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| 1 | Arabidopsis EXO70A1 recruits Patellin3 to the cell membrane independent of its role as an exocyst subunit显示文摘The exocyst is a well-known complex which tethers vesicles at the cell membrane before fusion. Whether an individual subunit can execute a unique function is largely unknown. Using yeast-two-hybrid(Y2H) analysis, we found that EXO70A1 interacted with the GOLD domain of Patellin3(PATL3). The direct EXO70A1-PATL3 interaction was supported by in vitro and in vivo experiments. In Arabidopsis, PATL3-GFP colocalized with EXO70A1 predominantly at the cell membrane, and PATL3 localization was insensitive to BFA and Try A23. Remarkably, in the exo70 a1 mutant, PATL3 proteins accumulated as punctate structures within the cytosol, which did not colocalize with several endomembrane compartment markers, and was insensitive to BFA. Furthermore, PATL3 localization was not changed in the exo70 e2, PRsec6 or exo84b mutants. These data suggested that EXO70A1, but not other exocyst subunits, was responsible for PATL3 localization,which is independent of its role in secretory/recycling vesicletethering/fusion. Both EXO70A1 and PATL3 were shown to bind PI4 P and PI(4,5)P2 in vitro. Evidence was obtained that the other four members of the PATL family bound to EXO70A1 as well, and shared a similar localization pattern as PATL3.These findings offered new insights into exocyst subunitspecific function, and provided data and tools for further characterization of PATL family proteins. | Chengyun Wu Lu Tan Max van Hooren Xiaoyun Tan Feng Liu Yan Li Yanxue Zhao Bingxuan Li Qingchen Rui Teun Munnik Yiqun Bao | 2017 | Journal of Integrative Plant Biology2017，59，12： | 3 |
| 2 | Correction:Assessment of wind and photovoltaic power potential in China显示文摘Following publication of the original article[1],the authors reported some errors in Table 5.The correct Table 5 has been provided in this Correction.The original article[1]has been updated. | Yang Wang Qingchen Chao Lin Zhao Rui Chang | 2022 | Carbon Neutrality2022，1，1： | 2 |
| 3 | Biomarkers of aging显示文摘Aging biomarkers are a combination of biological parameters to(i)assess age-related changes,(ii)track the physiological aging process,and(iii)predict the transition into a pathological status.Although a broad spectrum of aging biomarkers has been developed,their potential uses and limitations remain poorly characterized.An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research:How old are we?Why do we get old?And how can we age slower?This review aims to address this need.Here,we summarize our current knowledge of biomarkers developed for cellular,organ,and organismal levels of aging,comprising six pillars:physiological characteristics,medical imaging,histological features,cellular alterations,molecular changes,and secretory factors.To fulfill all these requisites,we propose that aging biomarkers should qualify for being specific,systemic,and clinically relevant. | Aging Biomarker Consortium Hainan Bao Jiani Cao Mengting Chen Min Chen Wei Chen Xiao Chen Yanhao Chen Yu Chen Yutian Chen Zhiyang Chen Jagadish K Chhetri Yingjie Ding Junlin Feng Jun Guo Mengmeng Guo Chuting He Yujuan Jia Haiping Jiang Ying Jing Dingfeng Li Jiaming Li Jingyi Li Qinhao Liang Rui Liang Feng Liu Xiaoqian Liu Zuojun Liu Oscar Junhong Luo Jianwei Lv Jingyi Ma Kehang Mao Jiawei Nie Xinhua Qiao Xinpei Sun Xiaoqiang Tang Jianfang Wang Qiaoran Wang Siyuan Wang Xuan Wang Yaning Wang Yuhan Wang Rimo Wu Kai Xia Fu-Hui Xiao Lingyan Xu Yingying Xu Haoteng Yan Liang Yang Ruici Yang Yuanxin Yang Yilin Ying Le Zhang Weiwei Zhang Wenwan Zhang Xing Zhang Zhuo Zhang Min Zhou Rui Zhou Qingchen Zhu Zhengmao Zhu Feng Cao Zhongwei Cao Piu Chan Chang Chen Guobing Chen Hou-Zao Chen Jun Chen Weimin Ci Bi-Sen Ding Qiurong Ding Feng Gao Jing-Dong JHan Kai Huang Zhenyu Ju Qing-Peng Kong Ji Li Jian Li Xin Li Baohua Liu Feng Liu Lin Liu Qiang Liu Qiang Liu Xingguo Liu Yong Liu Xianghang Luo Shuai Ma Xinran Ma Zhiyong Mao Jing Nie Yaojin Peng Jing Qu Jie Ren Ruibao Ren Moshi Song Zhou Songyang Yi Eve Sun Yu Sun Mei Tian Shusen Wang Si Wang Xia Wang Xiaoning Wang Yan-Jiang Wang Yunfang Wang Catherine CL Wong Andy Peng Xiang Yichuan Xiao Zhengwei Xie Daichao Xu Jing Ye Rui Yue Cuntai Zhang Hongbo Zhang Liang Zhang Weiqi Zhang Yong Zhang Yun-Wu Zhang Zhuohua Zhang Tongbiao Zhao Yuzheng Zhao Dahai Zhu Weiguo Zou Gang Pei Guang-Hui Liu | 2023 | Science China(Life Sciences)2023，66，5： | 2 |
| 4 | Assessment of wind and photovoltaic power potential in China显示文摘Decarbonization of the energy system is the key to China’s goal of achieving carbon neutrality by 2060.However,the potential of wind and photovoltaic(PV)to power China remains unclear,hindering the holistic layout of the renewable energy development plan.Here,we used the wind and PV power generation potential assessment system based on the Geographic Information Systems(GIS)method to investigate the wind and PV power generation potential in China.Firstly,the high spatial-temporal resolution climate data and the mainstream wind turbines and PV modules,were used to assess the theoretical wind and PV power generation.Then,the technical,policy and economic(i.e.,theoretical power generation)constraints for wind and PV energy development were comprehensively considered to evaluate the wind and solar PV power generation potential of China in 2020.The results showed that,under the current technological level,the wind and PV installed capacity potential of China is about 56.55 billion kW,which is approximately 9 times of those required under the carbon neutral scenario.The wind and PV power generation potential of China is about 95.84 PWh,which is approximately 13 times the electricity demand of China in 2020.The rich areas of wind power generation are mainly distributed in the western,northern,and coastal provinces of China.While the rich areas of PV power generation are mainly distributed in western and northern China.Besides,the degree of tapping wind and PV potential in China is not high,and the installed capacity of most provinces in China accounted for no more than 1%of the capacity potential,especially in the wind and PV potential-rich areas. | Yang Wang Qingchen Chao Lin Zhao Rui Chang | 2022 | Carbon Neutrality2022，1，1： | 1 |
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