Objective:To explore the causal association between insulin-like growth factor-1(IGF-1)and colorectal cancer(CRC)based on two sample Mendelian randomization(MR)analysis.Methods:A bidirectional two sample MR analysis was conducted based on publicly aggregated data from the IEU OpenGWAS project.The inverse variance weighted(IVW)method was used as the main analysis model to assess the causal relationship between IGF-1 and CRC.Additional analyses were performed using weighted median(WM),MR-Egger regression,weighted mode estimator(WME),and simple mode(SM)methods.Sensitivity analysis was performed to assess the robustness of the results.Results:A total of 386 single nucleotide polymorphisms(SNPs)were selected as instrumental variables(IVs)with IGF-1 as the exposure factor.The MR analysis results revealed a positive causal association between IGF-1 and the risk of CRC[odds ratio(OR)=1.178,95％confidence interval(CI):1.092-1.272)](P＜0.001),and the association remained significant after adjusting for height[OR(95％CI)=1.214(1.111,1.327)](P＜0.001).Cochran's Q-test showed heterogeneity among the IVs(P＜0.05),while the horizontal pleiotropy of IV was not detected by the MR-Egger regression(P＞0.05).The leave-one-out analysis showed that the MR results were robust.Reverse MR analysis indicated no reverse causal relationship between IGF-1 and CRC[OR(95％CI):1.017(0.997,1.037)](P=0.103).Conclusion:There is a causal relationship between IGF-1 level and CRC,and elevated IGF-1 level could be a risk factor for CRC.

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 study the influence of the severity of diabetic retinopathy (DR) on the visual function of patients with type 2 diabetes, to provide scientific basis for the early prevention and control of DR.Methods:This study was designed as a cross-sectional study, recruiting already-diagnosed type 2 diabetes patients in four community health service centers in Guizhou Province between February and September 2022. Employing the Chinese version of the Visual Function Index-14 (VF-14), assess the participants′ near vision, visual adaptation, subjective visual perception, and stereo vision, with higher scores indicating poorer visual function. Categorize the severity of each eye′s damage into no diabetic retinopathy (DR), mild non-proliferative diabetic retinopathy (NPDR), moderate NPDR, severe NPDR, and proliferative diabetic retinopathy (PDR), and use a 5-level DR grading system to evaluate the overall severity of diabetic retinopathy in both eyes. Employing linear regression analysis to investigate the linear relationship between DR and visual function index. Local weighted regression evaluates the nonlinear relationship between the DR composite score and the scores of visual function, with a steeper slope indicating poorer visual function for that level.Results:A total of 542 patients with type 2 diabetes were investigated, including 244 (45.02%) males, 298 (54.98%) females, and 162 (29.89%) patients with DR. After adjusting for confounders, compared with those without DR, patients with binocular DR Had overall scores ( β=0.136, P=0.003), near vision ( β=0.163, P<0.001), visual adaptation ( β=0.092, P=0.042), subjective vision ( β=0.120, P=0.009) and stereo vision ( β=0.094, P=0.044) were higher than those without DR. There were no differences in visual functions between DR And monocular DR. The local weighted regression curve showed that near vision (slope: 23.78) and overall score (slope: 58.37) increased sharply from mild to moderate NPDR in both eyes. Visual adaptation (slope: 5.37, 7.72), subjective vision (slope: 6.53, 7.93), stereovision (slope: 0.74, 0.91) increased slowly in mild to moderate NPDR in both eyes and in moderate to severe NPDR/PDR in both eyes. Conclusion:Binocular DR is associated with impaired visual function, but there is no difference between monocular DR And non-DR visual function. The early damage of DR To visual function is mainly manifested in near vision. In the prevention and control of DR, more attention should be paid to visual function, especially the change of near vision, and retinal damage should not be assessed solely by visual status.

Objective:To study the influence of the severity of diabetic retinopathy (DR) on the visual function of patients with type 2 diabetes, to provide scientific basis for the early prevention and control of DR.Methods:This study was designed as a cross-sectional study, recruiting already-diagnosed type 2 diabetes patients in four community health service centers in Guizhou Province between February and September 2022. Employing the Chinese version of the Visual Function Index-14 (VF-14), assess the participants′ near vision, visual adaptation, subjective visual perception, and stereo vision, with higher scores indicating poorer visual function. Categorize the severity of each eye′s damage into no diabetic retinopathy (DR), mild non-proliferative diabetic retinopathy (NPDR), moderate NPDR, severe NPDR, and proliferative diabetic retinopathy (PDR), and use a 5-level DR grading system to evaluate the overall severity of diabetic retinopathy in both eyes. Employing linear regression analysis to investigate the linear relationship between DR and visual function index. Local weighted regression evaluates the nonlinear relationship between the DR composite score and the scores of visual function, with a steeper slope indicating poorer visual function for that level.Results:A total of 542 patients with type 2 diabetes were investigated, including 244 (45.02%) males, 298 (54.98%) females, and 162 (29.89%) patients with DR. After adjusting for confounders, compared with those without DR, patients with binocular DR Had overall scores ( β=0.136, P=0.003), near vision ( β=0.163, P<0.001), visual adaptation ( β=0.092, P=0.042), subjective vision ( β=0.120, P=0.009) and stereo vision ( β=0.094, P=0.044) were higher than those without DR. There were no differences in visual functions between DR And monocular DR. The local weighted regression curve showed that near vision (slope: 23.78) and overall score (slope: 58.37) increased sharply from mild to moderate NPDR in both eyes. Visual adaptation (slope: 5.37, 7.72), subjective vision (slope: 6.53, 7.93), stereovision (slope: 0.74, 0.91) increased slowly in mild to moderate NPDR in both eyes and in moderate to severe NPDR/PDR in both eyes. Conclusion:Binocular DR is associated with impaired visual function, but there is no difference between monocular DR And non-DR visual function. The early damage of DR To visual function is mainly manifested in near vision. In the prevention and control of DR, more attention should be paid to visual function, especially the change of near vision, and retinal damage should not be assessed solely by visual status.

