Objective To investigate the correlation between two single nucleotide polymorphisms of the leukotriene A4 hydrolase (LTA4H) gene (rs2660845 and rs2540493) and risk of ischemic stroke in population of southern Zhejiang Province.Methods A total of 300 ischemic stroke patients and 300 healthy controls,recruited from the Department of Neurology,Third Affiliated Hospital of Wenzhou Medical University between September 2010 and June 2013,were enrolled in this study.Two single nucleotide polymorphisms of the LTA4H gene (rs2660845 and rs2540493) were analyzed by polymerase chain reaction and matrix-assisted laser desorption/ionization time of flight,respectively.Sixty-seven patients and thirty controls were randomly selected (complete randomization) and detected the serum leukotriene B4 (LTB4)concentration by ELISA method.Results There was no evidence of association between the two variants of LTA4H gene and the risk of ischemic stroke or its TOAST (Trial of Org 10 172 in acute stroke treatment)subtypes (P ＞ 0.05).Analysis of LTB4 levels revealed that there was no statistically significant difference in serum LTB4 concentration between patients (n =67) and controls (n =30; 0.991 ± 0.305 vs 1.035 ± 0.498 ; P =0.692),and no statistically significant difference in LTB4 concentration was found among the three genotypes of rs2660845 as well (AG genotype vs AA genotype vs GG genotype:0.938 ± 0.269 vs 1.038 ± 0.268 vs 1.043 ± 0.383 ; P =0.401).Conclusion The present study suggests that there is no association between the two polymorphisms in the LTA4H gene and risk of ischemic stroke in population of southern Zhejiang Province.

OBJECTIVETo establish a new method on stratification analysis when the stratification limits of confounding factors was not clear or contradictory.

METHODData on a study of diabetes mellitus in Guangdong province collected in the year of 1997 and 1998 was analyzed using cluster-stratification analysis.

RESULTSThe efficiency of stratification analysis was improved and the confounding bias was effectively controlled with information bias avoided when the clusters-stratification analysis was applied.

CONCLUSIONThe problem was logically solved using cluster analysis as an assistant stratification means.

Adult ; Age Factors ; Aged ; Bias ; China ; epidemiology ; Cluster Analysis ; Confounding Factors (Epidemiology) ; Data Interpretation, Statistical ; Diabetes Mellitus ; epidemiology ; Epidemiologic Methods ; Humans ; Middle Aged ; Multivariate Analysis ; Reproducibility of Results ; Risk Factors

[Objective] To compare the influence of first-degree relatives' cancer history on the genetic tendency of gastric and colorectal cancer. [Methods] Patients with gastric and colorectal cancer from six towns of Suzhou City were investigated by means of face-to-face survey based on the "Family History and History of Population Diseases Questionnaire"which included general conditions, family composition and cancer occurrence of all their three degree relatives. [Results] If there were first-degree relatives with history of cancer, individual risk of gastric cancer would be higher than that of colorectal cancer by 55％, with the adjusted OR (95％ CI) being 1.551 (1.021, 2.356). If there were first-degree relatives with history of digestive tract cancer, the risk of the subject would increase to 104％, with the adjusted OR (95％CI) being 2.037 (1.279, 3.246). Men with first-degree relatives who had cancer history was at91％ higher risk of developing gastric cancer than colorectal cancer, with the adjusted OR (95％CI) being1.911 (1.080, 3.381). And for history of digestive tract cancer, the risk would reach 156％, with the adjusted OR (95％ CI) being 2.559 (1.337, 4.897). The number of cancers suffered by first-degree relatives of those patients with gastric cancer was higher than that of patients with colorectal cancer, with Z =-6.873, P<0.001, while the number of digestive tract cancer was also higher, with Z =-6.137, P<0.001. [Conclusion] The history of cancer and digestive tract cancer with first-degree relatives, is more common in patients with gastric cancer than with colorectal cancer. It is necessary to focus health education on men with first-degree relatives suffering from cancer or digestive tract cancer and suggest some changes in their living habits and regular medical examinations to reduce the occurrence of gastric cancer.

OBJECTIVETo determine the applicability of multiplex ligation-dependent probe amplification (MLPA) for rapid detection of aneuploidies in prenatal diagnosis.

