Objective To construct a new molecular biological method for the analysis of microbial species in lower respiratory tract infections based on 16S rRNA gene by denaturing high-performance liquid chromatograph(DHPLC).Methods The universal primer set was analyzed basing on the highly conserved regions of 16S rRNA gene.DNA amplicons of lower respiratory tract were analyzed by DHPLC to generate peak profiles respectively.The incorporation of 40-bpGC clamp into the amplification primet was essential to effectively discriminate genetic differences identification.Results The primers could only amplify bacterial 16S rRNA.Bacterial of amplicons which incorporation of a 40-bpGC clamp were effectively discriminated genetic differences in DHPLC.The results of clinical isolares identification showed 100%according with the traditional method.Conclusion DHPLC has not only high accuracy,but also is a convenient,rapid and high-through technique for the discrimination bacteria.It has potential value in the detection of lower respiratory pathogenic bacteria.

Objective:To explore the correlation between glycemic control of type 2 diabetes mellitus (T2DM) patients and brachial-ankle pulse velocity (baPWV). Methods:A community-based cross-sec-tional study was conducted in Beijing, China. Every subject underwent physical examinations, glycated hemoglobin ( HbA1 c ) , blood lipid and baPWV measurements and completed a standardized question-naire. T2DM patients were divided into well controlled and poorly controlled groups according to HbA1c levels. The correlation between glycemic control of T2DM patients and baPWV was analyzed. Results:In this study, 1 341 subjects were recruited, including 733 T2DM patients and 608 non-diabetes sub-jects. Compared with non-diabetes subjects, abnormal baPWV ( baPWV≥1 700 cm/s) rate for T2DM patients was higher (40. 8% vs. 26. 8%, P<0. 001). With HbA1c<6. 5% or <7. 0% as the aim of glycemic control in T2DM patients, the abnormal baPWV rates for non-diabetes subjects, well controlled and poorly controlled T2DM patients were significantly different (non-diabetes vs. HbA1c<6. 5% T2DM vs. HbA1c≥6. 5% T2DM: 26. 8% vs. 32. 8% vs. 42. 6%, P <0. 001; non-diabetes vs. HbA1c <7. 0% T2DM vs. HbA1c≥7. 0% T2DM:26. 8% vs. 36. 1% vs. 43. 4%, P<0. 001). After being ad-justed for gender, age, smoking status, diabetes mellitus family history, T2DM duration, cardiovascular diseases ( CVD ) , waist hip ratio ( WHR ) , systolic blood pressure ( SBP ) , diastolic blood pressure ( DBP) , total triglycerides ( TG) , high density lipoprotein cholesterol ( HDL-C) , and low density lipo-protein cholesterol ( LDL-C ) , the Logistic regression models suggested that glycemic control status of T2DM patients was associated with abnormal baPWV. Compared with non-diabetes subjects, the ORs for abnormal baPWV in HbA1 c <6 . 5% T2 DM patients and HbA1 c≥6 . 5% T2 DM patients were 0 . 927 (95%CI 0. 560-1. 537) and 1. 826 (95%CI 1. 287-2. 591). Compared with non-diabetes subjects, the ORs for abnormal baPWV in HbA1c<7. 0% T2DM patients and HbA1c≥7. 0% T2DM patients were 1. 210 (95%CI 0. 808-1. 811) and 1. 898 (95%CI 1. 313-2. 745). Conclusion:The glycemic con-trol status of T2DM patients from communities is significantly associated with baPWV. Poor glycemic con-trol is a risk factor for abnormal baPWV. Keeping HbA1c under control might lower the risk of cardiovas-cular diseases in T2DM patients.

