Objective:To analyze the epidemiological characteristics, spatial clustering, and correlation between dental fluorosis detection rates and meteorological factors in children aged 8 - 12 years old in 37 counties (cities, districts, hereinafter referred to as counties) affected by coal-burning-borne endemic fluorosis in Guizhou Province, and to provide a scientific basis for prevention and control of the disease.Methods:Monitoring data on dental fluorosis in children aged 8 - 12 years old from 2019 to 2022 were collected from the National Health Security Information System for Endemic Diseases. Meteorological data, including annual average temperature, annual average precipitation, annual sunshine hours, and annual average relative humidity, were obtained from the Guizhou Provincial Bureau of Statistics. Descriptive epidemiology, analytical epidemiology, and spatial correlation analysis methods were used to analyze the data. Visual maps were created based on the clustering levels of annual dental fluorosis detection rates (high-high, low-low, high-low, low-high). Spatial autocorrelation and meteorological factors were used to analyze the epidemiological characteristics, spatial clustering, and the impact of meteorological factors on dental fluorosis.Results:From 2019 to 2022, a total of 3 649 161 children aged 8 - 12 in the counties affected by coal-burning-borne endemic fluorosis were monitored, and 115 793 children were diagnosed with dental fluorosis, with a detection rate of 3.17%. The detection rates were 4.73% (45 093/954 338) in 2019, 3.35% (31 424/938 445) in 2020, 2.86% (21 727/760 195) in 2021, and 1.76% (17 549/996 183) in 2022, respectively. The dental fluorosis indices were 0.09, 0.07, 0.06, and 0.03, respectively. The number of counties with detection rates > 6% was 7, 5, 5, and 0 in 2019 - 2022, respectively. Dafang County consistently had the highest detection rates, with rates of 10.06% (6 783/67 408), 10.07% (1 955/19 421), 13.54% (4 017/29 667), and 4.83% (3 284/76 206) in 2019 - 2022, respectively. The Moran's I indices for dental fluorosis detection rates were 0.45, 0.53, 0.53, and 0.53 in 2019 - 2022, with Z = 4.29, 5.07, 5.31, and 5.10, respectively ( P < 0.05), indicating global spatial autocorrelation (positive) and spatial clustering of dental fluorosis detection rates. The number of counties with "high-high" clustering of detection rates was 7, 7, 6, and 7 in 2019 - 2022, mainly concentrated in the northwestern region, including Qixingguan District, Nayong County, Dafang County, Zhijin County, and Jinsha County of Bijie City. "Low-high" clustering areas were distributed in Zhongshan District of Liupanshui City in 2019, 2020, and 2022. The detection rate of dental fluorosis was associated with local annual average temperature (°C) and annual precipitation (mm) ( r = - 0.393, - 0.337, P = 0.016, 0.041). Conclusions:From 2019 to 2022, the detection rate of dental fluorosis in children aged 8 - 12 in coal-burning-borne endemic fluorosis areas in Guizhou Province has been decreasing year by year, and it shows spatial clustering. The high clustering area is in the northwest of Guizhou Province, which should be regarded as a key prevention and control area for coal-burning-borne fluorosis in the future. At the same time, areas with lower temperatures and precipitation should also strengthen prevention and control efforts.

Objective:To analyze the epidemiological characteristics, spatial clustering, and correlation between dental fluorosis detection rates and meteorological factors in children aged 8 - 12 years old in 37 counties (cities, districts, hereinafter referred to as counties) affected by coal-burning-borne endemic fluorosis in Guizhou Province, and to provide a scientific basis for prevention and control of the disease.Methods:Monitoring data on dental fluorosis in children aged 8 - 12 years old from 2019 to 2022 were collected from the National Health Security Information System for Endemic Diseases. Meteorological data, including annual average temperature, annual average precipitation, annual sunshine hours, and annual average relative humidity, were obtained from the Guizhou Provincial Bureau of Statistics. Descriptive epidemiology, analytical epidemiology, and spatial correlation analysis methods were used to analyze the data. Visual maps were created based on the clustering levels of annual dental fluorosis detection rates (high-high, low-low, high-low, low-high). Spatial autocorrelation and meteorological factors were used to analyze the epidemiological characteristics, spatial clustering, and the impact of meteorological factors on dental fluorosis.Results:From 2019 to 2022, a total of 3 649 161 children aged 8 - 12 in the counties affected by coal-burning-borne endemic fluorosis were monitored, and 115 793 children were diagnosed with dental fluorosis, with a detection rate of 3.17%. The detection rates were 4.73% (45 093/954 338) in 2019, 3.35% (31 424/938 445) in 2020, 2.86% (21 727/760 195) in 2021, and 1.76% (17 549/996 183) in 2022, respectively. The dental fluorosis indices were 0.09, 0.07, 0.06, and 0.03, respectively. The number of counties with detection rates > 6% was 7, 5, 5, and 0 in 2019 - 2022, respectively. Dafang County consistently had the highest detection rates, with rates of 10.06% (6 783/67 408), 10.07% (1 955/19 421), 13.54% (4 017/29 667), and 4.83% (3 284/76 206) in 2019 - 2022, respectively. The Moran's I indices for dental fluorosis detection rates were 0.45, 0.53, 0.53, and 0.53 in 2019 - 2022, with Z = 4.29, 5.07, 5.31, and 5.10, respectively ( P < 0.05), indicating global spatial autocorrelation (positive) and spatial clustering of dental fluorosis detection rates. The number of counties with "high-high" clustering of detection rates was 7, 7, 6, and 7 in 2019 - 2022, mainly concentrated in the northwestern region, including Qixingguan District, Nayong County, Dafang County, Zhijin County, and Jinsha County of Bijie City. "Low-high" clustering areas were distributed in Zhongshan District of Liupanshui City in 2019, 2020, and 2022. The detection rate of dental fluorosis was associated with local annual average temperature (°C) and annual precipitation (mm) ( r = - 0.393, - 0.337, P = 0.016, 0.041). Conclusions:From 2019 to 2022, the detection rate of dental fluorosis in children aged 8 - 12 in coal-burning-borne endemic fluorosis areas in Guizhou Province has been decreasing year by year, and it shows spatial clustering. The high clustering area is in the northwest of Guizhou Province, which should be regarded as a key prevention and control area for coal-burning-borne fluorosis in the future. At the same time, areas with lower temperatures and precipitation should also strengthen prevention and control efforts.

