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 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 investigate the differences in prognosis between different surgical approaches in elderly patients with advanced ovarian cancer.Methods:Based on the Surveillance, Epidemiology and End Results (SEER) database, a cohort of elderly patients with advanced ovarian cancer from 2000 to 2020 was established. Through propensity score matching, 2 094 patients were selected from those who underwent two different surgical approaches to form a matched cohort (SEER database cohort), including 1 039 patients who received cytoreductive surgery and 1 055 patients who underwent local resection. Meanwhile, 148 elderly patients with advanced ovarian cancer who were treated at the First Affiliated Hospital of Shandong First Medical University from January 2012 to January 2024 were selected (hospital cohort), among whom 85 underwent cytoreductive surgery and 63 underwent local resection. The prognostic differences among patients who underwent cytoreductive surgery and local resection in two cohorts and stratified by the International Federation of Gynecology and Obstetrics (FIGO) staging were evaluated, respectively. The relationship between the causes of death and surgical approaches in elderly patients with advanced ovarian cancer was analyzed.Results:In the SEER database cohort, the median overall survival (OS) for patients who underwent cytoreductive surgery and local resection was 37 and 40 months, respectively, with 5-year OS rates of 31.47% and 33.74%, with no statistically significant difference ( χ2=0.78, P=0.378). After stratification by FIGO staging, the median OS for patients with stage ⅢB-ⅢC who underwent cytoreductive surgery ( n=998) and local resection ( n=962) was 38 and 40 months, respectively, with no statistically significant difference ( χ2=0.20, P=0.659). For patients with stage Ⅳ, the median OS for those who underwent cytoreductive surgery ( n=41) and local resection ( n=93) was 17 and 36 months, respectively, with a statistically significant difference ( χ2=9.37, P=0.002). Among 2 094 elderly patients with advanced ovarian cancer, 1 581 had clearly identified causes of death. In patients who underwent cytoreductive surgery, the proportions of deaths due to ovarian cancer and non-ovarian cancer were 94.52% (742/785) and 5.48% (43/785), respectively. In patients who underwent local resection, the proportions of deaths due to ovarian cancer and non-ovarian cancer were 91.46% (728/796) and 8.54% (68/796), respectively. There was a statistically significant difference in the distribution of causes of death between the two surgical approaches ( χ2=5.69, P=0.017). In the hospital cohort, the median OS for patients undergoing cytoreductive surgery and local resection was 39 and 51 months, respectively, with 5-year OS rates of 22.85% and 23.81%, with a statistically significant difference ( χ2=6.71, P=0.010). After stratification by FIGO staging, the median OS for patients with stage ⅢB-ⅢC undergoing cytoreductive surgery ( n=29) and local resection ( n=26) was 50 and 51 months, respectively, with no statistically significant difference ( χ2=0.15, P=0.699) ; for patients with stage Ⅳ undergoing cytoreductive surgery ( n=56) and local resection ( n=37), the median OS was 35 and 47 months, respectively, with a statistically significant difference ( χ2=6.55, P=0.011) . Conclusions:The survival outcomes of local resection in elderly patients with advanced ovarian cancer are not inferior to those of cytoreductive surgery. For FIGO stage Ⅳ patients, the survival period following local resection is superior to that of cytoreductive surgery.

