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 explore the mechanism of action of Neiyi Soft Extract in the treatment of endometriosis(EMS)based on network pharmacology and transcriptomics.Methods A model of SD rat with EMS was replicated by autotransplantation method.After successful modeling,the rats were randomly divided into model group,Neiyi Soft Extract low-,medium-and high-dose groups and dienogest group,with 10 rats in each group.Another sham-operated group(10 rats)was set up.After four consecutive weeks of intervention,the volume size of the endometriotic lesions was measured,and its pathological changes were detected by hematoxylin-eosin(HE)staining.RNA was extracted from the rat lesions for transcriptomic sequencing,and Gene Ontology(GO)enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)functional enrichment analysis were performed on the differential genes among various groups.The main active ingredients and their targets of Neiyi Soft Extract were collected and screened in databases such as TCMSP,the disease targets of EMS were collected through databases such as OMIM,the intersection targets between the drug ingredient targets and the diseases were obtained by using Venn diagrams,GO enrichment analysis and KEGG pathway enrichment analysis of genes in the intersection targets of the drug ingredients and the diseases were performed by using gene enrichment analysis online tool(Metascape).The network pharmacology enrichment pathway and transcriptomics enrichment pathway were taken for intersection,the mRNA and protein expression levels of the key targets on the intersection pathway were correspondingly detected by real-time quantitative polymerase chain reaction(qPCR)and Western Blot,respectively.Results The volume of lesions in the model group was significantly increased compared with that of the sham-operated group(P<0.01);the volume of lesions in rats in the drug-administered groups was significantly reduced compared with that of the model group(P<0.05).A total of 341 active ingredients were obtained from Neiyi Soft Extract,and there were 2 178 disease-related targets of EMS,and 278 intersections between drug targets and disease targets;189 differential genes were screened in the sham-operated group and the model group;255 differential genes were screened in the model group and Neiyi Soft Extract high-dose group;and 740 differential genes were screened in the sham-operated group and the Neiyi Soft Extract high-dose group,including 390 up-regulated genes and 350 down-regulated genes.The result of intersection of KEGG enrichment pathways between the network pharmacology and transcriptomics showed that the distriution mainly included P53 signaling pathway,FOXO signaling pathway,cell cycle,etc.The qPCR and Western Blot validation results showed that Neiyi Soft Extract could inhibit the proliferation of endometrial stromal cells and up-regulated the mRNA and protein expression levels of BAX,Caspase3 in EMS rats(P<0.05 or P<0.01),and down-regulated BCL-2 mRNA and protein expression levels(P<0.05 or P<0.01).Conclusion Neiyi Soft Extract may play a therapeutic role in the treatment of EMS by regulating the P53 signaling pathway.

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.

Objective:To discuss the clinical efficacy of recombinant human growth hormone(rhGH)in the treatment of the pediatric patients with growth hormone deficiency(GHD)and idiopathic short stature(ISS),and to clarify its clinical application value in the pediatric patients with short stature of different etiologies.Methods:The clinical data of 132 children with short stature who treated with rhGH from January 2018 to January 2023 were collected.They were divided into GHD group(n=70)and ISS group(n=62)based on different etiologies.The bone age,target height(TH),body mass index(BMI),height standard deviation score(HtSDS),changes in height standard deviation scores(ΔHtSDS)before treatment and 6 months after treatment,and growth velocity(GV)of the pediatric patients were calculated.Propensity score matching(PSM)and inverse probability of treatment weighting(IPTW)were used to balance the confounding factors between the pediatric patients in two groups and the efficacy and safety of the pediatric patients in two groups were evaluated.Results:There were significant differences in whether children were full-term,bone age,bone age maturity,and TH of the pediatric patients between two groups(P<0.05).Compared with before treatment,the height and HtSDS of the pediatric patients in both GHD and ISS groups were significantly increased after treated for 6 months(P<0.05).Before matched by PSM,there were significant differences in full-term,bone age,bone age maturity,and TH of the pediatric patients between two groups(P<0.05).After matched by PSM,there were no significant differences in gender,region,term birth status,mode of delivery,feeding method,age,bone age,height,BMI,TH,and pretreatment HtSDS of the pediatric patients between two groups(P>0.05);the standardized mean difference(SMD)differences of covariates except for region were<0.2.After weighted by IPTW,there were no significant differences in gender,region,term birth status,mode of delivery,feeding method,age,bone age,height,BMI,TH,and pretreatment HtSDS of the pediatric patients between two groups(P>0.05);all SMD of covariates except for term birth status were<0.2.Before balancing covariates,after meatched by PSM matching,and after weighted by IPTW weighting compared with GHD group,the GV and ΔHtSDS of the pediatric patients in ISS group were slightly increased,but the difference was not significant(P>0.05).In terms of adverse reactions,2 cases(2.68%)of fasting hyperglycemia and 7 cases(10.00%)of hypothyroidism occurred in GHD group;3 cases(4.84%)of fasting hyperglycemia and 2 cases(3.23%)of hypothyroidism occurred in ISS group.Conclusion:rhGH can promote the height increase in the patients with GHD and ISS,and there is no significant difference in the height-increasing efficacy between GHD and ISS children.The incidence of adverse reactions is relatively low during treatment,indicating good overall safety.

