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Objective To investigate the regulatory roles of cysteine rich protein 1 (CRIP1) in the proliferation and metastasis of endometrial cancer (EC) cells in vitro through binding to phosphoglycerate kinase 1 (PGK1). Methods The EC tissue samples and adjacent normal tissues were collected from 20 patients admitted in the Fourth Hospital Affiliated to Medical College of Shihezi University (First Division Hospital of Xinjiang Production and Construction Corps) between February 2019 and December 2020. NCBI online database was used to analyze CRIP1 expression in EC tissues. RT-qPCR and Western blotting were also performed to test the levels of CRIP1 and PGK1 in EC cells and tissues. Subsequently, EC Ishikawa cells were divided into control group, CRIP1 interference (shRNA-CRIP1-1 and shRNA-CRIP1-2) groups and control (shRNA-NC) group, CRIP1 interference+PGK1 overexpression (shRNA-CRIP1+Ov-PGK1) group and its control (shRNA-CRIP1+Ov-NC) group. Cell viability was detected by CCK-8 assay and EdU assay. Wound healing, transwell assay, Western blotting and immunofluorescence (IF) assay were conducted to detect the proliferation and metastasis of cells. The relationship between CRIP1 and PGK1 was predicted with Biogrid platform and then verified by co-immunoprecipitation (IP) assay. Results The expression level of CRIP1 was increased in the EC tissues and cells than the normal tissues and cells (P < 0.05). CRIP1 knockdown distinctly hindered the proliferation, migration, invasion and epithelial-mesenchymal transition (EMT) of EC cells (P < 0.05). PGK1 expression was also enhanced in EC cells as compared with normal cells (P < 0.05), while CRIP1 binding to PGK1 as well as CRIP1 knockdown notably inhibited the expression of PGK1 (P < 0.05). However, overexpression of PGK1 in CRIP1 knockdown cells partially restored the malignant phenotypes of EC cells (P < 0.05). Conclusion CRIP1 deficiency significantly attenuates the proliferation, migration, invasion and EMT of EC cells, and its mechanism may be associated with its binding to PGK1.

BackgroundCancer has become a leading cause of death for Chinese children, imposing a great economic burden on society and families. Therefore, it is extremely important to understand the epidemicsizes and trends of childhood malignancies.ObjectiveTo analyze the epidemiological characteristics of childhood cancer in China from 2005 to 2015, so as to provide evidence for the formulation of prevention and control strategies and rational allocation of health resources concerning childhood cancer in China.MethodsData regarding cancer incidence and mortality in Chinese 0-14 years old children during 2008 to 2018 were collected from the Chinese Cancer Registry Annual Report. Age-standardized incidence and mortality rates were computed by dividing the number of child deaths caused by cancer by the fifth national population census (2010) and multiplying by 100 000. Joinpoint Regression Program was used to compute the annual percentage change (APC) to analyze the temporal trends of annual child cancer incidence and mortality rates.Results(1) During the period of 2005 to 2015, the median crude incidence rate and median crude mortality rate of cancer in 0-14 years old were 9.35/100 000, and 3.91/100 000, respectively. The median crude incidence and median crude mortality rate of 0-4 years old group were higher than those of 5-9 years old group and 10-14 years old group (P

The semantic segmentation network based on U-Net (U-shaped network structure) in Si3N4 ceramic bearing cylindrical roller surface defect segmentation has the problems that low accuracy of defect feature extraction and large number of model parameters. It cannot meet the segmentation accuracy requirements of different size defects. The semantic segmentation network (D-A-IU-Net-Semantic segmentation network model with embedded multi-scale defective features) with embedded multi-scale defective feature fusion module is proposed. D-A-IU-Net inherits the encoding–decoding features of U-Net semantic segmentation network in structure and has the ability to sense multi-layer defective features. To reduce the number of model parameters and the network model training time, the D-A-IU-Net network model is downsampled only three times. To address the loss of detailed semantic information during downsampling, the network adopts a depthwise separable convolution layer with stride = 2 instead of the maximum pooling layer in the coding module. The segmentation accuracy is further improved. For overcoming the low segmentation accuracy of tiny defects on Si3N4 ceramic bearing cylindrical roller surface, the Atrous Spatial Pyramid Pooling Module (ASSP module-Hollow space convolution pool pyramid) is added to the bottom of the D-A-IU-Net network model to replace the model structure at the bottom of the U-net network model. To avoid the performance degradation caused by the increasing depth of the network model, two identity blocks are added at the bottom. A dataset of Si3N4 ceramic bearing cylindrical roller surface defects is prepared for validation. The experimental results show that the mIoU (mean Intersection over Union) of the D-A-IU-Net network model reaches 90.70%, the mPA (mean Pixel Accuracy) is improved to 95.13%, and the single image prediction time is 46.53 ms. The region segmentation efficiency of Si3N4 ceramic bearing cylindrical roller surface defects is improved. [ABSTRACT FROM AUTHOR]