C2005: OTUD1 Promotes AIF Nuclear Translocation and Activates Caspase-independent Apoptosis Signaling in Squamous Cell Carcinoma

The developing of 5G wireless network will further promote the biomedical big data paradigm and make the personalized and active healthcare practical. But the sharing and mining of big data still has lots of challenges. I will talk about the state-of-the-art of biomedical ontology and discuss the future integrative ontologies based data analysis and applications, introduce theories, models for the understanding of these diverse biomedical big data including genomic and phenotype data, lifestyle data and complex diseases by our researches and discuss the future developing of modern biomedical informatics, emphasizing the biomedical ontologies development and participatory medicine; evolutionary medicine ICBMS 2019 CONFERENCE ABSTRACT 9 and network robustness or vulnerability; physiological and sensor informatics; N-of-1 studies and systems health, etc. ICBMS 2019 CONFERENCE ABSTRACT 10 Keynote Speaker II Prof. Hiroshi Fujita Gifu University, Japan Prof. Hiroshi Fujita received the B.S. and M.S. degrees in electrical engineering from Gifu University, Japan, in 1976 and 1978, respectively, and Ph.D. degree from Nagoya University in 1983. He became a research associate in 1978 and an associate professor in 1986 at Gifu National College of Technology. He was a visiting researcher at the K. Rossmann Radiologic Image Laboratory, University of Chicago, in 1983-1986. He became an associate professor in 1991 and a professor in 1995 in the Faculty of Engineering, Gifu University. He has been a professor and chair of intelligent image information since 2002 at the Graduate School of Medicine, Gifu University. He is now a Research Professor of Gifu University. He is a member of the Society for Medical Image Information (Honorary President), the Institute of Electronics, Information and Communication Engineers (Fellow), its Technical Groups on Medical Image (Adviser), the Japan Society for Medical Image Engineering (Director), and some other societies such as SPIE. He has been also served as scientific committee or program committee members, such as in International Workshop on Digital Mammography (Breast Imaging), SPIE Medical Imaging, and Computer Assisted Radiology and Surgery (CARS). He was worked as a General co-chair of Asian Forum on Medical Imaging 2007 held in Cheju National University, Korea, and as a General Chair of International Workshop for Breast Imaging (IWDM2014, Gifu). He has also worked as a Guest Editor-in-Chief in Special Section Editorial Committee for Medical Imaging, issued in April, 2013, from IEICE Society in Japan, and also as a Guest Editor-in-Chief in the Special Issue on Advanced Image Technologies in Diagnostic Imaging in 2018 in the Journal of Medical Imaging and Health Informatics. His research interests include computer-aided diagnosis system, image analysis and processing, and image evaluation in medicine. He has published over 1000 papers in Journals, Proceedings, Book chapters and Scientific Magazines. Topic: "The State-of-the-art of AI-aided Diagnosis in Medical Imaging" Abstract—Computer-aided detection/diagnosis, so-called CAD, is rapidly entering the radiology mainstream. It has already become a part of the routine clinical work especially for the detection of breast cancer with mammograms, in which the computer output is used as a "second opinion" in assisting radiologists' image interpretations. Recent powerful artificial intelligence (AI) technology including deep learning advances the development and improving performance of CAD to the next stage, sometimes called as AI-CAD. In this talk, the state-of-the-art of AI-CAD and issues to be solved will be reviewed and discussed.Computer-aided detection/diagnosis, so-called CAD, is rapidly entering the radiology mainstream. It has already become a part of the routine clinical work especially for the detection of breast cancer with mammograms, in which the computer output is used as a "second opinion" in assisting radiologists' image interpretations. Recent powerful artificial intelligence (AI) technology including deep learning advances the development and improving performance of CAD to the next stage, sometimes called as AI-CAD. In this talk, the state-of-the-art of AI-CAD and issues to be solved will be reviewed and discussed. ICBMS 2019 CONFERENCE ABSTRACT 11 Keynote Speaker III Prof. Peidu Jiang University of Electronic Science and Technology of China, China Peidu Jiang received MD degree in Oncology from West China School of Medicine, Sichuan University (China) in 2011. Later, he received his second doctoral degree from Tokyo Medical and Dental University (Japan) where he studied Cell Biology. Following his doctorate, Dr. Jiang completed post-doctoral studied at the University of Tokyo (Japan) in the laboratory of Dr. Noboru Mizushima where he studied autophagy. Currently, Dr. Jiang is a Professor of Pharmacology at School of Medicine, University