Objective:Abnormal immune system activation and inflammation are crucial in causing Parkinson's disease.However,we still don't fully understand how certain immune-related genes contribute to the disease's development and progression.This study aims to screen key immune-related gene in Parkinson's disease based on weighted gene co-expression network analysis(WGCNA)and machine learning. Methods:This study downloaded the gene chip data from the Gene Expression Omnibus(GEO)database,and used WGCNA to screen out important gene modules related to Parkinson's disease.Genes from important modules were exported and a Venn diagram of important Parkinson's disease-related genes and immune-related genes was drawn to screen out immune related genes of Parkinson's disease.Gene ontology(GO)analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)were used to analyze the the functions of immune-related genes and signaling pathways involved.Immune cell infiltration analysis was performed using the CIBERSORT package of R language.Using bioinformatics method and 3 machine learning methods[least absolute shrinkage and selection operator(LASSO)regression,random forest(RF),and support vector machine(SVM)],the immune-related genes of Parkinson's disease were further screened.A Venn diagram of differentially expressed genes screened using the 4 methods was drawn with the intersection gene being hub nodes(hub)gene.The downstream proteins of the Parkinson's disease hub gene was identified through the STRING database and a protein-protein interaction network diagram was drawn. Results:A total of 218 immune genes related to Parkinson's disease were identified,including 45 upregulated genes and 50 downregulated genes.Enrichment analysis showed that the 218 genes were mainly enriched in immune system response to foreign substances and viral infection pathways.The results of immune infiltration analysis showed that the infiltration percentages of CD4+ T cells,NK cells,CD8+ T cells,and B cells were higher in the samples of Parkinson's disease patients,while resting NK cells and resting CD4+ T cells were significantly infiltrated in the samples of Parkinson's disease patients.ANK1 was screened out as the hub gene.The analysis of the protein-protein interaction network showed that the ANK1 translated and expressed 11 proteins which mainly participated in functions such as signal transduction,iron homeostasis regulation,and immune system activation. Conclusion:This study identifies the Parkinson's disease immune-related key gene ANK1 via WGCNA and machine learning methods,suggesting its potential as a candidate therapeutic target for Parkinson's disease.

Objective:To explore the genetic etiology of pediatric intensive care unit (PICU) mortality cases and summarize their clinical characteristics.Methods:This was a retrospective cohort study. The study population consisted of 234 children who died within 7 d after admitted to the PICU of Children′s Hospital of Fudan University from January 2017 to December 2021. The clinical diagnoses, laboratory test results, and genetic testing results were collected. These patients were divided into the pathogenic gene variation positive (PGVP) group and the pathogenic gene variation negative (PGVN) group according to the results of genetic testing. The Mann-Whitney U test and Pearson′s chi-square test or Fisher′s exact probability method were used to compare the clinical characteristics between the groups. Results:A total of 234 cases were enrolled, including 139 (59.4%) males and 95 (40.6%) females. The age at death was 1.0 (0.4, 3.7) years old and the length of PICU stay was 16 (6, 33) days. There were 62 cases (26.5%) PGVP, and the mutated pathogenic genes included immune genes (23 cases (37.1%)), metabolic genes (11 cases (17.7%)), neuromuscular genes (11 cases (17.7%)), cardiovascular genes (4 cases (6.5%)), and genes of other systems (13 cases (21.0%)). The age at death in PGVP cases was significantly lower than in PGVN cases (0.6 (0.3, 1.4) vs. 1.3(0.5, 4.3) years old, Z=3.85, P<0.001). Compared with the PGVN group, the PGVP group had a higher incidence of family history and chronic complex conditions (CCC) than the PGVN group (6.5% (4/62) vs. 0.6% (1/172) and 93.5% (58/62) vs. 76.2% (131/172), χ2=8.87, P=0.018 and 0.003, respectively). Children in the PGVP group were admitted with higher incidence of severe infection, decreased consciousness or coma, moderate-to-severe anemia, thrombocytopenia, protracted diarrhea, and abnormalities in muscle strength or tone than those in the PGVN group (74.2%(46/62) vs. 45.9%(79/172), 50.0%(31/62) vs. 35.5%(61/172), 32.3%(20/62) vs. 18.0%(31/172), 21.0%(13/62) vs. 10.5%(18/172), 25.8%(16/62) vs. 4.1%(7/172), 16.1%(10/62) vs. 5.2%(9/172), χ2=14.63, 4.04, 5.41, 4.37, 24.30, 7.25, all P<0.05). Pathogenic genes that occurred more than twice included IL2RG (5 cases), SMN1 (4 cases), and SH2D1A (3 cases, including 2 single gene varients and 1 copy number varient). Conclusions:Among the deceased cases in the PICU, the main genetic causes are immune-related, metabolic, and neuromuscular genetic disorders. Critically ill children with a family history, CCC, and early features such as severe infections, decreased consciousness or coma, moderate to severe anemia, thrombocytopenia, protracted diarrhea, or abnormalities in muscle strength or tone should be closely monitored and undergo early genetic testing.

