Objective:To investigate the application value of combined detection of urine genes Twist1,Onecut2,VIM methyl-ation and folate metabolism related genes MTHFR(C677T/A1298C),MTRR(A66G)polymorphisms in the screening and diagnosis of bladder cancer.Methods:A total of 134 patients with primary bladder cancer admitted to the Department of Urology of Qingyang Peo-ple's Hospital and the Second Hospital of Lanzhou University from January 2023 to January 2024 were selected(bladder cancer group),and a total of 130 patients with common benign urinary system diseases and other malignant tumors of urinary system treated with cystoscopy were admitted during the same period(control group).Methylation-specific polymerase chain reaction was used to de-tect the methylation of Twist1,Onecut2 and VIM genes in urine shed cells.PCR fluorescence probe fusion was used to detect the poly-morphism of folate metabolism-related genes in peripheral blood of patients,and collected the clinical data and immunological indica-tors,and to all the data for statistical analysis.Results:The methylation rates of hematuria,bladder irritation,Twist1,Onecut2 and VIM genes were significantly different between two groups(P<0.05).The area under ROC curve(AUC)of Twist1,Onecut2 and VIM genes methylation and their combined detection were 0.721,0.675,0.674 and 0.772,respectively.Sensitivity and specificity were 73.20%and 71.00%,56.10%and 79.00%,48.80%and 86.00%,80.50%and 69.00%,respectively.The AUC of hematuria and blad-der irritation were 0.661 and 0.652.The sensitivity and specificity were 60.20%and 72.00%,41.50%and 89.00%,respectively.The combined AUC of all indicators were the largest(0.858),and the sensitivity and specificity were higher.The frequencies of CC,CT,TT,and T alleles of MTHFR C677T in bladder cancer group were 21.64%,41.79%,36.56%and 57.46%,respectively.Compared with the control group,the difference was statistically significant(P<0.05).The T allele frequency was significantly different between methylated and unmethylated Twist1 groups(P<0.05).Others differences were not statistically significant,and there was no signifi-cant association with gene methylation(P>0.05).Conclusion:The methylation of Twist1,Onecut2 and VIM genes are highly ex-pressed in the urine cells of patients with bladder cancer,and the combination of hematuria and bladder irritation has a high predictive value for the diagnosis of bladder cancer.The MTHFR(C677T)T allele is associated with the methylation of Twist1 gene and may be one of the risk factors for bladder cancer.

Objective To observe the value of 2D SECara-Net and 3D U2-Net models constructed based on 2D maximal intensity projection(MIP)and 3D time-of-flight MR angiography(3D TOF-MRA)images,respectively,also of their combination for MRA detecting unruptured saccular intracranial aneurysms(USIA).Methods Totally 973 patients with single USIA and 300 subjects who underwent healthy physical examination were retrospectively collected and divided into training set(n=923,containing 723 cases of USIA and 200 healthy subjects)and test set(n=350,containing 250 cases of USIA and 100 healthy subjects)at the ratio of 7:3.Pre-processed 3D TOF-MRA and the obtained 2D-MIP images in training set were imported into 3D U2-Net and 2D SECara-Net models for training and adjusting parameters,respectively.The efficiency of 2 models and their combination for detecting USIA were evaluated.Results The sensitivity,specificity and accuracy of 2D SECara-Net model for detecting USIA in test set was 78.80％(197/250),95.00％(95/100)and 83.43％(292/350),of 3D U2-Net model was 82.80％(207/250),86.00％(86/100)and 83.71％(293/350),respectively.The specificity of 2D SECara-Net model was higher than that of 3D U2-Net model(P=0.030),while no significant difference of sensitivity nor accuracy was found between 2 models(both P＞0.05).The specificity of the combination of the 2 models was 99.00％(99/100),higher than that of 3D U2-Net model(P＜0.05),and the sensitivity and accuracy of the combination was 91.20％(228/250)and 93.43％(327/350),respectivelty,both higher than those of 2 single models(all P＜0.05).Conclusion 2D SECara-Net and 3D U2-Net models had similar,sensitivity and accuracy for MRA detecting USIA.Combination of them could improve the detecting efficacy.