of Electronic Science and Technology of China. His research focuses on autophagic degradation of proteins and organelles, pathogenesis and therapeutic strategy of intracellular turnover-related diseases. Topic: "Molecular Mechanism of Autophagy and Development of its Potent Modulators" Abstract—Autophagy is a self-degradative process by which cytosolic components and organelles are delivered to the lysosome for degradation. Although over 38 autophagy-related (Atg) genes have been identified in yeast and mammalian cells, the mechanism how autophagosomes fuse with lysosomes still needs to be further elucidated. Here, we identified YKT6 as a novel autophagosomal SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) protein. Depletion of YKT6 inhibited autophagosome–lysosome fusion partially in wild-type and completely in syntaxin 17 (a known autophagosomal SNARE) KO cells, suggesting that YKT6 and syntaxin 17 are independently required for autophagosome–lysosome fusion. Autophagy plays important roles in cellular homeostasis and disease pathogenesis. For example, downregulation of autophagy is involved in numerous diseases including neurodegenerative diseases, cancer, aging, metabolic disorders, and infectious diseases. Therefore, small chemical molecules that can modulate autophagy activity may have pharmacological value for treating these autophagy-related diseases. Using a GFP-LC3-based high content screening assay, we identified a novel chemical that is able to activate autophagy at initiation stage. This molecule, termed as CPC, increases the numbers of autophagosomes and reduces the autophagy substrate p62/SQSTM1 levels by inhibiting mTOR signaling pathway.Autophagy is a self-degradative process by which cytosolic components and organelles are delivered to the lysosome for degradation. Although over 38 autophagy-related (Atg) genes have been identified in yeast and mammalian cells, the mechanism how autophagosomes fuse with lysosomes still needs to be further elucidated. Here, we identified YKT6 as a novel autophagosomal SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) protein. Depletion of YKT6 inhibited autophagosome–lysosome fusion partially in wild-type and completely in syntaxin 17 (a known autophagosomal SNARE) KO cells, suggesting that YKT6 and syntaxin 17 are independently required for autophagosome–lysosome fusion. Autophagy plays important roles in cellular homeostasis and disease pathogenesis. For example, downregulation of autophagy is involved in numerous diseases including neurodegenerative diseases, cancer, aging, metabolic disorders, and infectious diseases. Therefore, small chemical molecules that can modulate autophagy activity may have pharmacological value for treating these autophagy-related diseases. Using a GFP-LC3-based high content screening assay, we identified a novel chemical that is able to activate autophagy at initiation stage. This molecule, termed as CPC, increases the numbers of autophagosomes and reduces the autophagy substrate p62/SQSTM1 levels by inhibiting mTOR signaling pathway. ICBMS 2019 CONFERENCE ABSTRACT 12 Keynote Speaker IV Prof. Hyoungseop Kim Kyushu Institute of Technology, Japan Prof. Hyoungseop Kim received his B.A. degree in electrical engineering from Kyushu Institute of Technology in 1994, the Masters and Ph.D. degree from Kyushu Institute of Technology in 1996 and 2001, respectively. He is a professor in the department of control engineering at Kyushu Institute of Technology. His research interests are focused on medical application of image analysis. Topic: "A Computer Aided Diagnosis Method for Identification of Rheumatoid Arthritis on CR Images" Abstract—With the aging of the population in Japan, patients with osteoporosis are increasing year by year. Because there is a prediction that the number of patients will increase due to the progress of aging society in the future, counterplan is socially important. On the other hand, although diagnostic imaging is effective for osteoporosis, many symptoms similar to osteoporosis are also present. In visual screening on osteoporosis, since it is very difficult to read an enormous number of images and interpret the affected part of osteoporosis accurately from each image, much screening time are required and the burden on interpreting doctors is concerned. To solve this problem, we are working on a computer-aided diagnosis (CAD) system for osteoporosis. In this study, we propose some segmentation methods of the phalange region from the phalange CR images and classification of osteoporosis based on machine techniques. In this talk, I will introduce a CAD system and its usefulness with some experimental results.With the aging of the population in Japan, patients with osteoporosis are increasing year by year. Because there is a prediction that the number of patients will increase due to the progress of aging society in the future, counterplan is socially important. On the other hand, although diagnostic imaging is effective for osteoporos