Objective To compare clinical efficacy of different regimens in treatment of pruritus in maintenance hemodialysis(MHD)patients.Methods A total of 50 patients with MHD admitted to the Sixth People's Hospital of Jiujiang City from August 1,2022 to April 30,2024 as subjects and were divided into two groups according to random number table method.Control group(n=25)was treated with sodium thiosulfate.On this basis,gabapentin combination therapy was added in observation group(n=25).Effects of two groups were compared after 8 weeks of treatment.Results Total clinical effective rate of observation group was significantly higher than that of control group(P＜0.05).After 8 weeks of treatment,scores and total scores of all dimensions of quality of life in two groups were higher than before treatment,and observation group was higher than control group(P＜0.05).Conclusion Sodium thiosulfate combined with gabapentin in treatment of MHD patients with pruritus can not only relieve pruritus symptoms,improve sleep quality,but also have good safety.

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 establish a quality standard for the bacterial endotoxin test method of fructose sodium diphosphate injections(FDP injections),so as to provide reference for the formulation and revision of the national standard for this drug.Methods:The interference test and bacterial endotoxins test of 22 batch samples of FDP in-jections from nine manufacturers were performed with TALs,and the bacterial endotoxins of samples were tested and the results were judged.Results:A bacterial endotoxin limit value of 0.72 EU·mg-1 for fructose sodium diphos-phate was established,which was suitable for 22 batches of FDP injections met the requirements.Conclusion:The bacterial endotoxin test method established in this study can be used to substitute the rabbit pyrogen test and meet the quality control requirements of FDP injections.

Objective To compare clinical efficacy of different regimens in treatment of pruritus in maintenance hemodialysis(MHD)patients.Methods A total of 50 patients with MHD admitted to the Sixth People's Hospital of Jiujiang City from August 1,2022 to April 30,2024 as subjects and were divided into two groups according to random number table method.Control group(n=25)was treated with sodium thiosulfate.On this basis,gabapentin combination therapy was added in observation group(n=25).Effects of two groups were compared after 8 weeks of treatment.Results Total clinical effective rate of observation group was significantly higher than that of control group(P＜0.05).After 8 weeks of treatment,scores and total scores of all dimensions of quality of life in two groups were higher than before treatment,and observation group was higher than control group(P＜0.05).Conclusion Sodium thiosulfate combined with gabapentin in treatment of MHD patients with pruritus can not only relieve pruritus symptoms,improve sleep quality,but also have good safety.

Objective:To establish a quality standard for the bacterial endotoxin test method of fructose sodium diphosphate injections(FDP injections),so as to provide reference for the formulation and revision of the national standard for this drug.Methods:The interference test and bacterial endotoxins test of 22 batch samples of FDP in-jections from nine manufacturers were performed with TALs,and the bacterial endotoxins of samples were tested and the results were judged.Results:A bacterial endotoxin limit value of 0.72 EU·mg-1 for fructose sodium diphos-phate was established,which was suitable for 22 batches of FDP injections met the requirements.Conclusion:The bacterial endotoxin test method established in this study can be used to substitute the rabbit pyrogen test and meet the quality control requirements of FDP injections.

Objective:To explore the differences of the circadian rhythm gene polymorphisms between patients with major depressive disorder and those with bipolar disorder, providing a genetic basis for differential diagnosis.Methods:70 patients who were still diagnosed with major depressive disorder after 5 years and 68 patients who were still diagnosed with bipolar disorder from Zhongda Hospital affiliated to Southeast University from 2012 to 2018 were included in this study. Single nucleotide polymorphisms (SNPs) of circadian rhythm gene were selected for genetic testing. And the differences in genotype frequency, allele frequency, and haplotypes of each SNP between major depressive disorder and bipolar disorder were analyzed using UNPHASED 3.1.7.Results:The analysis of genotype frequency revealed statistically significant differences in genotype frequency of PER1rs2253820, PER1rs2735611, PER3rs12566042, PER3rs17031614, and PER3rs79372391 between the two groups ( OR(95% CI)=2.386(1.173-4.854), 2.357(1.166-4.764), 0.351(0.176-0.703), 0.389(0.196-0.773), 0.389(0.196-0.773) respectively; all P<0.05). Haplotype analysis showed that the T-C-C-T-G haplotype, in CLOCK loci (rs12505266, rs2272073, rs3817444, rs11133389 and rs12505265) was significantly different between major depressive disorder group and bipolar disorder group ( OR(95% CI)=0.108(0.010-1.185), P=0.027). Conclusion:There are significant differences in circadian rhythm gene polymorphisms between patients with major depressive disorder and bipolar disorder. Carrying the PER1rs2253820TT and PER1rs2735611GG genotypes is a risk factors for bipolar disorder.

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 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.