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| 1 | Recently duplicated sesterterpene(C25) gene clusters in Arabidopsis thaliana modulate root microbiota显示文摘Land plants co-speciate with a diversity of continually expanding plant specialized metabolites(PSMs) and root microbial communities(microbiota).Homeostatic interactions between plants and root microbiota are essential for plant survival in natural environments.A growing appreciation of microbiota for plant health is fuelling rapid advances in genetic mechanisms of controlling microbiota by host plants.PSMs have long been proposed to mediate plant and single microbe interactions.However,the effects of PSMs,especially those evolutionarily new PSMs,on root microbiota at community level remain to be elucidated.Here,we discovered sesterterpenes in Arabidopsis thaliana,produced by recently duplicated prenyltransferase-terpene synthase(PT-TPS) gene clusters,with neo-functionalization.A single-residue substitution played a critical role in the acquisition of sesterterpene synthase(sesterTPS) activity in Brassicaceae plants.Moreover,we found that the absence of two root-specific sesterterpenoids,with similar chemical structure,significantly affected root microbiota assembly in similar patterns.Our results not only demonstrate the sensitivity of plant microbiota to PSMs but also establish a complete framework of host plants to control root microbiota composition through evolutionarily dynamic PSMs. | Qingwen Chen Ting Jiang Yong-Xin Liu Haili Liu Tao Zhao Zhixi Liu Xiangchao Gan Asis Hallab Xuemei Wang Juan He Yihua Ma Fengxia Zhang Tao Jin M. Eric Schranz Yong Wang Yang Bai Guodong Wang | 2019 | Science China(Life Sciences)2019，62，7： | 11 |
| 2 | Leaf phenotypic variation of endangered plant Tetracentron sinense Oliv.and influence of geographical and climatic factors显示文摘To analyze the degree and pattern of phenotypic variation in leaves of Tetracentron sinense Oliv from the perspective of genetic and environmental adaptation and thus contribute to effective evidence-based conservation and management strategies for germplasm resources,we measured 17 morphological and epidermal micromorphological leaf traits from 24 natural populations of T.sinense.Nested analysis of variance,multiple comparison,principal component analysis(PCA),cluster analysis,and correlation analysis were used to explore phenotypic leaf variation among and within populations and potential correlations with geographic and environmental factors.There were significant differences in 17 leaf phenotypic traits among and within populations.The mean phenotypic differentiation coefficient of the 17 traits was 56.34%,and the variation among populations(36.4%)was greater than that within populations(27.2%).The coefficient of variation(CV)of each trait ranged from 4.6 to 23.8%,and the mean was 11.8%.Phenotypic variation of leaves was related to environmental factors such as average annual sunshine hours,average July temperature,and average annual rainfall.The variation changed along gradients of longitude,latitude,and altitude.The PCA clustered the 24 natural populations into four groups.Our study suggests that phenotypic variation in T.sinense occurred primarily among populations,with moderate levels of phenotypic differentiation among populations and low levels of phenotypic variation within populations.The plant’s poor adaptability to the environment is likely an important contributor to its endangerment.Accordingly,conservation strategies are proposed to protect and manage the natural populations of T.sinense. | Yang Li Shan Li Xueheng Lu Qinqin Wang Hongyan Han Xuemei Zhang Yonghong Ma Xiaohong Gan | 2021 | Journal of Forestry Research2021，32，2： | 3 |
| 3 | Death causes and pathogens analysis of systemic lupus erythematosus during the past 26 years显示文摘 | Yunyun Fei Xiaochun Shi Fengying Gan Xuemei Li Wen Zhang Mengtao Li Yong Hou Xuan Zhang Yan Zhao Xiaofeng Zeng Fengchun Zhang | 2014 | Clinical Rheumatology2014，，1： | 1 |
| 4 | Human health risk of organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs) in edible fish from Huairou Reservoir and Gaobeidian Lake in Beijing, China显示文摘 | Xuemei Li Yiping Gan Xiangping Yang Jun Zhou Jiayin Dai Muqi Xu | 2008 | Food Chemistry2008，，2： | 1 |
