Objective To investigate the associations of single nucleotide polymorphism of ( SNP ) of rs77418916 and rs8108402 in miR-181 with the risk of systemic lupus erythematosus ( SLE) in the Chinese population of Guangxi. Methods The lymphocyte sub-sets were analyzed by flow cytometry. The SNPs of miR-181 gene were detected by single nucleotide primer extension assay with SNaP-shot and DNA sequencing method. The relative expressions of miR-181a and miR-181c in mononuclear cells were detected by real time RT-quantitative PCR. Results The polymorphism of rs8108402 locus contained CC, CT and TT genotypes. The frequencies of CT and TT genotypes as well as the dominant and recessive model were different significantly between SLE group and control group ( CT vs CC:OR=1.50, 95％CI:1.03 to 2.19, P=0.033; TT vs CC: OR=2.65, 95％CI: 1.18 to 5.98, P=0.019; CC/CT vs TT: OR=2.23, 95％CI:1.01 to 4.93, P=0.048;TT/CT vs CC:OR=1.61, 95％CI:1.12 to 2.31, P=0.010) . The polymorphism of rs77418916 locus contain AA, AT and TT genotypes, but no association between rs77418916 polymorphism and susceptibility of SLE was found. The rel-ative expressions of miR-181a and miR-181c genes in SLE group were down-regulated compared with control group ( Z=-3. 22, P<0.01 and Z=-3.24, P<0.01, respectively) , and the patients carrying rs8108402 CT and TT genotype showed lower level of miR-181c compared with the patients carrying CC genotype (Z=-2.51, P<0.05). The absolute numbers of CD3+, CD4+, CD8+ and NK cells were decreased significantly in SLE group compared with that of control group ( P<0.01) . Conclusion The polymorphism of miR-181c rs8108402 may associate with the susceptibility of Chinese SLE patients in Guangxi region. The risk of SLE may increase in the individ-uals caring CT or TT genotype by decreasing the expression of miR-181c gene.

Objective:To assess the effectiveness of influenza vaccine in children aged 6-72 months.Methods:The cohort study was conducted based on community child vaccination clinics in Yiwu and Yongkang counties of Zhejiang province. From October 2017 to December 2017, a total of 1 752 children aged 6-72 months were enrolled from 10 child vaccination clinics. The questionnaire survey was conducted after the written consents were obtained from the parents or legal guardians of the children. Then, a follow up was conducted for enrolle children until 30 April 2018, the influenza vaccination status and the number of influenza-like illness (ILI) cases, hospital visit due to ILI, self-medication due to ILI were observed and recorded every month. Vaccine effectiveness (VE) was estimated by using the generalized linear model (GLM) where dependent variables were the number of ILI cases, hospital visit and self-medication respectively.Results:Of the 1 752 children, 925 (52.80%) were boys and the median age was 30.00 months. The cumulative observation was 308 166 person days at the end of 2017-2018 season, with 5.27 ILI cases per 1 000 person days, 3.41 hospital visit due to ILI per 1 000 person days, 1.45 self-medication due to ILI per 1 000 person days. Of the 1 752 children, 643 received the influenza vaccination in 2017-2018 season. Compared with unvaccinated children, the VE was 23.5% against ILI case number (95% CI: 15.1%-31.1%), 19.3% against hospital visit due to ILI (95% CI: 8.2%-29.1%) and 25.8% against self-medication due to ILI (95% CI: 9.3%- 39.3%). Modeling splitting 643 children with 2017-2018 vaccination into those before and after vaccination, the influenza VE was 31.9% against ILI case number (95% CI: 12.7%-46.9%), 32.6% against hospital visit due to ILI (95% CI: 8.6%-50.3%) and 44.3% against self-medication due to ILI (95% CI: 11.9%-64.8%) in children aged 36-72 months. However, the children aged 6-35 months showed no significant VEs. For the VE analysis in children with different vaccination status, the VEs were significant if they received vaccination in both 2016-2017 season and 2017-2018 season or only in 2017-2018 seasons. The VE was not demonstrated among the children who were immunized only in 2016-2017 season. Conclusion:Influenza vaccination is moderate effective in preventing the incidence of ILI and hospital visit and self-medication in children in influenza season, the protection effect in children aged 36-72 months is better than that in children aged 6-35 months.

Objective:To assess the performance of machine learning(ML),and integrate the clinical parameters with coronary artery calcium(CAC)score of computed tomography(CT)and quantification of automated epicardial adipose tissue(EAT),so as to predict the long-term risk of myocardial infarction(MI)and cardiogenic death in asymptomatic patients.Methods:A total of 1 058 subjects with cardiovascular risk factors and without symptoms of coronary heart disease who underwent physical examination at the Fifth Medical Center of Chinese PLA General Hospital from January 2013 to October 2015 were selected as this study subjects.A long-term follow-up was conducted on them after CAC score.EAT volume and density were quantified using a fully automated deep learning method.ML extreme gradient boosting was trained by using clinical data,risk score of atherosclerotic cardiovascular disease,CAC score and automated EAT measure,and the repeated 10-fold cross validation was used to verify the model.Results:During the 8-year follow-up period,61 cases of 1 058 subjects occurred events of MI and(or)cardiac death.The area under curve(AUC)value of ML was significantly higher than that of the atherosclerotic cardiovascular disease(ASCVD)risk and the predicting events of CAC score(ML:0.82,ASCVD:0.77,CAC:0.77).Compared with ML with only clinical variable,machine learning based on ASCVD,CAC and EAT had more predictive ability for MI and cardiac death[AUC 0.82(95%CI:77-87)vs.0.78(95%CI:0.72-0.84),P=0.02].The survival rate of subjects with high ML scores had a greater decline degree with the increasing of time,therefore,the subjects with higher ML scores were more likely to experience events.Conclusion:ML,which integrated clinical and quantitative imaging variables,can provide long-term risk prediction for patients with cardiovascular risk factors.