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 analyze the key β-amyloid protein (Aβ) deposition in brain regions affecting the progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD).Methods:Based on the positron emission tomography data of Aβ in the Alzheimer's disease neuroimaging initiative database, the penalized generalized estimating equation (PGEE) and the mixed effects regression forest algorithm (MERF) were used to conduct dimensionality reduction analysis on 164 brain regions with Aβ deposition. Additionally, a multivariate longitudinal data joint model was used to screen the key Aβ deposition brain regions that influence the progression from MCI to AD.Results:Five key brain regions were commonly screened out by the PGEE and MERF models, they were the right prefrontal orbital cortex, the left superior temporal sulcus shore cortex, the right medial orbitofrontal cortex, the left putamen, and the right transverse temporal cortex, respectively. The results of the multivariate longitudinal data joint model based on these 5 Aβ deposition brain regions showed that, except the left superior temporal sulcus shore cortex, the longitudinal change trajectories of the other 4 Aβ deposition brain regions all affected the progression from MCI to AD ( P<0.05). Conclusion:The Aβ deposition in the right prefrontal orbital cortex, right medial orbitofrontal cortex, left putamen and right transverse temporal cortex affect the progression from MCI to AD.

Objective:To identify circulating proteins associated with cardiovascular, renal, and cardiorenal comorbidity events in individuals with metabolic syndrome, to construct a predictive model incorporating these proteins to improve prediction accuracy and to investigate their mediating effects on the interplay between cardiovascular and renal diseases.Methods:Data from the UK Biobank cohort were utilized. Cox proportional hazards models were applied to identify circulating proteins associated with various outcomes, followed by time-truncated sensitivity analyses. A predictive model incorporating protein scores was then developed using the LightGBM algorithm and compared with other models. Gene Ontology(GO) functional enrichment analysis was performed to explore the biological pathways of the identified proteins. Finally, mediation effect analysis was conducted to assess the role of circulating proteins in cardiorenal interactions. Results:The Cox analysis identified 180, 275, and 322 circulating proteins associated with cardiovascular events, renal events, and cardiorenal comorbidity events, respectively. Incorporating protein scores significantly improved model performance; the areas under the curve(AUC) for cardiovascular, renal, and cardiorenal events were 0.833, 0.907, and 0.890, respectively. GO functional enrichment analysis demonstrated significant enrichment in pathways such as cytokine activity(GO: 0005125), glycosaminoglycan binding(GO: 0005539), and humoral immune response(GO: 0006959) among all outcome-related proteins. Notably, EDA2R, GDF15, and WFDC2 exhibited significant mediating effects, each with mediation proportions exceeding 10%. Conclusions:A predictive model incorporating circulating protein scores can substantially improve prediction accuracy for cardiovascular and renal outcomes in individuls with metabolic syndrome.

Objective:To analyze the situation of rodents carrying Hantavirus and the genetic and evolutionary characteristics of the virus in Zibo city, Shandong province in 2022, and provide reference for the scientific prevention and control of hemorrhagic fever with renal syndrome (HFRS).Methods:Real-time quantitative PCR (RT-qPCR) was used to detect hantavirus (HV) nucleic acids in rodent lung tissues and identify HV genotypes. Each nucleic acid fragment was designed to amplify various gene fragments by segment, and the whole genome of Hantavirus was sequenced by second generation sequencing. Sequence assembly was performed using SeqMan 7.1.0.44, a subprogram of DNAStar. Sequence alignment and evolutionary analysis were conducted using MEGA 7.0 and BioEdit software.Results:A total of 270 host animals were captured in this survey. Among them, 13 rodent lung samples tested positive for Hantavirus, resulting in a virus-positive rate of 4.8%. The full-genome sequences of four hantavirus strains were successfully obtained, all identified as Seoul virus (SEOV) genotype. Four Hantavirus-positive samples showed high nucleotide sequence homology in the M gene and belonged to the SEOV S3 subtype. These strains exhibited high similarity with those from Hebei, Liaoning, and Beijing. The amino acid sequences of the nucleoprotein and glycoprotein immunogenic epitopes were identical to those of the vaccine strain Z37.Conclusions:This study successfully determined the full genome sequences of four hantavirus strains from Zibo city, Shandong province. The genotypes are primarily SEOV, with the subtype being S3. The homology of genes within the same subtype is high, with no significant variations observed. The alignment of immune epitopes in key proteins suggests that the current vaccine may provide protection against locally circulating strains, but further in-depth research is still required.

