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| 1 | Investigation of PM_(2.5) pollution during COVID-19 pandemic in Guangzhou,China显示文摘The COVID-19 pandemic has raised awareness about various environmental issues,includ-ing PM_(2.5) pollution.Here,PM_(2.5) pollution during the COVID-19 lockdown was traced and an-alyzed to clarify the sources and factors influencing PM_(2.5) in Guangzhou,with an emphasis on heavy pollution.The lockdown led to large reductions in industrial and traffic emissions,which significantly reduced PM_(2.5) concentrations in Guangzhou.Interestingly,the trend of PM_(2.5) concentrations was not consistent with traffic and industrial emissions,as minimum concentrations were observed in the fourth period(3/01-3/31,22.45 μg/m^(3))of the lockdown.However,the concentrations of other gaseous pollutants,e.g.,SO_(2),NO_(2) and CO,were corre-lated with industrial and traffic emissions,and the lowest values were noticed in the sec-ond period(1/24-2/0_(3))of the lockdown.Meteorological correlation analysis revealed that the decreased PM_(2.5) concentrations during COVID-19 can be mainly attributed to decreased in-dustrial and traffic emissions rather than meteorological conditions.When meteorological factors were included in the PM_(2.5) composition and backward trajectory analyses,we found that long-distance transportation and secondary pollution offset the reduction of primary emissions in the second and third stages of the pandemic.Notably,industrial PM_(2.5) emis-sions from western,southern and southeastern Guangzhou play an important role in the formation of heavy pollution events.Our results not only verify the importance of control-ling traffic and industrial emissions,but also provide targets for further improvements in PM_(2.5) pollution. | Luyao Wen Chun Yang Xiaoliang Liao Yanhao Zhang Xuyang Chai Wenjun Gao Shulin Guo Yinglei Bi Suk-Ying Tsang Zhi-Feng Chen Zenghua Qi Zongwei Cai | 2022 | Journal of Environmental Sciences2022，34，5： | 2 |
| 2 | 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 |
| 3 | High-Quality de novo Genome Assembly of Huajingxian 74, a Receptor Parent of Single Segment Substitution Lines显示文摘Rice(Oryza sativa L.)is grown nearly worldwide and provides the staple food for more than half of the global population(Luo et al,2017).The genomes of several cultivated rice varieties including Nipponbare(NPB)(Kawahara et al,2013;Sakai et al,2013),IR64(Tanaka et al,2020),93-11(Zhang et al,2018)and R498(Du et al,2017)at chromosome level,and Minghui 63 and Zhenshan 97(Zhang et al,2016)at scaffold level have been assembled,annotated and released,among which the R498 and NPB genomes are widely used as reference genomes in rice research.However,there are thousands of rice cultivars,landraces and wild rice varieties in the world with dramatically different genetic backgrounds,and the genomes of native rice varieties in South China,which is one of the major rice production areas in China,have not been de novo assembled.Huajingxian 74(HJX74)is an indica rice variety bred in South China Agricultural University,Guangdong Province with widely environmental adaptability and high yield(www.ricedata.cn/variety/varis/602548.htm).HJX74 exhibits significant phenotypic and genetic differences from those varieties whose whole genomes have been properly sequenced and assembled(Fig.1). | LI Fangping GAO Yanhao WU Bingqi CAI Qingpei ZHAN Pengling YANG Weifeng SHI Wanxuan LI Xiaohua YANG Zifeng TAN Quanya LUAN Xin ZHANG Guiquan WANG Shaokui | 2021 | Rice science2021，28，2： | 0 |
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