| 5 | Human health risk of organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs) in edible fish from Huairou Reservoir and Gaobeidian Lake in Beijing,China显示文摘 | Xuemei Li Yiping Gan Xiangping Yang | | 0，，109： | 1 |
| 6 | The archaeal KEOPS complex possesses a functional Gon7 homolog and has an essential function independent of the cellular t^(6)A modification level显示文摘Kinase,putative Endopeptidase,and Other Proteins of Small size(KEOPS)is a multisubunit protein complex conserved in eukaryotes and archaea.It is composed of Pcc1,Kae1,Bud32,Cgi121,and Gon7 in eukaryotes and is primarily involved in N^(6)-threonylcarbamoyl adenosine(t^(6)A)modification of transfer RNAs(tRNAs).Recently,it was reported that KEOPS participates in homologous recombination(HR)repair in yeast.To characterize the KEOPS in archaea(aKEOPS),we conducted genetic and biochemical analyses of its encoding genes in the hyperthermophilic archaeon Saccharolobus islandicus.We show that aKEOPS also possesses five subunits,Pcc1,Kae1,Bud32,Cgi121,and Pcc1-like(or Gon7-like),just like eukaryotic KEOPS.Pcc1-like has physical interactions with Kae1 and Pcc1 and can mediate the monomerization of the dimeric subcomplex(Kae1-Pcc1-Pcc1-Kae1),suggesting that Pcc1-like is a functional homolog of the eukaryotic Gon7 subunit.Strikingly,none of the genes encoding aKEOPS subunits,including Pcc1 and Pcc1-like,can be deleted in the wild type and in a t^(6)A modification complementary strain named TsaKI,implying that the aKEOPS complex is essential for an additional cellular process in this archaeon.Knock-down of the Cgi121 subunit leads to severe growth retardance in the wild type that is partially rescued in TsaKI.These results suggest that aKEOPS plays an essential role independent of the cellular t^(6)A modification level.In addition,archaeal Cgi121 possesses dsDNA-binding activity that relies on its tRNA 3ʹCCA tail binding module.Our study clarifies the subunit organization of archaeal KEOPS and suggests an origin of eukaryotic Gon7.The study also reveals a possible link between the function in t^(6)A modification and the additional function,presumably HR. | Pengju Wu Qi Gan Xuemei Zhang Yunfeng Yang Yuanxi Xiao Qunxin She Jinfeng Ni Qihong Huang Yulong Shen | 2023 | mLife2023，2，1： | 0 |
| 7 | Digital twin-enabled adaptive scheduling strategy based on deep reinforcement learning显示文摘The modern complicated manufacturing industry and smart manufacturing tendency have imposed new requirements on the scheduling method,such as self-regulation and self-learning capabilities.While traditional scheduling methods cannot meet these needs due to their rigidity.Self-learning is an inherent ability of reinforcement learning(RL) algorithm inhered from its continuous learning and trial-and-error characteristics.Self-regulation of scheduling could be enabled by the emerging digital twin(DT) technology because of its virtual-real mapping and mutual control characteristics.This paper proposed a DT-enabled adaptive scheduling based on the improved proximal policy optimization RL algorithm,which was called explicit exploration and asynchronous update proximal policy optimization algorithm(E2APPO).Firstly,the DT-enabled scheduling system framework was designed to enhance the interaction between the virtual and the physical job shops,strengthening the self-regulation of the scheduling model.Secondly,an innovative action selection strategy and an asynchronous update mechanism were proposed to improve the optimization algorithm to strengthen the self-learning ability of the scheduling model.Lastly,the proposed scheduling model was extensively tested in comparison with heuristic and meta-heuristic algorithms,such as wellknown scheduling rules and genetic algorithms,as well as other existing scheduling methods based on reinforcement learning.The comparisons have proved both the effectiveness and advancement of the proposed DT-enabled adaptive scheduling strategy. | GAN XueMei ZUO Ying ZHANG AnSi LI ShaoBo TAO Fei | 2023 | Science China(Technological Sciences)2023，66，7： | 0 |
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