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| 1 | Molecular evolution and functional divergence of HAK potassium transporter gene family in rice(Oryza sativa L.)显示文摘The high-affinity K+(HAK) transporter gene family is the largest family in plant that functions as potassium transporter and is impor-tant for various aspects of plant life.In the present study,we identified 27 members of this family in rice genome.The phylogenetic tree divided the land plant HAK transporter proteins into 6 distinct groups.Although the main characteristic of this family was established before the origin of seed plants,they also showed some differences between the members of non-seed and seed plants.The HAK genes in rice were found to have expanded in lineage-specific manner after the split of monocots and dicots,and both segmental duplication events and tandem duplication events contributed to the expansion of this family.Functional divergence analysis for this family provided statis-tical evidence for shifted evolutionary rate after gene duplication.Further analysis indicated that both point mutant with positive selection and gene conversion events contributed to the evolution of this family in rice. | Zefeng Yang Qingsong Gao Changsen Sun Wenjuan Li Shiliang Gu Chenwu Xu | 2009 | Journal of Genetics and Genomics2009，36，3： | 21 |
| 2 | Genomewide comparative phylogenetic and molecular evolutionary analysis of tubby-like protein family in Arabidopsis , rice, and poplar显示文摘 | Zefeng Yang Yong Zhou Xuefeng Wang Shiliang Gu Jianmin Yu Guohua Liang Changjie Yan Chenwu Xu | 2008 | Genomics2008，，4： | 1 |
| 3 | COVID-19 induces new-onset insulin resistance and lipid metabolic dysregulation via regulation of secreted metabolic factors显示文摘Abnormal glucose and lipid metabolism in COVID-19 patients were recently reported with unclear mechanism.In this study,we retrospectively investigated a cohort of COVID-19 patients without pre-existing metabolic-related diseases,and found new-onset in suli n resista nee,hyperglycemia,and decreased HDL-C in these patie nts.Mecha nistically,SARS-CoV-2 infecti on in creased the expression of RE1-silencing transcription factor(REST),which modulated the expression of secreted metabolic factors including myeloperoxidase,apelin,and myostatin at the transcriptional level,resulting in the perturbation of glucose and lipid metabolism.Furthermore,several lipids,including(±)5-HETE,(±)12-HETE,propionic acid,and isobutyric acid were identified as the potential biomarkers of COVID-19-induced metabolic dysregulation,especially in insulin resistance.Taken together,our study revealed insulin resistance as the direct cause of hyperglycemia upon COVID-19,and further illustrated the underlying mechanisms,providing potential therapeutic targets for COVID-19-induced metabolic complications. | Xi He Chenshu Liu Jiangyun Peng Zilun Li Fang Li Jian Wang Ao Hu Meixiu Peng Kan Huang Dongxiao Fan Na Li Fuchun Zhang Weiping Cai Xinghua Tan Zhongwei Hu Xilong Deng Yueping Li Xiaoneng Mo Linghua Li Yaling Shi Li Yang Yuanyuan Zhu Yanrong Wu Huichao Liang Baolin Liao Wenxin Hong Ruiying He Jiaojiao Li Pengle Guo Youguang Zhuo Lingzhai Zhao Fengyu Hu Wenxue Li Wei Zhu Zefeng Zhang Zeling Guo Wei Zhang Xiqiang Hong Wei kang Cai Lei Gu Ziming Du Yang Zhang Jin Xu Tao Zuo Kai Deng Li Yan Xinwen Chen Sifan Chen Chunliang Lei | 2022 | Signal Transduction and Targeted Therapy2022，7，1： | 0 |
| 4 | Facile and diverse logic circuits based on dumbbell DNA-templated fluorescent copper nanoclusters and S1 nuclease detection显示文摘DNA-based logic gates promote the development of molecular computing and show enormous potential in the fields of nanotechnology and biotechnology. Dumbbell oligonucleotides(DNA) with poly-thymine(poly-T) loops and a nicked random double strand have been demonstrated to be an efficient template for the formation of fluorescent copper nanoclusters(Cu NCs) in our previous work. Herein, a new platform technology is presented with which to construct molecular logic gates by employing Cu NCs probe as a basic output generator, coupling of functional nucleases as the inputs. Two dumbbell DNAs are used with the difference in stem length(8 bp and 16 bp, respectively). The degradation of DNA templates can be tuned by various nucleic acid enzymes, single-stranded nuclease(S1), double-stranded specific nuclease(DSN), E. coli DNA ligase, exonucleases Ⅰ and Ⅲ. Briefly, S1 can digest both DNA templates, while the cleavage ability of DSN will be resistant by the short stem of SS-DNA(short-stem DNA). Exonuclease Ⅰ and Ⅲ can degrade these two nicked DNA templates, which are inhibited due to the ligation of E. coli DNA ligase. With this novel strategy, a set of logic gates is successfully constructed at the molecular level,including “YES”, “PASS 0”, “OR”, “INHIBIT”, which take the advantages of no label, easy operation, fast speed, high efficiency and low cost. Furthermore, S1 nuclease, as the biomarker of numerous carcinogens,is selectively detected in the range of 0.05–50 U/m L with the detection limit of 0.005 U/m L(1×10^(−6)U)based on this platform. | Zefeng Gu Anchen Fu Ru Qiu Ru Sun Zhijuan Cao | 2022 | Chinese Chemical Letters2022，33，5： | 0 |
| 5 | Knowledge Graph Representation Learning Based on Automatic Network Search for Link Prediction显示文摘Link prediction,also known as Knowledge Graph Completion(KGC),is the common task in Knowledge Graphs(KGs)to predict missing connections between entities.Most existing methods focus on designing shallow,scalable models,which have less expressive than deep,multi-layer models.Furthermore,most operations like addition,matrix multiplications or factorization are handcrafted based on a few known relation patterns in several wellknown datasets,such as FB15k,WN18,etc.However,due to the diversity and complex nature of real-world data distribution,it is inherently difficult to preset all latent patterns.To address this issue,we proposeKGE-ANS,a novel knowledge graph embedding framework for general link prediction tasks using automatic network search.KGEANS can learn a deep,multi-layer effective architecture to adapt to different datasets through neural architecture search.In addition,the general search spacewe designed is tailored forKGtasks.We performextensive experiments on benchmark datasets and the dataset constructed in this paper.The results show that our KGE-ANS outperforms several state-of-the-art methods,especially on these datasets with complex relation patterns. | Zefeng Gu Hua Chen | 2023 | Computer Modeling in Engineering & Sciences2023，，6： | 0 |
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