Objective To investigate the value of DWI in the evaluation of the therapeutic effect of cyber knife in the treatment of hepatocellular carcinoma.Methods Ninety patients who were clinically diagnosed with hepatocellular carcinoma (95 lesions) in the 5th Medical Center of General Hospital of PLA from February 2011 to December 2013 were retrospectively analyzed. All 90 patients underwent pre‐treatment dynamic contrast‐enhanced MRI scans of liver. Fourty six of them underwent liver MRI scan 3 months after treatment with cyber knife, and 49 patients underwent liver MRI scans 6 months after treatment. According to the evaluation criteria of solid tumor effect, complete necrosis tumor lesions and postoperative residual active lesions were determined. The ADC values of residual active tissue lesion, necrosis lesion in tumor and normal liver were measured. Paired sample t test was used to compare the difference of ADC values of tumor necrosis lesions and normal liver tissues between 3 and 6 months after treatment and before treatment, and ROC was used to evaluate the efficacy of ADC values in predicting complete tissue necrosis after treatment. Results In the 95 lesions, 91 lesions were completely necrotic, and active tissues were found in 4 lesions after treatment. There were statistically significant differences in the ADC values of the lesions at 3 and 6 months after treatment and before treatment (P<0.05),and the ADC values of the tissues after treatment were higher than those before treatment. There was no statistically significant difference in ADC values between 3 and 6 months after treatment and before treatment in normal liver tissue (P>0.05). The area under the ROC of using ADC value to predict the complete necrosis after treatment with cyber knife was 0.767, and the ADC value was 1.23×10‐3 mm2/s as the diagnostic cutoff value. The sensitivity and specificity of the diagnosis were 76.5% and 70.6%, respectively. Conclusion ADC values can distinguish the necrotic component from the active component of hepatocellular carcinoma after treatment, and can be used to evaluate the therapeutic effect of cyber knife in hepatocellular carcinoma.

Objective: To explore the value of CT texture analysis (CTTA) in differentiating the pathological grade of urothelial carcinoma of the bladder (UCB). Methods: A total of 53 lesions from 43 patients with bladder cancer confirmed by postoperative pathology were retrospectively analyzed, including 27 cases of high-grade urothelial carcinoma (HGUC) and 26 cases of low-grade urothelial carcinoma (LGUC). All the patients took pelvic CT and enhanced scanning in the same CT scanner with same scanning parameters. Lesions on both plain and enhanced CT images were delineated on software by two radiologists to extract the corresponding volumes of interest (VOI) and then 92 parameters based on feature classes were generated. The average values of two radiologists were obtained. The difference parameters between HGUC group and LGUC group were screened by nonparametric test, and the receiver operating characteristic (ROC) was drawn. The corresponding optimal thresholds were determined and diagnostic effect was assessed. Results: Nine difference texture parameters between HGUC group and LGUC group were selected, including 5 parameters on unenhanced images, namely, skewness, root mean squared, cluster shade, zone percentage and large area high gray level emphasis. There were 4 parameters on enhanced images, namely, skewness, kurtosis, cluster shade and zone percentage. The largest area under curve of 0.840±0.058 (95% CI 0.726-0.955) was obtained from skewness generated by VOI of unenhanced images. The cut-off value of skewness was 0.186 5, which permitted the diagnosis of HGUC with sensitivity of 92.59%, specificity of 73.08%, positive predictive value of 78.13%, negative predictive value of 90.48% and accuracy of 83.02%. Conclusion CTTA can effectively distinguish between LGUC and HGUC. Skewness from unenhanced CT images had the optimal diagnostic performance.

Objective To study the characteristics and regularities of Chinese drugs preparations ADR in order to improve the rational drug use.Methods A total of 112 cases of TCM ADR reports collected in 2009～2011 which have been presented to the Guangzhou ADR Monitoring Center.Results Of the 112 cases,26 kinds of drugs were involved,quinquagenarian were the main crowd,intravenous infusion was the main route of administration,the main types of TCM ADR were lesions of skin and accessories.Conclusion Great importance should be attached to TCM ADR monitoring to promote rational drug use in the clinic.