Objective To analyze the association between lifestyle and the risk of type 2 diabetes(T2D)among adult residents.Methods The data was sourced from the Shanghai Suburban Adult Cohort and Biobank.A total of 42 096 adult residents who had not developed T2D were recruited from four districts of Shanghai(Songjiang,Jiading,Minhang,and Xuhui)between 2016 and 2019.The follow-up ended on Feb 28,2023.A structured questionnaire was used to collect information on six lifestyle-related items,including smoking,alcohol consumption,BMI,waist circumference(WC),physical activity,and diet.The unhealthy lifestyle scores(UHLS)were calculated by counting the number of all the unhealthy lifestyle items,with a range of 0-6.New-onset T2D events diagnosed by physicians were obtained through the medical information system.Cox proportional hazards regression model and restricted cubic spline model were utilized to evaluate the association between unhealthy lifestyles and the risk of T2D incidence.Results About 28.1%of the participants led 4-6 unhealthy lifestyles.A total of 1 752 new T2D cases were identified during 218 513.4 person-years of follow-up.Analysis of single unhealthy lifestyle showed that abnormal WC(HR=1.5,95%CI:1.4-1.7)and abnormal BMI(HR=1.3,95%CI:1.2-1.5)were associated with an increased risk of T2D.Compared with individuals with a UHLS of 0-1,those with a UHLS of 3 and 4-6 had 30%(95%CI:1.1-1.6)and 50%(95%CI:1.2-1.8)higher risks of T2D,respectively.Each additional unhealthy lifestyle was associated with a 10%increase in T2D incidence risk(HR=1.1,95%CI:1.1-1.2).Conclusion The risk of T2D in adult residents increases with the cumulative number of unhealthy lifestyles.Adult residents with abnormal WC or BMI,or have three or more unhealthy lifestyles accumulated,will increase the risk of new-onset T2D.

Objective·To analyze the clinicopathologic characteristics,gene mutation profile,and prognostic factors of patients with adrenal diffuse large B-cell lymphoma(DLBCL).Methods·From March 2002 to December 2022,a total of 105 patients with adrenal DLBCL admitted to Ruijin Hospital,Shanghai Jiao Tong University School of Medicine were retrospectively analyzed for their clinicopathological data,survival outcomes,and prognostic factors.Patients'gene mutation profiles were evaluated by targeted sequencing of 152 lymphoma-related genes.Results·The median age of the patients was 62(15?82)years and the male-to-female ratio was 2.3∶1.Among them,63 patients(60.0%)were over 60 years old,22 patients(21.0%)had an Eastern Cooperative Oncology Group(ECOG)performance status of two or higher,87 patients(82.9%)were staged Ann Arbor Ⅲ?Ⅳ,92 patients(87.6%)had elevated serum lactate dehydrogenase(LDH)levels(above the upper limit of reference),84 patients(80.0%)had extranodal invasion in at least two organs,67 patients(63.8%)were of non-germinal center B-cell(non-GCB)origin,and 95 patients(90.5%)had an international prognosis index(IPI)scored over 2.With a median follow-up of 28.3(0.7?191.9)months,the estimated 2-year overall survival(OS)rate and progression-free survival(PFS)rate were 68.3%and 53.1%,respectively.The estimated 5-year OS rate and PFS rate were 52.6%and 44.0%,respectively.Among 93 patients who could be evaluated for clinical outcomes,62(66.7%)got a complete response(CR).Univariate analysis and multivariate Cox analysis revealed that age over 60 years was an adverse prognostic factor for PFS,and ECOG performance status of two or higher was an adverse prognostic factor for both OS and PFS.Targeted gene sequencing in 46 adrenal diffuse DLBCL patients showed high mutation frequencies in lysine methyltransferase 2D(KMT2D;n=17,37%),Pim-1 proto-oncogene,serine/threonine kinase(PIM1;n=17,37%),MYD88 innate immune signal transduction adaptor(MYD88;n=15,33%),CD79b molecule(CD79B;n=13,28%),and BTG anti-proliferation factor 2(BTG2;n=10,22%).Conclusion·Age over 60 years is an adverse prognostic factor for PFS,and ECOG performance status of two or higher is an adverse prognostic factor for both OS and PFS in patients with adrenal DLBCL.Patients exhibited high frequencies of KMT2D,PIM1,MYD88,CD79B,and BTG2 mutations,as well as an increased proportion of the MCD-like subtype.

