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您的检索式：作者名="Yiqun Dang"
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| 1 | A genetically engineered Escherichia coli that senses and degrades tetracycline antibiotic residue显示文摘Due to the abuse of antibiotics,antibiotic residues can be detected in both natural environment and various industrial products,posing threat to the environment and human health.Here we describe the design and implementation of an engineered Escherichia coli capable of degrading tetracycline(Tc)-one of the commonly used antibiotics once on humans and now on poultry,cattle and fisheries.A Tcdegrading enzyme,TetX,from the obligate anaerobe Bacteroides fragilis was cloned and recombinantly expressed in E.coli and fully characterized,including its Km and kcat value.We quantitatively evaluated its activity both in vitro and in vivo by UVeVis spectrometer and LC-MS.Moreover,we used a tetracycline inducible amplification circuit including T7 RNA polymerase and its specific promoter PT7 to enhance the expression level of TetX,and studied the dose-response of TetX under different inducer concentrations.Since the deployment of genetically modified organisms(GMOs)outside laboratory brings about safety concerns,it is necessary to explore the possibility of integrating a kill-switch.Toxin-Antitoxin(TA)systems were used to construct a mutually dependent host-plasmid platform and biocontainment systems in various academic and industrious situations.We selected nine TA systems from various bacteria strains and measured the toxicity of toxins(T)and the detoxifying activity of cognate antitoxins(A)to validate their potential to be used to build a kill-switch.These results prove the possibility of using engineered microorganisms to tackle antibiotic residues in environment efficiently and safely. | Zepeng Mu Zhuoning Zou Ye Yang Wenbo Wang Yue Xu Jianyi Huang Ruiling Cai Ye Liu Yajin Mo Boyi Wang Yiqun Dang Yongming Li Yushan Liu Yueren Jiang Qingyang Tan Xiaohong Liu Cheng Hu Hua Li Sha Wei Chunbo Lou Yang Yu Jiangyun Wang | 2018 | Synthetic and Systems Biotechnology2018，3，3： | 0 |
| 2 | A real 3D scene rendering optimization method based on region of interest and viewing frustum prediction in virtual reality显示文摘As an important technology of digital construction,real 3D models can improve the immersion and realism of virtual reality(VR)scenes.The large amount of data for real 3D scenes requires more effective rendering methods,but the current rendering optimization methods have some defects and cannot render real 3D scenes in virtual reality.In this study,the location of the viewing frustum is predicted by a Kalman filter,and eye-tracking equipment is used to recognize the region of interest(ROI)in the scene.Finally,the real 3D model of interest in the predicted frustum is rendered first.The experimental results show that the method of this study can predict the frustrum location approximately 200 ms in advance,the prediction accuracy is approximately 87%,the scene rendering efficiency is improved by 8.3%,and the motion sickness is reduced by approximately 54.5%.These studies help promote the use of real 3D models in virtual reality and ROI recognition methods.In future work,we will further improve the prediction accuracy of viewing frustums in virtual reality and the application of eye tracking in virtual geographic scenes. | Pei Dang Jun Zhu Jianlin Wu Weilian Li Jigang You Lin Fu Yiqun Shi Yuhang Gong | 2022 | International Journal of Digital Earth2022，15，1： | 0 |
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