikosaponin B₁， saikosaponin B₂， saikosaponin C and saikosaponin D were identified as potential Q-Marker through S-plot differential marker screening. Combined with the disease-drug-component-target network， saikosaponin A， saikosaponin B₁， saikosaponin B₂ and saikosaponin D were identified as antidepressant Q-Marker of raw and vinegar-processed products of BP. According to the results of pharmacodynamic tests， after 28 d of administration， compared with the blank group， the body mass， sucrose preference index and open field total score of rats in model group， fluoxetine group and total saponin group decreased significantly（P<0.01）. Compared with the model group， the body mass， sucrose preference index and open field total score in total saponin group increased significantly（P<0.01）. Compared with the blank group， mRNA expression levels of PI3K， Akt， mTOR and β-catenin in hippocampus of rats in the model group decreased significantly（P<0.05）， while mRNA expression levels of GSK-3β and FoxO3a increased significantly（P<0.05）. Compared with the model group， mRNA expression levels of PI3K， Akt， mTOR and β-catenin in hippocampus of rats in the total saponin group were increased significantly（P<0.05）， while mRNA expression levels of GSK-3β and FoxO3a decreased significantly（P<0.05）. Compared with the blank group， the protein expression levels of Akt and mTOR in hippocampus of the model group decreased significantly（P<0.01）， while the protein expression levels of PI3K and FoxO3a increased significantly（P<0.01）. Compared with the model group， the expression level of Akt in hippocampus of the total saponin group increased significantly（P<0.01）， the mTOR expression level was increased but not statistically significant， while the protein expression levels of PI3K and FoxO3a decreased significantly（P<0.01）. ConclusionThe chemical constituents of BP changed greatly after vinegar-processing， and the antidepressant Q-Marker of raw and vinegar-processed products of BP was determined by chemical basis， pharmacodynamics， network pharmacology and signaling pathway， which provided a reference for further research on quality control， pharmacodynamic substance basis and processing mechanism of BP.

Objective:To screen the main characteristic variables affecting the incidence of cardiovascular and cerebrovascular diseases,and to construct the Bayesian network model of cardiovascular and cerebrovascular disease incidence risk based on the top 10 characteristic variables,and to provide the reference for predicting the risk of cardiovascular and cerebrovascular disease incidence.Methods:From the UK Biobank Database,315 896 participants and related variables were included.The feature selection was performed by categorical boosting(CatBoost)algorithm,and the participants were randomly divided into training set and test set in the ratio of 7∶3.A Bayesian network model was constructed based on the max-min hill-climbing(MMHC)algorithm.Results:The prevalence of cardiovascular and cerebrovascular diseases in this study was 28.8％.The top 10 variables selected by the CatBoost algorithm were age,body mass index(BMI),low-density lipoprotein cholesterol(LDL-C),total cholesterol(TC),the triglyceride-glucose(TyG)index,family history,apolipoprotein A/B ratio,high-density lipoprotein cholesterol(HDL-C),smoking status,and gender.The area under the receiver operating characteristic(ROC)curve(AUC)for the CatBoost training set model was 0.770,and the model accuracy was 0.764;the AUC of validation set model was 0.759 and the model accuracy was 0.763.The clinical efficacy analysis results showed that the threshold range for the training set was 0.06-0.85 and the threshold range for the validation set was 0.09-0.81.The Bayesian network model analysis results indicated that age,gender,smoking status,family history,BMI,and apolipoprotein A/B ratio were directly related to the incidence of cardiovascular and cerebrovascular diseases and they were the significant risk factors.TyG index,HDL-C,LDL-C,and TC indirectly affect the risk of cardiovascular and cerebrovascular diseases through their impact on BMI and apolipoprotein A/B ratio.Conclusion:Controlling BMI,apolipoprotein A/B ratio,and smoking behavior can reduce the incidence risk of cardiovascular and cerebrovascular diseases.The Bayesian network model can be used to predict the risk of cardiovascular and cerebrovascular disease incidence.