Dalian Medical University
3 articles published in JoVE
Generation and Characterization of Right Ventricular Myocardial Infarction Induced by Permanent Ligation of the Right Coronary Artery in Mice Ruoxi Liao1, Mingyuan He2, Donghong Hu2, Chengzheng Gong1, Huiying Du1, Hairuo Lin2, Huijun Sun3 1The First Clinical College of Dalian Medical University, 2Department of Cardiology, State Key Laboratory of Organ Failure Research, Nanfang Hospital, Southern Medical University, 3College of Pharmacy, Dalian Medical University There are several differences between the right and left ventricles. However, the pathophysiology of right ventricular infarction (RVI) has not been clarified. In the present protocol, a reproducible method for RVI mouse model generation is introduced, which may provide a means to explain the mechanism of RVI.
Skeletal Phenotype Analysis of a Conditional Stat3 Deletion Mouse Model Yiling Yang*1, Qianye Chen*2, Siru Zhou1, Xinyi Gong1, Hongyuan Xu1, Yueyang Hong1, Qinggang Dai3, Lingyong Jiang1 1Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Science, Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, National Clinical Research center of Stomatology, 2Department of Stomatology, Dalian Medical University, 3The 2nd Dental Center, Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, National Clinical Research center of Stomatology This protocol describes a canonical method to understand the critical genes controlling osteoclast activity in vivo. This method uses a transgenic mouse model and some canonical techniques to analyze skeletal phenotype.
Engineering Artificial Factors to Specifically Manipulate Alternative Splicing in Human Cells Huan-Huan Wei*1, Yuanlong Liu*1, Yang Wang2, Qianyun Lu1, Xuerong Yang1, Jiefu Li1, Zefeng Wang1 1Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences (SIBS), 2Institute of Cancer Stem Cell, Second Affiliated Hospital, Cancer Center, Dalian Medical University This report describes a bioengineering method to design and construct novel Artificial Splicing Factors (ASFs) that specifically modulate the splicing of target genes in mammalian cells. This method can be further expanded to engineer various artificial factors to manipulate other aspects of RNA metabolism.