Objective:To analysis the influenced factors of readmission in hospital among patients with mood disorder,construct predictive models and compare the predictive performance of the models.Methods:The electron-ic medical record data of patients with mood disorder admitted to Beijing Anding Hospital from January 2010 to De-cember 2018 were retrospectively collected.Utilizing stepwise logistic regression to analyze the related factors of re-admission in patients with mood disorder.Logistic regression,support vector machine,random forest,extreme gradi-ent boosting(XGBoost)algorithms and convolutional neural networks(CNN)were used to construct a readmission prediction model and compare the predictive performances of the different models by using the accuracy,precision,recall,et.al.Results:A total of 6 234 patients with mood disorder were enrolled,24.9％(n=1 549)patients were readmitted after discharge.The stepwise logistic regression results revealed that readmissions were more likely to occur in patients with mood disorder who were female,had comorbidities,had a treatment outcome of cure,were treated with MECT and were on second-generation antipsychotics(OR=1.26,1.68,1.26,1.35,1.18).The CNN model demonstrated the highest accuracy,precision,and F1 scores,all at 0.87,with a recall of 0.86.The random forest achieved a recall of 0.86 and an AUC of 0.95.Conclusion:Readmission of patients with mood disorder is influenced by a multitude of factors.The convolutional neural networks and random forest models outperform other models in prediction.

Objective:This study aims to analyze the trends,hotspots,and interrelations in research on retroperito-neal tumors through bibliometric methods,providing the latest scientific information support for clinicians and research-ers.Methods:Data were sourced from the SCI-expanded database of the Web of Science Core Collection,covering the period from 2004 to 2023.Statistical analysis and visualization of the number of publications,total citations,average citations per article,countries,institutions,journals,and keywords were conducted using Microsoft Excel 2019,VOS-viewer,and CiteSpace.Results:A total of 6,842 relevant articles were retrieved,with a total of 113 753 citations and an average of 16.63 citations per article.The number of publications had been increasing annually,peaking in 2022.The United States,China,and Japan are the major research countries,with the United States contributing the most.Memo-rial Sloan Kettering Cancer Center and the University of Texas MD Anderson Cancer Center are the leading research in-stitutions.The journal with the most publications was the Cureus Journal of Medical Science.Gronchi Alessandro was the most prolific author.The ain keywords were"Management","Surgery",and"Tumor",and the most cited papers focus on surgery and multicenter studies.Conclusion:Research on retroperitoneal tumors is increasing annually,with hot-spots focusing on treatment methods and prognosis analysis.The United States is the main contributor to this field,with significant international collaboration.Future research should further explore the pathogenesis of retroperitoneal tumors and more effective treatment strategies.

Depression is a highly heterogeneous psychiatric disorder with complex pathogenesis influenced by the interplay of biological,psychological,and social-environmental factors.Based on the 2021 edition of the Chinese Guidelines for the Prevention and Treatment of Depressive Disorders,which explicitly identify gender as a significant risk factor for depression onset,this paper systematically reviews the gender-differentiated pathogenesis and therapeutic advances in depression from both traditional Chinese medicine(TCM)and Western medical perspectives.In Western medicine,a large number of studies have demonstrated the sex-specific mechanism of estrogen/testosterone fluctuations and monoamine transmitter system regulation.While in TCM,although the constitution theory proposes that there are significant gender differences in congenital constitution and that qi depression and qi deficiency are associated with susceptibility to depression,current evidence primarily relies on cross-sectional surveys and lacks validation through high-quality RCTs.Compared with Western medicine,the direct research on gender-differentiated antidepressant effects in TCM remains relatively underdeveloped.In future study,it may be possible to deepen and improve the research on anti-depression in TCM from the biological markers of particular constitutions in the gender dimension.This paper advocates establishing a bio-psycho-social integrated intervention model,advancing mechanistic exploration through prospective cohort studies and multi-omics technologies,and promoting precision diagnosis and treatment systems based on gender differences,and to form a three-dimensional diagnosis and treatment and research system that covers biomarkers,social role assessment,and TCM constitution identification,in order to provide a new theoretical framework and a practical pathway for the precise medical treatment of depression.