Objective To observe the value of 2D SECara-Net and 3D U2-Net models constructed based on 2D maximal intensity projection(MIP)and 3D time-of-flight MR angiography(3D TOF-MRA)images,respectively,also of their combination for MRA detecting unruptured saccular intracranial aneurysms(USIA).Methods Totally 973 patients with single USIA and 300 subjects who underwent healthy physical examination were retrospectively collected and divided into training set(n=923,containing 723 cases of USIA and 200 healthy subjects)and test set(n=350,containing 250 cases of USIA and 100 healthy subjects)at the ratio of 7:3.Pre-processed 3D TOF-MRA and the obtained 2D-MIP images in training set were imported into 3D U2-Net and 2D SECara-Net models for training and adjusting parameters,respectively.The efficiency of 2 models and their combination for detecting USIA were evaluated.Results The sensitivity,specificity and accuracy of 2D SECara-Net model for detecting USIA in test set was 78.80％(197/250),95.00％(95/100)and 83.43％(292/350),of 3D U2-Net model was 82.80％(207/250),86.00％(86/100)and 83.71％(293/350),respectively.The specificity of 2D SECara-Net model was higher than that of 3D U2-Net model(P=0.030),while no significant difference of sensitivity nor accuracy was found between 2 models(both P＞0.05).The specificity of the combination of the 2 models was 99.00％(99/100),higher than that of 3D U2-Net model(P＜0.05),and the sensitivity and accuracy of the combination was 91.20％(228/250)and 93.43％(327/350),respectivelty,both higher than those of 2 single models(all P＜0.05).Conclusion 2D SECara-Net and 3D U2-Net models had similar,sensitivity and accuracy for MRA detecting USIA.Combination of them could improve the detecting efficacy.

Objective:To investigate the application value of combined detection of urine genes Twist1,Onecut2,VIM methyl-ation and folate metabolism related genes MTHFR(C677T/A1298C),MTRR(A66G)polymorphisms in the screening and diagnosis of bladder cancer.Methods:A total of 134 patients with primary bladder cancer admitted to the Department of Urology of Qingyang Peo-ple's Hospital and the Second Hospital of Lanzhou University from January 2023 to January 2024 were selected(bladder cancer group),and a total of 130 patients with common benign urinary system diseases and other malignant tumors of urinary system treated with cystoscopy were admitted during the same period(control group).Methylation-specific polymerase chain reaction was used to de-tect the methylation of Twist1,Onecut2 and VIM genes in urine shed cells.PCR fluorescence probe fusion was used to detect the poly-morphism of folate metabolism-related genes in peripheral blood of patients,and collected the clinical data and immunological indica-tors,and to all the data for statistical analysis.Results:The methylation rates of hematuria,bladder irritation,Twist1,Onecut2 and VIM genes were significantly different between two groups(P<0.05).The area under ROC curve(AUC)of Twist1,Onecut2 and VIM genes methylation and their combined detection were 0.721,0.675,0.674 and 0.772,respectively.Sensitivity and specificity were 73.20%and 71.00%,56.10%and 79.00%,48.80%and 86.00%,80.50%and 69.00%,respectively.The AUC of hematuria and blad-der irritation were 0.661 and 0.652.The sensitivity and specificity were 60.20%and 72.00%,41.50%and 89.00%,respectively.The combined AUC of all indicators were the largest(0.858),and the sensitivity and specificity were higher.The frequencies of CC,CT,TT,and T alleles of MTHFR C677T in bladder cancer group were 21.64%,41.79%,36.56%and 57.46%,respectively.Compared with the control group,the difference was statistically significant(P<0.05).The T allele frequency was significantly different between methylated and unmethylated Twist1 groups(P<0.05).Others differences were not statistically significant,and there was no signifi-cant association with gene methylation(P>0.05).Conclusion:The methylation of Twist1,Onecut2 and VIM genes are highly ex-pressed in the urine cells of patients with bladder cancer,and the combination of hematuria and bladder irritation has a high predictive value for the diagnosis of bladder cancer.The MTHFR(C677T)T allele is associated with the methylation of Twist1 gene and may be one of the risk factors for bladder cancer.

