ObjectivesXinjiang is one of the high TB burden provinces of China. A spatial analysis was conducted using geographical information system (GIS) technology to improve the understanding of geographic variation of the pulmonary TB occurrence in Xinjiang, its predictors, and to search for targeted interventions.MethodsNumbers of reported pulmonary TB cases were collected at county/district level from TB surveillance system database. Population data were extracted from Xinjiang Statistical Yearbook (2006~2014). Spatial autocorrelation (or dependency) was assessed using global Moran’s I statistic. Anselin’s local Moran’s I and local Getis-Ord statistics were used to detect local spatial clusters. Ordinary least squares (OLS) regression, spatial lag model (SLM) and geographically-weighted regression (GWR) models were used to explore the socio-demographic predictors of pulmonary TB incidence from global and local perspectives. SPSS17.0, ArcGIS10.2.2, and GeoDA software were used for data analysis.ResultsIncidence of sputum smear positive (SS+) TB and new SS+TB showed a declining trend from 2005 to 2013. Pulmonary TB incidence showed a declining trend from 2005 to 2010 and a rising trend since 2011 mainly caused by the rising trend of sputum smear negative (SS-) TB incidence (p<0.0001). Spatial autocorrelation analysis showed the presence of positive spatial autocorrelation for pulmonary TB incidence, SS+TB incidence and SS-TB incidence from 2005 to 2013 (P <0.0001). The Anselin’s Local Moran’s I identified the “hotspots” which were consistently located in the southwest regions composed of 20 to 28 districts, and the “coldspots” which were consistently located in the north central regions consisting of 21 to 27 districts. Analysis with the Getis-Ord Gi* statistic expanded the scope of “hotspots” and “coldspots” with different intensity; 30 county/districts clustered as “hotspots”, while 47 county/districts clustered as “coldspots”. OLS regression model included the “proportion of minorities” and the “per capita GDP” as explanatory variables that explained 64% the variation in pulmonary TB incidence (adjR2 = 0.64). The SLM model improved the fit of the OLS model with a decrease in AIC value from 883 to 864, suggesting “proportion of minorities” to be the only statistically significant predictor. GWR model also improved the fitness of regression (adj R2 = 0.68, AIC = 871), which revealed that “proportion of minorities” was a strong predictor in the south central regions while “per capita GDP” was a strong predictor for the southwest regions.ConclusionThe SS+TB incidence of Xinjiang had a decreasing trend during 2005–2013, but it still remained higher than the national average in China. Spatial analysis showed significant spatial autocorrelation in pulmonary TB incidence. Cluster analysis detected two clusters—the “hotspots”, which were consistently located in the southwest regions, and the “coldspots”, which were consistently located in the north central regions. The exploration of socio-demographic predictors identified t...
ObjectivesXinjiang is one of the highest TB-burdened provinces of China. A time-series analysis was conducted to evaluate the trend, seasonality of active TB in Xinjiang, and explore the underlying mechanism of TB seasonality by comparing the seasonal variations of different subgroups.MethodsMonthly active TB cases from 2005 to 2014 in Xinjiang were analyzed by the X-12-ARIMA seasonal adjustment program. Seasonal amplitude (SA) was calculated and compared within the subgroups.ResultsA total of 277,300 confirmed active TB cases were notified from 2005 to 2014 in Xinjiang, China, with a monthly average of 2311±577. The seasonality of active TB notification was peaked in March and troughed in October, with a decreasing SA trend. The annual 77.31% SA indicated an annual mean of additional TB cases diagnosed in March as compared to October. The 0–14-year-old group had significantly higher SA than 15–44-year-old group (P<0.05). Students had the highest SA, followed by herder and migrant workers (P<0.05). The pleural TB cases had significantly higher SA than the pulmonary cases (P <0.05). Significant associations were not observed between SA and sex, ethnic group, regions, the result of sputum smear microcopy, and treatment history (P>0.05).ConclusionTB notification in Xinjiang shows an apparent seasonal variation with a peak in March and trough in October. For the underlying mechanism of TB seasonality, our results hypothesize that winter indoor crowding increases the risk of TB transmission, and seasonality was mainly influenced by the recent exogenous infection rather than the endogenous reactivation.
BackgroundThe incidence of tuberculosis (TB) remains high among Chinese Uygurs (a long-dwelling ethnic minority in Xinjiang) in China and the variants in IL-23R likely contribute to individual’s diversity in host response during infection.MethodsA hospital based one to one matched case–control study was performed to assess the role of single nucleotide polymorphisms (SNPs) and copy number variation (CNV) of IL-23R in susceptibility and clinical features of pulmonary TB in Chinese Uygurs. Thirteen SNPs in IL-23R were genotyped by multiplex SNaPshot and a CNV was analyzed using Taqman real-time PCR in 250 pairs of pulmonary TB patients and controls.ResultsThe SNP rs7518660 (OR = 4.78, 95 % CI 3.14–8.52) and the CNV in IL23R (OR = 2.75, 95 % CI 1.51–4.98) were significantly associated with susceptibility to pulmonary TB. The SNP rs11465802 (OR = 3.23, 95 % CI 1.85–5.62) was significantly associated with drug-resistance and the SNP rs1884444 (OR = 3.61, 95 % CI 1.90–6.85) was significantly related to cavitary lesion in Chinese Uygurs.ConclusionsOur study shows for the first time that SNP and CNV in IL23R were associated with susceptibility, drug resistance and cavity formation of pulmonary TB. Our findings indicate that these IL-23R polymorphisms may be considered as risk factors for active pulmonary TB and its severe clinical forms.Electronic supplementary materialThe online version of this article (doi:10.1186/s12879-015-1284-2) contains supplementary material, which is available to authorized users.
Abstract. Eosinophils exert a number of inflammatory effects through the degranulation and release of intracellular mediators, and are considered to be key effector cells in allergic disorders, including asthma. In order to investigate the regulatory effects of the natural polyphenol, resveratrol, on eosinophils derived from asthmatic individuals, the cell counting Kit-8 assay and flow cytometry analysis were used to determine cell proliferation and cell cycle progression in these cells, respectively. Cellular apoptosis was detected using annexin V-fluorescein isothiocyanate/propidium iodide double-staining. The protein expression levels of p53, p21, cyclin-dependent kinase 2 (CDK2), cyclin A, cyclin E, Bim, B-cell lymphoma (Bcl)-2 and Bcl-2-associated X protein (Bax) were measured by western blot analysis following resveratrol treatment. The results indicated that resveratrol effectively suppressed the proliferation of eosinophils from asthmatic patients in a concentration-and time-dependent manner. In addition, resveratrol was observed to arrest cell cycle progression in G 1 /S phase by increasing the protein expression levels of p53 and p21, and concurrently reducing the protein expression levels of CDK2, cyclin A and cyclin E. Furthermore, resveratrol treatment significantly induced apoptosis in eosinophils, likely through the upregulation of Bim and Bax protein expression levels and the downregulation of Bcl-2 protein expression. These findings suggested that resveratrol may be a potential agent for the treatment of asthma by decreasing the number of eosinophils.
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