Objective: To investigate the gene mutation of telomerase reverse transcriptase (TERT) promoter in inverted urothelial lesions of the bladder and its significance in differential diagnosis. Methods: From March 2016 to February 2022, a total of 32 patients with inverted urothelial lesions diagnosed in Department of Pathology at Qingdao Chengyang People's Hospital and 24 patients at the Affiliated Hospital of Qingdao University were collected, including 7 cases of florid glandular cystitis, 13 cases of inverted urothelial papilloma, 8 cases of inverted urothelial neoplasm with low malignant potential, 17 cases of low-grade non-invasive inverted urothelial carcinoma, 5 cases of high-grade non-invasive inverted urothelial carcinoma, and 6 cases of nested subtype of urothelial carcinoma were retrospectively analyzed for their clinical data and histopathological features. TERT promoter mutations were analyzed by Sanger sequencing in all the cases. Results: No mutations in the TERT promoter were found in the florid glandular cystitis and inverted urothelial papilloma. The mutation rates of the TERT promoter in inverted urothelial neoplasm with low malignant potential, low grade non-invasive inverter urothelial carcinoma, high grade non-invasive inverted urothelial carcinoma and nested subtype urothelial carcinoma were 1/8, 8/17, 2/5 and 6/6, respectively. There was no significant difference in the mutation rate of TERT promoter among inverted urothelial neoplasm with low malignant potential, low-grade non-invasive inverted urothelial carcinoma, and high-grade non-invasive inverted urothelial carcinoma (P>0.05). All 6 cases of nested subtype of urothelial carcinoma were found to harbor the mutation, which was significantly different from inverted urothelial neoplasm with low malignant potential and non-invasive inverted urothelial carcinoma (P<0.05). In terms of mutation pattern, 13/17 of TERT promoter mutations were C228T, 4/17 were C250T. Conclusions: The morphology combined with TERT promoter mutation detection is helpful for the differential diagnosis of bladder non-invasive inverted urothelial lesions.
Humans ; Urinary Bladder Neoplasms/genetics* ; Carcinoma, Transitional Cell/pathology* ; Urinary Bladder/pathology* ; Diagnosis, Differential ; Retrospective Studies ; Mutation ; Cystitis/genetics* ; Neoplasms, Glandular and Epithelial/diagnosis* ; Papilloma/diagnosis* ; Telomerase/genetics*

Objective: To analyze the spatial distribution and identify the high risk areas of pulmonary tuberculosis at the township level in Beijing during 2005-2015. Methods: Data on pulmonary tuberculosis cases was collected from the tuberculosis information management system. Global autocorrelation analysis, local indicators of spatial association and Kulldorff's Scan Statistics were applied to map the spatial distribution and detect the space-time clusters of the pulmonary tuberculosis cases during 2005-2015. Results: Spatial analysis on the incidence of pulmonary tuberculosis at the township level demonstrated that the spatial autocorrelation was positive during the study period. The values of Moran's I ranged from 0.224 3 to 0.291 8 with all the P values less than 0.05. Hotspots were primarily distributed in 8 towns/streets as follows: Junzhuang, Wangping, Yongding and Tanzhesi in Mentougou district, Yancun in Fangshan district, Wangzuo town in Fengtai district, Tianqiao street in Xicheng district and Tianzhu town in Shunyi district. Spatiotemporal clusters across the entire study period were identified by using Kulldorff's spatiotemporal scan statistic. The primary cluster was located in Chaoyang and Shunyi districts, including 17 towns/streets, as follows: Cuigezhuang, Maizidian, Dongfeng, Taiyanggong, Zuojiazhuang, Hepingjie, Xiaoguan, Xiangheyuan, Dongba, Jiangtai, Wangjing, Jinzhan, Jiuxianqiao, Laiguangying, Sunhe towns/streets in Chaoyang district, Houshayu and Tianzhu town in Shunyi district, during January to December 2005. Conclusion: Incidence rates of pulmonary tuberculosis displayed spatial and temporal clusterings at the township level in Beijing during 2005-2015, with high risk areas relatively concentrated in the central and southern parts of Beijing.
Beijing ; China ; Cluster Analysis ; Humans ; Incidence ; Spatial Analysis ; Spatio-Temporal Analysis ; Tuberculosis ; Tuberculosis, Pulmonary/ethnology*