Objective To explore the influencing factors of depression risk in elderly patients with hypertension and construct and validate a nomogram prediction model.Methods A total of 869 elderly patients with hypertension were selected from national survey database of the China Health and Retirement Longitudinal Study(CHARLS)in 2018.Multivariate Logistic regression analysis was used to identify the risk factors for depression in elderly patients with hypertension,and a nomogram prediction model was constructed.The accuracy and effectiveness of the model were validated by the Hosmer-Lemeshow(H-L)goodness-of-fit test,the area under the curve(AUC)of the receiver oper-ating characteristic(ROC)curve,and the calibration curve.Results The incidence of depression in elderly patients with hypertension was 47.18％.Factors influencing the risk of depression included rural residence(OR=2.191,P＜0.05),impaired basic activities of daily living(BADL)(OR=2.338,P＜0.05),impaired instrumental activitiesofdaily living(IADL)(OR=1.674,P＜0.05),poor life satisfaction(OR=7.348,P＜0.05),fair self-rated health(OR=0.441,P＜0.05),good self-rated health(OR=0.259,P＜0.05),and sleep duration of 6 to 9 hours(OR=0.510,P＜0.05).The AUC of the ROC curve was 0.795,the slope of the calibration curve was close to 1,and the H-L goodness-of-fit test yielded x2=5.074.The validation set showed an AUC of 0.703.Conclusion The prediction model established in this study has high accuracy and discriminative ability.Healthcare professionals can take effective preventive measures based on individual patient factors.

Objective To evaluate the cost-effectiveness of toripalimab plus axitinib compared to sunitinib in the first-line treatment of advanced renal cell carcinoma patients.Methods Based on the RENOTORCH trial,constructed a partitioned survival model to evaluate the long-term costs and health outcomes of toripalimab plus axitiniband sunitinib in the first-line treatment of advanced renal cell carcinoma(RCC)patients from the Chinese healthcare system perspective.The cycle length of the model was 3weeks,simulating the total cost,quality adjusted life years(QALYs),and incremental cost-effectiveness ratio(ICUR)for patients over 25 years.The costs were derived from the average bidding price of Yaozhi database in 2023 and published literature.The health state utility values were derived from clinical trials.The discount rate was 5%,and the willingness to pay(WTP)threshold was 3 times the per capita gross domestic product(GDP)in 2022.One-way and probability sensitivity analyses were used to test the robustness of the model.Results Based on the progression free survival(PFS)evaluated by the Independent Review Committee(IRC)and Investigator(IA),the ICUR values were 239 436.39 yuan/QALY and 175 440.39 yuan/QALY,respectively,both lower than the WTP threshold.One-way sensitivity analysis showed that the health state utility values of PFS status and the price of axitinib had a significant impact on the model.Probability sensitivity analysis showed that the probability of toripalimab plus axitinib being cost-effective was 63.64%and 98.03%according to the IRC and IA assessments,respectively.Conclusion Toripalimab plus axitinib was cost-effective in the first-line treatment of advanced RCC patients.

Objective To develop a toolkit suitable for assisting community health institutions in the early identification and inter-vention of mild cognitive impairment(MCI)among older adults.Methods A literature review was conducted to construct a draft of the identification and intervention toolkit.Tools with an expert approval rate above 70%were included after expert consultation.The final version of the toolkit was developed by integrating these tools with officially recommended tools in China.Results The expert consultation yielded an authority coefficient of 0.84.The finalized toolkit included the assessment tools of Mini-Mental State Examination,Montreal Cognitive Assessment,General Practitioner Assessment of Cognition,Cognitive Abilities Screening Instrument and Clock Drawing Test,and 18 intervention measures in-cluding pharmacological treatment,cognitive training and psychological interventions,etc.Conclusion The MCI Identification-Intervention Toolkit may serve as a reference for guiding the identification and inter-vention of MCI among older adults for community health institutions.