Objective:To investigate the effect of combined treatment of hyperforin(HPF) and amlexanox(AM) on obesity and metabolic disorders.Methods:ob/ob mice were used as an obese mice model and treated with HPF alone(2.5 mg/kg intraperitoneal injection) or combined with AM(50 mg/kg, gavage administration) for 4 weeks. Their body weight and food intake were monitored, glucose tolerance test and insulin tolerance test were performed, serum alanine aminotransferase(ALT) and aspartate aminotransferase(AST) levels were detected. Nuclear magnetic resonance was used to detect the body composition and metabolic cage was used to detect the energy consumption. After sampling, HE staining was used to observed the pathological change of fat and liver tissues, Western blotting and enzyme-linked immunosorbent assay(ELISA) were used to detect the cyclic adenosine monophosphate(cAMP)-protein kinase A(PKA) signaling pathway.Results:Compared to the vehicle-treated mice(54.07 g), HPF-treated mice showed attenuated body weight gain(51.33 g, P=0.042) and reduced total fat mass( P=0.011); while administration of HPF in combination with AM(HPF/AM) further reduced the body weight(47.61 g, P=0.041). HE staining analysis showed that HPF alone or HPF/AM treatment both decreased the diameters of adipocytes and infiltration of white fat( P=0.014, P=0.032) in brown adipose tissues, which resulted in a trend of browning. However, HPF/AM-treatment didn′t further diminish adipocytes or reduce lipid accumulation in brown adipose tissues compared to HPF-treated mice. In addition, the basal oxygen consumption rate(VO 2, P<0.001) and(VCO 2, P=0.002) of HPF-treated mice were mainly elevated in the light phase relative to that of control mice; while HPF/AM-treatment further promote the energy consumption both in the dark phase and light phase. Notably, cAMP-PKA signaling pathway was obviously activated under HPF/AM-treatment in inguinal white adipose tissue. Moreover, HPF/AM-treatment showed beneficial effects on glucose metabolism and fatty liver, as indicated by improved insulin resistance, reduced liver steatosis( P=0.049) and the serum ALT levels( P=0.008). Conclusion:Combined administration of HPF and AM is an effective strategy in the treatment of obesity, improvement of metabolic disorders and alleviation of catecholamine resistance.

