| 1 | Abnormal expression of homeobox c6 in the atherosclerotic aorta and its effect on proliferation and migration of rat vascular smooth muscle cells显示文摘Homeobox c6(Hoxc6)affects the proliferati on,migration,and in filtration of maligna nt tumor cells;however,the effect of Hoxc6 on atherosclerosis(AS)as well as the proliferation and migration of vascular smooth muscle cells(VSMCs),which play a role in promoting AS,has not yet been well clarified.In the present study,we tested the hypothesis that Hoxc6 affects the proliferation and migration of rat VSMCs,and hence is involved in AS.The results showed that the expression of Hoxc6 mRNA and protein was higher in normal rat aortic wall than in the myocardium.Subsequently,a rat model of AS was established by high-fat feeding for 2 months.The expression of Hoxc6 mRNA and protein was increased significantly in AS lesions,while the expression of p53 protein was decreased and that of proliferating cell nuclear antigen(PCNA)was increased.Moreover,not only the proliferation and mobility of cells in normal culture were decreased,but also the proliteration was stimulated by oxidized low-density lipoproteinr which was decreased after downregulation of Hoxc6 expression in VSMCs in rat.Consecutively,the expression of PCNA protein was decreased,while that of p53 was increased.These results indicated that Hoxc6 is probably involved in AS via p53 and PCNA by affecting the proliferation and migration of VSMCs. | Xiangshu Long Ganhua You Qiang Wu Yu Zhou Fuxun Yu Yan Xiao Shiyan Deng Fang Song Jing Huang Maobo Tian | 2020 | Acta Biochimica et Biophysica Sinica2020，52，9： | 1 |
| 2 | Privacy-preserving federated learning for transportation mode prediction based on personal mobility data显示文摘Personal daily mobility trajectories/traces like Google Location Service integrates many valuable information from individuals and could benefit a lot of application scenarios,such as pandemic control and precaution,prod-uct recommendation,customized user profile analysis,traffic management in smart cities,etc.However,utilizing such personal mobility data faces many challenges since users’private information,such as home/work addresses,can be unintentionally leaked.In this work,we build an FL system for transportation mode prediction based on personal mobility data.Utilizing FL-based training scheme,all user’s data are kept in local without uploading to central nodes,providing high privacy preserving capability.At the same time,we could train accurate DNN models that is close to the centralized training performance.The resulted transportation mode prediction system serves as a prototype on user’s traffic mode classification,which could potentially benefit the transportation data analysis and help make wise decisions to manage public transportation resources. | Fuxun Yu Zirui Xu Zhuwei Qin Xiang Chen | 2022 | High-Confidence Computing2022，2，4： | 0 |
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