METHODSA total of 561 prenatal samples were analyzed in parallel by MLPA and traditional karyotyping. Another 20 clinical samples with known common chromosome abnormalities were also determined by MLPA to evaluate the accuracy and reliability of MLPA. The results obtained from MLPA were compared with that from traditional karyotyping.

RESULTSThe results were available within 48 h. A total of 38 aneuploidies were identified by MLPA, including 20 cases of trisomy 21, 10 cases of trisomy 18, 1 case of trisomy 13, 4 cases of Turner syndrome, 1 case of Klinefelter syndrome, 1 case of 47, XYY trisomy and 1 case of 48,XYY, +18. MLPA was able to detect all the expected aneuploidies with 100% accuracy. The results obtained from MLPA agreed with traditional karyotyping. Among 561 prenatal samples, the results of 550 samples were concordant with those of karyotyping, and the coincidence rate of MLPA was 98.04%.

CONCLUSIONMLPA is a rapid, simple and reliable method for detection of the most common chromosome aneuploidies in prenatal diagnosis. MLPA is a valuable tool in prenatal clinical practice.

Adult ; Aneuploidy ; Chromosome Aberrations ; Chromosome Disorders ; diagnosis ; Female ; Humans ; Karyotyping ; Nucleic Acid Amplification Techniques ; Pregnancy ; Prenatal Diagnosis ; Young Adult

OBJECTIVETo investigate the germline mutations of the CHD7 gene and their roles in patients with congenital heart disease (CHD).

METHODSGenomic DNAs extracted from peripheral blood were subjected to screen mutations in CHD7 gene by denaturing high performance liquid chromatography (DHPLC) followed by DNA sequencing of aberrant peaks in 67 CHD patients and 100 healthy control. Case-control study and bioinformatic analysis were utilized to explore the potential functional roles of the variations detected.

RESULTSSeven kinds of single nucleotide substitution were detected in the CHD patients in different introns of the CHD7 gene. Among them, IVS11+ 127A to G and IVS12+ 21T to G were rare variations and the allele frequencies of both were 0.0075; while IVS2+ 34G to A, IVS4+ 39G to A, IVS12-5T to C and IVS16+ 51C to A were the single nucleotide polymorphisms and the allele frequency was 0.2635, 0.2156, 0.1505 and 0.3636 respectively. The frequency of IVS12-5T to C in the CHD group was significantly lower than that in the control group (5.42%versus 9.57%, P< 0.05). The variant of IVS14-35C to G was only detected in patients with CHD. Bioinformatic analysis showed that IVS12-5T to C might increase exon splicing ability comparing with the wild-type sequence.

CONCLUSIONThe CHD7 gene mutation may not be the main reason for sporadic congenital heart disease, whereas the single nucleotide polymorphism of IVS12-5T to C might play a protective role in the onset of this disease.

Base Sequence ; Case-Control Studies ; Child, Preschool ; DNA Helicases ; genetics ; DNA Mutational Analysis ; DNA-Binding Proteins ; genetics ; Exons ; genetics ; Gene Frequency ; Heart Diseases ; congenital ; genetics ; Humans ; Mutation ; Polymorphism, Single Nucleotide

Digital intelligent diagnostic and treatment technology refers to a novel technology which is based by associating digitalized and intelligent high-tech with modern science to form a multi-knowledge and multi-disciplinary domain; it includes three-dimensional visualization,3 D printing,molecular fluorescence imaging,mixed reality,photoacoustic imaging,artificial intelligence-radiomis and real-time multimodal image surgical navigation.It plays a significant role in precision diagnosis,preoperative planning and intraoperative navigation of diseases.The authors' team,combining digital intelligent technology with the actual vascular distribution of patients,has been committed to the realization of individualized liver segmentation,volume calculation,simulation surgery,preoperative planning,mixed reality,tumor boundary definition and real-time image fusion for navigation in liver surgery.The research results were applied clinically,and achieved anatomical,functional,and radical hepatectomy for liver tumors.

