1.Advances in the application of natural orifice specimen extraction surgery in colorectal surgery
Jin GAO ; Dong TANG ; Daorong WANG ; Jiaming XU ; Zhuangzhuang LIU ; Hanjian ZHU ; Yongkun FANG ; Cheng YAN ; Qi ZHAO
International Journal of Surgery 2020;47(4):272-277
With the further development of endoscopic technology and the application of minimally invasive concept in the diagnosis and treatment of colorectal surgery diseases, the diagnosis and treatment of colorectal related diseases have undergone tremendous changes. Surgical diagnosis and treatment of colorectal diseases have achieved great results in the minimally invasive field, ranging from traditional transabdominal surgery to laparoscopic surgery, transvaginal surgery, and transvaginal specimen removal. One of the most cutting-edge surgical methods in the field of minimally invasive colorectal surgery at present, this method avoids the incision in the abdominal wall by taking specimens through the rectum and vagina, thus further minimally invasive colorectal surgery. The NOSES technology combines the advantages of traditional laparoscopic surgery with the concept of modern minimally invasive surgery. It embodies the characteristics of minimally invasive, fast track rehabilitation in surgery, functional surgery and other concepts on the basis of ensuring the operation effect. This paper mainly summarizes the relevant experience, experience and experience in the development of colorectal surgery diagnosis and treatment by carrying out the nose technology at home and abroad.
2.Release and uptake mechanisms of vesicular Ca stores.
Junsheng YANG ; Zhuangzhuang ZHAO ; Mingxue GU ; Xinghua FENG ; Haoxing XU
Protein & Cell 2019;10(1):8-19
Cells utilize calcium ions (Ca) to signal almost all aspects of cellular life, ranging from cell proliferation to cell death, in a spatially and temporally regulated manner. A key aspect of this regulation is the compartmentalization of Ca in various cytoplasmic organelles that act as intracellular Ca stores. Whereas Ca release from the large-volume Ca stores, such as the endoplasmic reticulum (ER) and Golgi apparatus, are preferred for signal transduction, Ca release from the small-volume individual vesicular stores that are dispersed throughout the cell, such as lysosomes, may be more useful in local regulation, such as membrane fusion and individualized vesicular movements. Conceivably, these two types of Ca stores may be established, maintained or refilled via distinct mechanisms. ER stores are refilled through sustained Ca influx at ER-plasma membrane (PM) membrane contact sites (MCSs). In this review, we discuss the release and refilling mechanisms of intracellular small vesicular Ca stores, with a special focus on lysosomes. Recent imaging studies of Ca release and organelle MCSs suggest that Ca exchange may occur between two types of stores, such that the small stores acquire Ca from the large stores via ER-vesicle MCSs. Hence vesicular stores like lysosomes may be viewed as secondary Ca stores in the cell.
3.A review of deep learning methods for the detection and classification of pulmonary nodules.
Qingyi ZHAO ; Ping KONG ; Jianzhong MIN ; Yanli ZHOU ; Zhuangzhuang LIANG ; Sheng CHEN ; Maoju LI
Journal of Biomedical Engineering 2019;36(6):1060-1068
Lung cancer has the highest mortality rate among all malignant tumors. The key to reducing lung cancer mortality is the accurate diagnosis of pulmonary nodules in early-stage lung cancer. Computer-aided diagnostic techniques are considered to have potential beyond human experts for accurate diagnosis of early pulmonary nodules. The detection and classification of pulmonary nodules based on deep learning technology can continuously improve the accuracy of diagnosis through self-learning, and is an important means to achieve computer-aided diagnosis. First, we systematically introduced the application of two dimension convolutional neural network (2D-CNN), three dimension convolutional neural network (3D-CNN) and faster regions convolutional neural network (Faster R-CNN) techniques in the detection of pulmonary nodules. Then we introduced the application of 2D-CNN, 3D-CNN, multi-stream multi-scale convolutional neural network (MMCNN), deep convolutional generative adversarial networks (DCGAN) and transfer learning technology in classification of pulmonary nodules. Finally, we conducted a comprehensive comparative analysis of different deep learning methods in the detection and classification of pulmonary nodules.
Deep Learning
;
Humans
;
Multiple Pulmonary Nodules
;
Neural Networks, Computer
;
Solitary Pulmonary Nodule
;
Tomography, X-Ray Computed