Objectives:To explore the spatial distribution characteristics, trend changes, and spatial clustering of esophageal cancer among residents in China at the county (city, district) scale, a spatial epidemiological approach was used, with the aim of providing localized evidence for the prevention and treatment of esophageal cancer in China.Methods:The data source was the incidence (crude rate) and mortality (crude rate) of esophageal cancer from 2005 to 2016 in the 2008-2019 edition of China Cancer Registration Annual Report published by the National Cancer Center. The Joinpoint model was used for time trend analysis. The tumor registration area in 2016 was selected as the study area for spatial feature analysis, with a total of 487 counties (cities and districts), covering 27.6% of the national population. Spatial autocorrelation analysis was performed to reveal spatial distribution characteristics by using Arcgis 10.6 software, and spatial scanning statistics was used to analyze spatial clustering characteristics by using SaTScan 9.5 software. The log-likelihood ratio ( LLR) and relative risk ( RR) were calculated in different windows, and the region with the largest LLR value represented the most likely cluster. Results:From 2005 to 2016, the incidence and mortality rate of esophageal cancer in China showed a trend of increasing at first and then decreasing. The incidence and mortality rate of esophageal cancer in 2016 were characterized by spatial positive correlation. High incidence and high mortality were mainly concentrated in the areas through which the Huaihe River flowed. The primary clusters (taking high incidence rate as an example LLR=6 374.41, RR=2.37, P＜0.001) were mainly distributed in Jiangsu, Anhui and Shandong in eastern China and eastern Henan and southern Hebei in central China, and secondary clusters (taking high incidence rate as an example LLR=1 971.19, RR=1.91, P＜0.001) in Gansu, Ningxia Hui Autonomous Region, Shaanxi, Sichuan and other central and western regions. Conclusions:The incidence and mortality of esophageal cancer in China have decreased since 2010. The disease burden of esophageal cancer has obvious spatial differences, and measures should be taken according to local conditions in high-risk cluster areas such as the Huaihe River basin.

Objectives:To explore the spatial distribution characteristics, trend changes, and spatial clustering of esophageal cancer among residents in China at the county (city, district) scale, a spatial epidemiological approach was used, with the aim of providing localized evidence for the prevention and treatment of esophageal cancer in China.Methods:The data source was the incidence (crude rate) and mortality (crude rate) of esophageal cancer from 2005 to 2016 in the 2008-2019 edition of China Cancer Registration Annual Report published by the National Cancer Center. The Joinpoint model was used for time trend analysis. The tumor registration area in 2016 was selected as the study area for spatial feature analysis, with a total of 487 counties (cities and districts), covering 27.6% of the national population. Spatial autocorrelation analysis was performed to reveal spatial distribution characteristics by using Arcgis 10.6 software, and spatial scanning statistics was used to analyze spatial clustering characteristics by using SaTScan 9.5 software. The log-likelihood ratio ( LLR) and relative risk ( RR) were calculated in different windows, and the region with the largest LLR value represented the most likely cluster. Results:From 2005 to 2016, the incidence and mortality rate of esophageal cancer in China showed a trend of increasing at first and then decreasing. The incidence and mortality rate of esophageal cancer in 2016 were characterized by spatial positive correlation. High incidence and high mortality were mainly concentrated in the areas through which the Huaihe River flowed. The primary clusters (taking high incidence rate as an example LLR=6 374.41, RR=2.37, P＜0.001) were mainly distributed in Jiangsu, Anhui and Shandong in eastern China and eastern Henan and southern Hebei in central China, and secondary clusters (taking high incidence rate as an example LLR=1 971.19, RR=1.91, P＜0.001) in Gansu, Ningxia Hui Autonomous Region, Shaanxi, Sichuan and other central and western regions. Conclusions:The incidence and mortality of esophageal cancer in China have decreased since 2010. The disease burden of esophageal cancer has obvious spatial differences, and measures should be taken according to local conditions in high-risk cluster areas such as the Huaihe River basin.

Objective: To further observe the efficacy of combined transplantation of islet and bone marrow mesenchymal stem cells (BMSC) in diabetic rats, PET-CT was used to trace cells in vivo to determine the homing and distribution of cells in vivo. Methods: Streptozotocin (STZ)was used to construct a rat model of diabetes mellitus. BMSC could be isolated and cultured by full adherence method; islets were isolated by collagenase; Islets and BMSC were labeled with 18F-FDG in vitro. Diabetic rats were randomly divided into 4 groups, 15 rats in each group: A, Control group; B, Stem cell transplantation group; C, Islet Transplantation group; D, Combined transplantation group, a total of four groups, all transplanted through portal vein, PET-CT tracing the distribution of cells transplanted into the body.7 days after transplantation, the livers of each group were taken, and the homing and distribution of transplanted cells were detected by immunofluorescent staining.The SUV was calculated by the analysis of variance of random block, and the difference between groups was compared by t-test. Results: PET-CT results showed that BMSC were mainly distributed uniformly in the right liver, and the islets of the pancreas were mainly clustered in terminal branches of hepatic portal vein, and BMSC were around the islets of pancreas, but there was no obvious development in the liver of the control group. Conclusions PET-CT can directly reveal the distribution of islets and BMSC in liver after transplantation through portal vein.