Objective: To describe the prevalence and the association of sleep quality trajectory, social jetlag and comorbid symptoms of anxiety and depression among college students, in order to provide a theoretical basis for improving the comorbid symptoms of anxiety and depression in college students. Methods: A questionnaire survey was conducted among 1 135 college students from two universities in Shangrao, Jiangxi Province and Hefei, Anhui Province from April to May 2019, and were followed up once every one year for a total of three times, with a valid sample size of 1 034 individuals after matching with the baseline survey. A selfassessment questionnaire was used to investigate the social jetlag of college students, the Generalized Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire 9 (PHQ-9) were used to evaluate anxiety and depression symptoms, respectively, while the Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality. College students with GAD-7 score ≥5 and PHQ-9 score ≥5 were defined as having comorbid anxiety and depression symptoms. Latent class growth model (LCGM) was employed to analyze the sleep quality trajectory of college students, and binary Logistic regression was used to analyze the relationship between social jetlag, sleep quality trajectory and comorbid symptoms of anxiety and depression. Results: The detection rate of comorbid symptoms of anxiety and depression among college students was 16.9%, and the detection rate of social jetlag ≥2 h was 13.8%. The sleep quality showed an overall improvement trend, and the two trajectories were good sleep quality (81.6%) and poor sleep quality (18.4%). Binary Logistic regression model showed that poor sleep quality and social jetlag ≥2 h were positively correlated with comorbid symptoms of anxiety and depression (OR=5.94, 1.84, P<0.05). Conclusions Poor sleep quality and social jetlag ≥2 h in college students increase the risk of comorbid symptoms of anxiety and depression. Early screening and intervention of sleep quality and reduction of social jetlag are crucial for enhancing the mental health of college students.

Objective: To describe the prevalence and association of sleep quality and anxiety-depression co-morbid symptoms among nursing students, in order to provide a reference basis for promoting the development of nursing students mental health. Methods: Using a prospective study design, baseline survey was conducted in January 2019 among a random cluster sample of 1 716 individuals in three medical universities in Hefei, Anhui Province, and a follow-up survey was conducted in October 2019, with a valid number of 1 573 individuals after matching with the baseline survey. The Pittsburgh Sleep Quality Index (PSQI) was used to assess nursing students sleep quality, and the Depression Anxiety Stress Scale (DASS-21) to assess the anxiety-depression comorbid symptoms. Results: The detection rates of anxiety-depression co-morbidities among nursing students at baseline and follow-up survey were 16.9% and 18.2%, respectively, and the detection rates of poor sleep quality among nursing students at baseline and follow-up survey were 10.1% and 10.3%, respectively. The results of the binary Logistic regression model showed that baseline PSQI score were positively associated with the risk of anxiety-depression co-morbid symptoms among nursing students at baseline ( OR=1.49, 95%CI =1.40-1.59) and after nine months of follow-up ( OR=1.22, 95%CI =1.16-1.28). Furthermore, the influence of baseline sleep quality on the risk of anxiety-depression co-morbid symptoms were mainly concentrated in the five dimensions of sleep time, sleep efficiency, sleep disorders, hypnotic drugs and daytime dysfunction, and such effects of sleep time, sleep disorders and daytime dysfunction still existed in the follow-up investigation. Conclusion Poor sleep quality of nursing students can increase the risk of anxiety-depression co-morbidities. Improving sleep quality of nursing students has a positive effect on improving their mental health.

MicroRNA (miRNA) is a non-coding small molecule RNA, which is involved in the occu-rrence and development of tumor as an oncogene or tumor suppressor gene. The abnormal expression of many kinds of miRNAs in hepatocellular carcinoma (HCC) can directly or indirectly act on PI3K, Akt, mTOR, IGF-1R, TGF-β and other signal molecules in mTOR signal pathway, they are crucial in the appreciation, invasion and metastasis of HCC cells.