Background Fine particulate matter (PM_2.5) is a serious air pollutant associated with elevated levels of C-reactive protein (CRP), an inflammatory indicator. Objective To assess the potential impacts of long-term exposure to PM_2.5 on CRP levels based on previous epidemiological studies. Methods PubMed, Embase, Web of Science, CNKI, and Wanfang databases were searched to screen the cohort studies published from January 1, 2000 to January 1, 2022 on the effects of long-term exposure to PM_2.5 on CRP levels. "Fine Particulate Matter", "PM_2.5", "Particulate Air Pollutants", "Ambient Particulate Matter", "CRP", "C-reactive Protein", and "High Sensitivity C-reactive Protein" in English or Chinese were the key words used in the search. The percentage change in CRP level per 10 μg·m⁻³ increase in PM_2.5 concentration in each study was extracted, followed by meta-analysis, subgroup analysis, and sensitivity analysis. Results A total of 1241 articles were retrieved, and 7 articles were included. Random-effects models were used to merge the included data, and it was found that the percentage of CRP level increased by 10.41% (95%CI: 2.24%-18.57%, P<0.05), when PM_2.5 concentration increased by 10 μg·m⁻³, І²=84.2%. The subgroup analysis conducted with grouping based on the annual mean concentration of PM_2.5 long-term exposure showed that the intra-group heterogeneity was significantly reduced in the <15 μg·m⁻³ and the 15- μg·m⁻³ groups, and the subgroup forest analysis showed differences between the two groups. The results of sensitivity analysis showed that there was a high degree of heterogeneity among the 7 studies, and the 2 papers with the highest annual average PM_2.5 concentration were the sources of heterogeneity. The Egger test and the funnel plot indicated that no obvious publication bias was found. Conclusion Long-term exposure to PM_2.5 can raise levels of CRP in human body.

Objective:To assess the urethral mobility of normal parous women in China and explore the impacts of related risk factors on it using translabial ultrasound.Methods:Females who met the inclusion criteria in 37 tertiary hospitals from February 2017 to August 2018 were included. All women underwent standardized translabial ultrasound examination and the urethral rotation angle (URA), bladder neck position at maximum Valsalva maneuver (BNP-V) and bladder neck descent (BND) were measured. Questionnaires were used to collect basic information including age, height, weight, body mass index (BMI), past medical history, maternity history, and urinary incontinence related history. Mann-Whitney U test and multiple linear regression analysis were adopted to explore the influences of age, BMI, delivery mode and parity on normal parous women′s urethral mobility. Then, the study subjects were divided into different groups and the corresponding values of URA, BNP-V and BND were compared. Results:Compared with parous women with normal BMI and no history of vaginal delivery, those who were overweight and/or had a history of vaginal delivery were more likely to gain greater URA and BND ( P<0.05). The URA and BND were not significantly different between women with different times of cesarean sections ( P>0.05); while for women with a history of vaginal delivery, these two parameters increased with the increase of the number of transvaginal deliveries ( P<0.05). Conclusions:BMI and vaginal delivery are important risk factors for the urethral mobility of normal parous women. The urethral mobility increases with the increase of BMI and the number of vaginal deliveries.

Subject To compare the irradiation-induced injury and clinical efficacy between SIB-IMRT and LB-IMRT for early-stage breast cancer after breast-conserving surgery.Methods:From November 2002 to February 2012, 353 early breast cancer patients who underwent IMRT after breast-preserving surgery at Shandong Cancer Hospital were selected, of whom 218 patients receiving SIB-IMRT and 135 patients receiving LB-IMRT.The prescription dose of the SIB-IMRT group was the ipsilateral breast (PTV b ) 1.8-1.9 Gy, 27-28 times, and concurrent tumor bed (PTV t) 2.15-2.3 Gy, 27-28 times. In the LB-IMRT group, the prescription dose was PTV b 2.0 Gy, 25 times, followed by PTV t boost 2.0 Gy, 5-8 times. Results:The median follow-up time was 92 months. The excellent, good, fair, and poor cosmetic results in the SIB-IMRT and LB-IMRT groups were 10.1% and 12.6%, 85.8% and 80.7%, 3.7% and 5.2%, 0.5%, and 0.7%, respectively ( P=0.731). The 5-year locoregional recurrence rates (LRRs) in the SIB-IMRT and LB-IMRT groups were 3.21% and 5.93% and the 10-year LRRs were 4.13% and 6.67%, respectively ( P=0.209, 0.280). The 3-, 5-, 8-, and 10-year overall survival rate in the SIB-IMRT and LB-IMRT groups were 97.7% and 97.8%, 96.3% and 95.2%, 94.9% and 92.0%, 93.6% and 90.3%, respectively ( P=0.288). The 3-, 5-, 8-, and 10-year disease-free survival in the SIB-IMRT and LB-IMRT groups were 95.4% and 93.8%, 91.8% and 87.7%, 89.9% and 84.1%, 89.0% and 82.1%, respectively ( P=0.160). Conclusion:There is no significant difference in the cosmetic effect, local control rate, and survival rate between SIB-IMRT and LB-IMRT after breast-preserving surgery in patients with early-stage breast cancer. SIB-IMRT is a safe and feasible treatment.