Objective: To explore the relationship between glycemic control and visceral adiposity index (VAI) among type 2 diabetes mellitus (T2DM) patients.Methods: A community-based epidemiological field study for patients with T2DM aged ≥ 40 years was conducted in China.Every participant underwent physical examinations, biochemical tests of fasting glucose, glycosylated hemoglobin (HbA1c), total cholesterol (TC), triglyceride (TG), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C) and so on, and a questionnaire, including anthropometric characteristics, lifestyle, disease history, family history, and medication use.Those participants with HbA1c ≥7.0% were classified as the poorly controlled in our analysis of relationship between glycemic control and VAI.Anthropometric characteristics, lifestyle, and biochemical indexes of the participants were compared among the groups of different VAI levels.Logistic models were applied in multiple analysis adjusting for possible confounders.Results: A total of 1 607 patients with T2DM were recruited in our analysis with a mean age of (59.4±8.1) years and an average T2DM duration of (7.0±6.4) years.Among them, 78.3% were on hypoglycemic therapy.The cutoff points of quartiles of VAI were calculated for the males and females, respectively.According to the ascending order of the quartiles of VAI, the participants were divided into four groups, i.e.Q1, Q2, Q3, and Q4.The poor glycemic control rate for these groups were 60.6%, 65.7%, 70.1%, and 71.0%, respectively (Trend χ2=12.20, P<0.001).After adjustment for age, gender, systolic blood pressure (SBP), diastolic blood pressure (DBP), LDL-C, smoking, cardio-cerebral vascular disease (CVD) history, hypoglycemic therapy, T2DM duration, and family history of diabetes, the Logistic regression models showed that the glycemic control rate was significantly associated with VAI levels among the patients with T2DM.Compared with the participants in group Q1, the ORs of poor glycemic control for those in groups Q2, Q3, and Q4 were 1.239 (95%CI 0.918 to 1.672), 1.513 (95%CI 1.117 to 2.050), and 1.535 (95%CI 1.128to 2.088), respectively (trend P=0.003).With each quartile increase in VAI, the OR of poor glycemic control was 1.162 (95%CI 1.054 to 1.282).Conclusion: The glycemic control among the patients with T2DM is significantly associated with VAI.High level of VAI is an indicator of poor glycemic control.

Objective To explore the relationship between type 2 diabetes mellitus(T2DM)and serum stromal cell derived factor-1(SDF-1)levels. Methods A community-based epidemiological field study for T2DM patients and non-T2DM subjects was conducted in Beijing,China. Every subject underwent physical examinations, biochemical tests of stromal cell derived factor 1 and so on,and completed a standardized questionnaire. A total of 756 subjects were recruited in our analysis ,including 267 T2DM patients and 489 non-T2DM subjects ,T2DM patients were further divided into 81 simple T2DM patients and 186 macrovascular complication patients on the basis of the status of macrovascular complication. The correlation between serum SDF-1 levels and T2DM was analyzed. Results Compared with non-T2DM group,the level of SDF-1 in T2DM group was higher(P=0.019). The level of SDF-1 in simple T2DM group was also higher than macrovascular complication group(P=0.044). In the multi-ple linear regression analysis,after adjustment for age,gender,smoking,drinking,dyslipidemia,hypertension and BMI,SDF-1 level in simple T2DM group was higher than macrovascular complication group(P = 0.049), still. Conclusions Simple T2DM patients had a higher serum SDF-1 level than T2DM patients with macrovascular complications as well as those who did not suffer T2DM,suggesting that the stromal cell derived factor-1 may play a certain role in the development of T2DM and macrovascular complications.

Objective: To identify post-marketing active surveillance systems for vaccine safety around the world and understand their features and mechanisms, in order to provide guidance for vaccine administration activities in China. Methods: Following the steps of scoping review, literature about active surveillance system for vaccine safety and published by 30 June 2018 were identified by searching electronic databases, including PubMed, Scopus, and Cochrane Library. Grey literature were also sought by exploring relevant websites. Identified literature were screened according to eligibility criteria, and informative data from included literature were then charted. Framework Synthesis and Thematic Analysis were performed to integrate the charted data. Results: 97 pieces of literature were included for review, and 11 active surveillance systems for vaccine safety were identified, mostly located in developed countries. These systems were constructed by 3 types of organizations: administration departments, academic or research institutions, and health care providers. Their data sources included immunization registries, electronic medical records, claims data, case reports of adverse events following immunization electronic questionnaires, and epidemiologic study data. According to their operation procedures, these systems were grouped into 4 modes of active surveillance: Data Linkage, Investigator Network, Automatic Follow-up System, Studies Consortium. Conclusion Practice of active surveillance for vaccine safety greatly varies across countries, with different conditions and advantages. It is suggested that developing countries should choose suitable mode of active surveillance considering their local situations.