Objective:To explore the association between greenspace morphology and the risk of severe fever with thrombocytopenia syndrome (SFTS) in Shandong Province.Methods:The SFTS cases data and land use data in Shandong province from 2018 to 2022 were collected, 6 landscape indices were calculated through Fragstats 4.2 software, and a negative binomial regression model was used to quantitatively evaluate the effect. Meteorological and socioeconomic factors during the same period were controlled as covariates. Subgroup analysis were conducted by age, gender and occupation. The percentage of relative risk[(RR-1)×100%] with 95% confidence interval (95% CI) was used as effect estimates. Results:There was a significant association between greenspace morphology and the risk of SFTS. Every 1% increase in the percentage, the mean area, fragmentation, aggregation, connectedness, and complexity of the shape of greenspace will lead to an increase in the risk of SFTS by 4.28% (95% CI: 2.88%-5.68%), 3.56% (95% CI: 1.06%-6.12%), 2.43% (95% CI: 1.38%-3.61%), 2.22% (95% CI: 1.39%-3.11%), 0.41% (95% CI: 0.26%-0.56%), 0.26% (95% CI: 0.10%-0.41%), respectively. There were statistically significant differences in the association between greenspace morphology and the risk of SFTS among different age and occupational subgroups. The elderly and farmers were the more susceptible to the changes in the percentage of greenspace and the complexity of the shape of greenspace. Conclusions:Greenspace morphology is related to the risk of SFTS. The elderly and farmers are vulnerable populations.

Objective:To investigate the current status and related factors of antiviral treatment for chronic hepatitis B virus (HBV) infection in rural communities in China.Methods:In 2023, 866 chronic HBV-infected individuals from rural communities in Zhangqiu District, Jinan City, were included in the study. Basic information, disease status and antiviral treatment conditions of the infected individuals were collected through questionnaires, specimen collection and laboratory tests. Univariate and multivariate logistic regression were used to analyze the related factors of the antiviral treatment rate of those who met the indications for hepatitis B antiviral treatment.Results:The median age ( Q1, Q3) of subjects was 56 (48, 66) years old, among which 436 (50.4%) were males. There were 712 (82.2%) individuals who met the indications for hepatitis B antiviral treatment, and 110 individuals received antiviral treatment with a rate of 15.5%. Multivariate logistic regression analysis showed that compared with males, families with an average monthly income per capita of <1 000 yuan, no alcohol consumption, no smoking, and a family history of HBV infection, females ( OR=4.66, 95% CI: 2.88-7.53), families with an average monthly income per capita of 1 000-1 999 yuan ( OR=1.64, 95% CI: 1.00-2.68) and ≥2 000 yuan ( OR=2.78, 95% CI: 1.54-5.03), alcohol consumption ( OR=6.42, 95% CI: 2.80-14.7), smoking ( OR=1.98, 95% CI: 1.04-3.77), and no family history of HBV infection ( OR=1.90, 95% CI: 1.16-3.09) had a lower antiviral treatment rate for chronic HBV infection. Conclusion:The antiviral treatment rate of chronic HBV-infected individuals in rural communities of Zhangqiu District, Jinan City is low, and the related factors are female, high monthly income per capita, alcohol consumption, smoking, and no family history of HBV infection.

Rhinovirus (RV) has been reported as one of the main viral causes of human respiratory infections and has received increasing attention in recent years due to its strong association with various respiratory diseases. Studies have shown that RV not only causes the common cold but also plays a critical role in lower respiratory tract conditions such as bronchiolitis, pneumonia, and asthma. Notably, RV is implicated in both the onset and exacerbation of asthma. This review systematically summarizes a wide range of RV-associated respiratory diseases in the available literature. Although there are currently no specific antiviral therapies or vaccines targeting RV, advances in the development of polyvalent vaccines and antiviral drugs provide promising directions for future prevention and treatment. Clarifying the relationship between RV and diseases will provide strong support for optimizing treatment strategies and preventing and controlling respiratory diseases.

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.