Objective To study the prevalence and distribution of mental disorders among registered and non-registered residents in Shenzhen. Methods An epidemiological survey on mental disorders were carried out in Shenzhen by stratified multi-stage randomized sampling method; 7134 respondents were assessed through face-to-face interview, using the WHO standardized version on World Mental Health (WMH) Survey Initiative of the Composite International Diagnostic Interview (CIDI3.1). Results (1)The weighting prevalence of mental disorders was 21.87%. The prevalence of non-registered residents was significantly higher than that of the registered residents (22.34% vs. 19.99% ; OR= 1.15,95%CI: 1.03-1.29; P<0.05) and the prevalence of females was significantly higher than that of males (22.68% vs. 19.67%; OR=1.20,95%CI: 1.07-1.34; P<0.05). The weighting prevalence of mood disorders, anxiety disorders and psychoses were 9.62%, 14.45% and 1.40%, respectively. (2) The weighting twelve-month incidence of mental disorders was 13.42%. The incidence of non-registered residents was significantly higher than that of the registered residents (13.80% vs. 11.90%; OR=1.19, 95%CI: 1.03-1.36; P<0.05). (3)The co-morbidity rate between mental disorders was 35.76%. (4)The prevalence and severity of mental disorders were associated with sex, household situation of registration, marital status, education, economic condition and occupation status. Conclusion Mental disorders have become common diseases and serious public health problem in Shenzhen, with non-registered residents and females deserve more attention.

Objective To determine whether early catheterization laboratory activation would reduce median door-to-balloon time in patients with ST elevation myocardial infarction (STEMI) . Methods Consecutive patients with STEMI underwent primary percutaneous coronary intervention (PCI) from January 2006 to December 2008 in Beijing Anzhen Hospital were analyzed. Patients were divided into three groups. Group A included patients without prehospital ECG (n = 168) , group B included patients with prehospital ECG (n = 224) and group C included patients with prehospital ECG and early telephonic notification to activate catheterization laboratory (n = 114). Primary end point was door-to-balloon time, secondary end points included peak Troponin I elevation, left ventricular ejection fraction, length of hospital stay, hospital mortality and 30 days follow-up mortality. Results Baseline characteristics were similar among groups. Door-to-balloon time and door-to-catheter laboratory time (110 minutes, 94 minutes and 85 minutes, respectively, all P <0. 01; 91 minutes, 74 minutes and 64 minutes, respectively, all P < 0. 01) were significantly shorter in group B and C than those in group A. The percentage of patients with door-to-balloon time less than 90 minutes increased significantly from 32% in group A to 43% in group B and 59% in group C ( P < 0. 01). Conclusion Early activation of catheterization laboratory by prehospital ECG and telephonic notification could markedly reduce door-to-balloon time in patients with STEMI.

Objective To investigate the prevalence of common diseases among primary and secondary school students in Yichang City from 2019 to 2022, and to provide a scientific basis for formulating effective intervention measures in the future. Methods By random cluster sampling , 7 schools in urban areas and 5 schools in suburban counties were selected to screen common diseases such as myopia, dental caries, obesity and abnormal spinal curvature. Descriptive epidemiological methods were employed for statistical analysis. Results A total of 17 023 primary and secondary school students were screened from 2019 to 2022. The overall detection rate of common diseases from high to low was myopia (54.12%), caries (36.75%), overweight (15.17%), obesity (11.88%), malnutrition (5.80%), and abnormal spinal curvature (3.49%). The detection rates of myopia and abnormal curvature of the spine showed an increasing trend with years and school stages, while the detection rates of malnutrition and dental caries showed a decreasing trend with years and school stages. The detection rates of overweight and obesity showed no trend difference with years, and the detection rates of obesity showed a decreasing trend with school stages. The rates of myopia, overweight and obesity were higher in urban areas than those in suburban counties, and the rate of dental caries was higher in suburban counties than that in urban areas. The prevalence of overweight, obesity, and malnutrition in boys was higher than that in girls. The prevalence of myopia and dental caries in girls was higher than that in boys. The above differences were statistically significant (all P<0.05). Conclusion Myopia, dental caries, obesity, and abnormal curvature of the spine are the current focus of the prevention and treatment of common diseases in students. There are great differences between different regions, school stages, and genders. The ^“tripartite linkage^” of schools, families, and communities should be achieved with the joint efforts of the education and health departments to actively take targeted intervention measures to reduce the prevalence.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.