Objective:To develop and validate a prediction model for medication adherence among patients receiving allergen sublingual immunotherapy (SLIT).Methods:A prospective cross-sectional study was conducted, and a total of 288 patients who received SLIT treatment at an allergy center in the First Affiliated Hospital with Nanjing Medical University (Jiangsu Province Hospital) from December 2023 to July 2024 were assigned to the modeling group. Additionally, 122 patients from August to October 2024 were assigned to the validation group. Data of patients′ general information, medication beliefs, anxiety levels, social support, disease perception, and medication adherence were collected. Single-factor analysis and LASSO regression were utilized to identify potential predictors, and a prediction model for medication adherence was constructed using multifactorial logistic regression. A nomogram was then developed based on the model. The model′s discriminatory ability was evaluated using receiver operating characteristic curve (ROC), the area under curve (AUC), sensitivity, and specificity. The model was then validated in the validation cohort.Results:Single-factor analysis and LASSO regression identified a total of nine predictive factors. Logistic regression revealed that medical belief tendency [ OR (95% CI) =2.420 (1.116-5.248), P=0.025], the somatic control dimension in self-rating anxiety scales [ OR (95% CI)=1.404 (1.241-1.589), P<0.001], the subjective support dimension in social support assessment [ OR (95% CI)=0.784 (0.725-0.847), P<0.001], and the cognitive dimension in illness perception [ OR (95% CI)=0.725 (0.647-0.813), P<0.001] were independent predictors of medication adherence in patients undergoing SLIT. The AUC value of the model was 0.899 (95% CI=0.863-0.934) in the modeling group and 0.882 (95% CI=0.820-0.944) in the validation group, indicating good discriminatory ability. The optimal cutoff value of the model was 0.493, with a sensitivity of 81.1% and specificity of 85.7% in the modeling group, and a sensitivity of 87.3% and specificity of 82.5% in the validation group. Conclusion:The medication adherence prediction model developed in this study for patients undergoing SLIT exhibits good predictive performance and provides valuable guidance for early intervention by clinical healthcare professionals.

Objective:To analysis the influenced factors of readmission in hospital among patients with mood disorder,construct predictive models and compare the predictive performance of the models.Methods:The electron-ic medical record data of patients with mood disorder admitted to Beijing Anding Hospital from January 2010 to De-cember 2018 were retrospectively collected.Utilizing stepwise logistic regression to analyze the related factors of re-admission in patients with mood disorder.Logistic regression,support vector machine,random forest,extreme gradi-ent boosting(XGBoost)algorithms and convolutional neural networks(CNN)were used to construct a readmission prediction model and compare the predictive performances of the different models by using the accuracy,precision,recall,et.al.Results:A total of 6 234 patients with mood disorder were enrolled,24.9％(n=1 549)patients were readmitted after discharge.The stepwise logistic regression results revealed that readmissions were more likely to occur in patients with mood disorder who were female,had comorbidities,had a treatment outcome of cure,were treated with MECT and were on second-generation antipsychotics(OR=1.26,1.68,1.26,1.35,1.18).The CNN model demonstrated the highest accuracy,precision,and F1 scores,all at 0.87,with a recall of 0.86.The random forest achieved a recall of 0.86 and an AUC of 0.95.Conclusion:Readmission of patients with mood disorder is influenced by a multitude of factors.The convolutional neural networks and random forest models outperform other models in prediction.