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 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:To explore the mechanism of Tanshinone ⅡA(TⅡA)in improving ischemia/reperfusion(I/R)injury of H9c2 cardiomyocytes by activating Sirtuin 1(SIRT1)-adenosine 5'-monophosphateactivated protein kinase(AMPK)pathway through miR-155-5p.Methods:H9c2 cells were cultured in vitro and I/R damage model was established.After modeling,H9c2 cells were randomly divided into model group,TⅡA group,TⅡA+miR-NC group,TⅡA+miR-155-5p mimics group,10 μmol/L TⅡA was added for intervention after transfection,and the H9c2 cells supplemented with DMSO were used as control group.qRT-PCR was used to detect expression level of miR-155-5p;MTT method was used to analyze cell proliferation ability;flow cytometry was used to evaluate cell apoptosis;ELISA was used to determine the levels of TNF-α,IL-4,IL-10,IL-17,lactate dehydrogenase(LDH),malo-ndialdehyde(MDA)and superoxide dismutase(SOD);Western blot was used to detect relative expressions of SIRT1,AMPK and p-AMPK proteins.Results:Compared with control group,expression of miR-155-5p in model group was increased,cell viability was decreased,apoptosis rate and expressions of TNF-α,IL-17,LDH and MDA were increased,while expressions of IL-4,IL-10,SOD,SIRT1 and p-AMPK were decreased(P<0.05);compared with model group,expression of miR-155-5p in TⅡA group was reduced,cell viability was increased,apoptosis rate and expressions of TNF-α,IL-17,LDH and MDA were decreased,while expressions of IL-4,IL-10,SOD,SIRT1 and p-AMPK were increased(P<0.05);compared with TⅡA group and TⅡA+miR-NC group,expression of miR-155-5p in TⅡA+miR-155-5p mimics group was increased,cell viability was decreased,apoptosis rate and expressions of TNF-α,IL-17,LDH and MDA were increased,while expressions of IL-4,IL-10,SOD,SIRT1 and p-AMPK were decreased(P<0.05).Conclusion:TⅡA can improve I/R injury of H9c2 cardiomyocytes by down-regulating miR-155-5p,and its mechanism may be related to the activation of SIRT1-AMPK pathway.

The mesencephalic astrocyte-derived neurotrophic factor (MANF) has been recently identified as a neurotrophic factor, but its role in hepatic fibrosis is unknown. Here, we found that MANF was upregulated in the fibrotic liver tissues of the patients with chronic liver diseases and of mice treated with CCl₄. MANF deficiency in either hepatocytes or hepatic mono-macrophages, particularly in hepatic mono-macrophages, clearly exacerbated hepatic fibrosis. Myeloid-specific MANF knockout increased the population of hepatic Ly6C^high macrophages and promoted HSCs activation. Furthermore, MANF-sufficient macrophages (from WT mice) transfusion ameliorated CCl₄-induced hepatic fibrosis in myeloid cells-specific MANF knockout (MKO) mice. Mechanistically, MANF interacted with S100A8 to competitively block S100A8/A9 heterodimer formation and inhibited S100A8/A9-mediated TLR4-NF-κB signal activation. Pharmacologically, systemic administration of recombinant human MANF significantly alleviated CCl₄-induced hepatic fibrosis in both WT and hepatocytes-specific MANF knockout (HKO) mice. This study reveals a mechanism by which MANF targets S100A8/A9-TLR4 as a "brake" on the upstream of NF-κB pathway, which exerts an impact on macrophage differentiation and shed light on hepatic fibrosis treatment.

Objective:To investigate the current status of health checkups and the management willingness of post-test abnormal values in residents of mega communities, and to explore the factors affecting the demand for health management of abnormal values after examination.Methods:A cross-sectional study. The residents of Huaguoyuan Community in Guiyang City were enrolled as the objects of this surveywith stratified systematic sampling method and questionnaire survey. The binary logistic regression was used to analyze the influencing factors of health management demand for abnormal values after examination.Results:There were 404 residents participating in this survey, and 182 cases were male (45.05%) and 222 cases were female (54.95%); the mean age was (39.64±15.03) years. There were 179 (44.31%) urban residents and 225 (55.69%) rural residents. There were 162 (40.10%) floating population and 242 (59.90%) non-floating population. Of the residents, 34.2% participated in the physical examination independently due to physical reasons. The age ( χ 2=16.227), household registration ( χ 2=16.117) and occupation ( χ 2=36.454) had statistically significant differences in residents′ participation in physical examination; the household registration ( χ 2=18.726, P<0.001) and occupation ( χ 2=18.094, P=0.034) had significant differences in the handling methods of abnormal values of physical examination. The age ( OR=7.00, P=0.032) and income ( OR=0.33, P=0.047) were the influencing factors of health management needs of abnormal values after health checkup. Conclusion:The awareness of active physical examination of residents in mega community is weak, and it is recommended to strengthen health education and health promotion; residents have a high willingness to the management of abnormal values after health checkup, it can be an important supplement to improve the service quality of physical examination related institutions.