This study investigated the types and distribution of rodents,and the infection status of eight pathogens in the high-altitude areas of western Sichuan,to provide a basis for control of rodent-borne diseases and pathogen surveillance in rodents in the area.From August to November of 2023,rodents were captured through the night method in high-altitude areas of western Sichuan.Nucleic acids were collected from the rodents'livers and lungs,and eight important pathogens were detected:Dabie bandavirus,Han-tavirus,Bartonella,Francisella tularensis,Anaplasma phagocytophilum,Rickettsia mooseri,Orientia tsutsugamushi,and Leptospira interrogans.The chi-square test was used to compare the composition ratios of rodent species and the difference in pathogen positivity rates among groups.A total of 114 rodents of nine species were captured.The dominant species in this area were Apodemus agrarius(22.81%),Apodemus chevrieri(18.42%),Niviventer confucianus(17.54%),Apodemus latronum(16.67%),and Apodemus peninsu-lae(13.16%).Other rodent species included Rattus nitidus(4.39%),Neodon irene(4.39%),Chodsigoa hypsibia(1.75%),and Nivi-venter excelsior(0.88%).Statistically significant differences in rodent species composition were observed among regions,altitudes,and habitats(χ2Region=112.358,P<0.05;χ2Altitude=96.843,P<0.05;χ2Habitat=48.842,P<0.05).The liver and lung pathogen results showed that the positivity rate of Bartonella was highest(29/114),whereas those of the other seven pathogens were 0%-4.39%.Five rodents were co-infected with two or more pathogens,and the composite positivity rate was 4.36%(5/114).Statistically significant differences in the positivity rates were observed for Leptospira interrogans among species(χ2=6.568,P=0.028)and Anaplasma phagocytophilum among habitats(χ2=7.596,P=0.027);however,no significant differences in the positivity rates of other pathogens were found among rodent species,regions,altitudes,habitats,and sexes(P>0.05).Thus,rodent species were abundant in the high-altitude areas of western Sichuan and carried a variety of pathogens.Multiple pathogens showed compound infections,among which the positivity rate of Bartonella was relatively high.The total infection rate of pathogens in living areas was relatively high,and the risk of pathogenesis to the population is greater.Therefore,rodent control and disease monitoring efforts should be strengthened.

Objective In this study,a risk prediction model for Alzheimer's disease(AD)was constructed based on Alzheimer's disease neuroimaging initiative(ADNI)database to provide a theoretical basis for a better understanding of AD,as well as to provide a reference basis for the rational allocation of health resources and the development of preventive and control strategies.Methods The ADNIMERGE,UPENNBIOMK,ADNINIGHTINGALELONG and DXSUM datasets from the ADNI database were downloaded and random forest algorithm was used for the missing values imputation.Variable screening was performed by LASSO regression.Borderline-1 SMOTE resampling was used to adjusted for intergroup balance,and the variables were incorporated into base classifiers including XGBoost,random forest,bagging,AdaBoost,and support vector machine.Enhanced integrated classifiers were then constructed based on voting and Stacking strategies.Youden index,area under curve(AUC),F-score,G-mean,accuracy,Matthews correlation coefficient(MCC)and Kappa on the validation set were used to evaluate and compare the model efficacy.Results The performance of the classifiers based on balanced data were improved for both base and enhanced integrated classifiers.The performance of stacking and voting enhanced integrated classifiers constructed based on advantageous base classifiers have better performance compared to the base classifiers.After data balancing,the XGBoost performed better in the base classifiers(AUC:0.9090,accuracy:0.9091)and voting algorithm performs better in enhanced integrated classifiers(AUC:0.9178,accuracy:0.9179).Conclusion After Borderline-1 SMOTE resampling adjusted,the performance of both base classifiers and the enhanced integrated classifiers were all improved.For balanced data,XGBoost classifier and the voting enhanced integrated classifier can effectively assist in clinical prediction of Alzheimer's disease progression.

During the 14th Five-Year Plan period, the population of China has turned into a stage of negative growth, the fertility rate gradually declined, and the infertility rate gradually increased. The most effective treatment for infertility is assisted reproductive technology (ART), which has brought hope for fertility to many patients. However, the current promotion of the utilization of ART is still fraught with many obstacles. In this context, focusing on the realistic challenges of ART on its development in China, we will take a problem-oriented approach, utilize the relevant policies of ART in foreign countries as references, and put forward policy recommendations for the further implementation of ART, such as coordinating the balanced distribution of ART resources in the region, strengthening policy safeguards for ART, enhancing the institutional functioning of professional associations in medical ethics, and standardizing the application of ART treatments.