Depression is a highly heterogeneous psychiatric disorder with complex pathogenesis influenced by the interplay of biological,psychological,and social-environmental factors.Based on the 2021 edition of the Chinese Guidelines for the Prevention and Treatment of Depressive Disorders,which explicitly identify gender as a significant risk factor for depression onset,this paper systematically reviews the gender-differentiated pathogenesis and therapeutic advances in depression from both traditional Chinese medicine(TCM)and Western medical perspectives.In Western medicine,a large number of studies have demonstrated the sex-specific mechanism of estrogen/testosterone fluctuations and monoamine transmitter system regulation.While in TCM,although the constitution theory proposes that there are significant gender differences in congenital constitution and that qi depression and qi deficiency are associated with susceptibility to depression,current evidence primarily relies on cross-sectional surveys and lacks validation through high-quality RCTs.Compared with Western medicine,the direct research on gender-differentiated antidepressant effects in TCM remains relatively underdeveloped.In future study,it may be possible to deepen and improve the research on anti-depression in TCM from the biological markers of particular constitutions in the gender dimension.This paper advocates establishing a bio-psycho-social integrated intervention model,advancing mechanistic exploration through prospective cohort studies and multi-omics technologies,and promoting precision diagnosis and treatment systems based on gender differences,and to form a three-dimensional diagnosis and treatment and research system that covers biomarkers,social role assessment,and TCM constitution identification,in order to provide a new theoretical framework and a practical pathway for the precise medical treatment of depression.

ObjectiveTo explore effect of Xianlian Jiedu prescription on the recurrence of colorectal cancer （CRC） and investigate the related mechanisms. MethodsA postoperative recurrence model was established in 25 Balb/c mice by injecting CT26 cells subcutaneously into the armpit， followed by surgical removal of 99% of the subcutaneous tumor. The mice were randomly divided into model group， low-dose Xianlian Jiedu prescription （XLJDP-L） group （6.45 g·kg^-1·d^-1）， medium-dose Xianlian Jiedu prescription （XLJDP-M） group （12.9 g·kg^-1·d^-1）， high-dose Xianlian Jiedu prescription （XLJDP-H） group （25.8 g·kg^-1·d^-1）， and 5-fluorouracil （5-FU） group （1×10^-3 g·kg^-1·d^-1）. The mice were euthanized after 14 days of continuous intervention， and recurrent tumor tissue was harvested. Hematoxylin and eosin （HE） staining was used to observe pathological and morphological changes in the recurrent tumor tissue. Immunohistochemistry （IHC） was employed to assess the expression of proliferating cell nuclear antigen （Ki67）， vascular endothelial growth factor （VEGF）， and platelet-endothelial cell adhesion molecule （CD31） in recurrent tumor tissue. The Western blot was used to detect the protein expression levels of angiopoietin-2 （ANG-2）， VEGF， phosphorylated-protein kinase B （p-Akt）， protein kinase B （Akt）， phosphorylated-phosphatidylinositol 3-kinase （p-PI3K）， and phosphatidylinositol 3-kinase （PI3K） in recurrent tumor tissue. ResultsBefore treatment， there were no statistical differences in tumor volume， tumor weight， and body mass among the XLJDP-L， XLJDP-M， and XLJDP-H groups and the 5-FU group compared to the model group， indicating model stability. After treatment， compared with those in the model group， the tumor volume and tumor weight in the XLJDP-L， XLJDP-M， and XLJDP-H groups and the 5-FU group were significantly reduced （P<0.01）， showing dose dependency. Meanwhile， there were no significant differences in body weight among the XLJDP-L， XLJDP-M， and XLJDP-H groups and the 5-FU group compared to the model group. HE staining showed that compared with that in the model group， tumor tissue in the XLJDP-L， XLJDP-M， and XLJDP-H groups and the 5-FU group had loosely arranged cells， increased intercellular spaces， small and shriveled nuclei， light staining， fewer mitotic figures and atypical nuclei， and increased necrotic areas. IHC showed that compared with those of the model group， the positive rates of Ki67， VEGF， and CD31 in the recurrent tumor tissue of the XLJDP-L， XLJDP-M， and XLJDP-H groups and the 5-FU group were significantly reduced （P<0.01） in a dose-dependent manner. Western blot results showed that compared with those of the model group， the protein expression levels of ANG-2 and VEGF in the recurrent tumor tissue of the XLJDP-L， XLJDP-M， and XLJDP-H groups and the 5-FU group were significantly downregulated （P<0.05， P<0.01）， and the p-Akt/Akt and p-PI3K/PI3K ratios were significantly decreased in a dose-dependent manner （P<0.05， P<0.01）. ConclusionXianlian Jiedu prescription significantly inhibits the recurrence of CRC in mice after subcutaneous tumor surgery. The mechanism may involve regulating the PI3K/Akt pathway and downregulating key angiogenic proteins such as ANG-2， VEGF， and CD31.