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| 1 | Methionine metabolism in chronic liver diseases:an update on molecular mechanism and therapeutic implication显示文摘As one of the bicyclic metabolic pathways of one-carbon metabolism,methionine metabolism is the pivot linking the folate cycle to the transsulfuration pathway.In addition to being a precursor for glutathione synthesis,and the principal methyl donor for nucleic acid,phospholipid,histone,biogenic amine,and protein methylation,methionine metabolites can participate in polyamine synthesis.Methionine metabolism disorder can aggravate the damage in the pathological state of a disease.In the occurrence and development of chronic liver diseases(CLDs),changes in various components involved in methionine metabolism can affect the pathological state through various mechanisms.A methionine-deficient diet is commonly used for building CLD models.The conversion of key enzymes of methionine metabolism methionine adenosyltransferase(MAT)1 A and MAT2A/MAT2B is closely related to fibrosis and hepatocellular carcinoma.In vivo and in vitro experiments have shown that by intervening related enzymes or downstream metabolites to interfere with methionine metabolism,the liver injuries could be reduced.Recently,methionine supplementation has gradually attracted the attention of many clinical researchers.Most researchers agree that adequate methionine supplementation can help reduce liver damage.Retrospective analysis of recently conducted relevant studies is of profound significance.This paper reviews the latest achievements related to methionine metabolism and CLD,from molecular mechanisms to clinical research,and provides some insights into the future direction of basic and clinical research. | Zhanghao Li Feixia Wang Baoyu Liang Ying Su Sumin Sun Siwei Xia Jiangjuan Shao Zili Zhang Min Hong Feng Zhang Shizhong Zheng | 2020 | Signal Transduction and Targeted Therapy2020，5，1： | 3 |
| 2 | Identification and characterization of a novel peptide ligand of Tie2 for targeting gene therapy显示文摘有免疫球蛋白和表皮的生长因素相同 domain-2 (Tie2 ) 的酷氨酸 kinase 在稳固的肿瘤为基因治疗被看作了一个合理目标。以便为指向的基因治疗识别 Tie2 的新奇的肽 ligand,我们屏蔽了一个噬菌体显示肽图书馆并且识别了候选人肽 ligand NSLSNASEFRAPY (指明的 GA5 ) 。有约束力的试金和 Scatchard 分析表明 GA5 能明确地与 2.1 的一个分离常数绑在 Tie2 ?鷐 吗?? | Xianghua Wu Zonghai Li Ming Yao Huamao Wang Sumin Qu Xianlian Chen Jinjun Li Ye Sun Yuhong Xu Jianren Gu | 2008 | Acta Biochimica et Biophysica Sinica2008，40，3： | 2 |
| 3 | Defect engineering for high-selection-performance of NO reduction to NH3 over CeO_(2)(111)surface:A DFT study显示文摘To reduce the greenhouse effect caused by the surgery of nitrogen-oxides concentration in the atmosphere and develop a future energy carrier of renewables,it is very critical to develop more efficient,controllable,and highly sensitive catalytic materials.In our work,we proposed that nitric oxide(NO),as a supplement to N_(2) for the synthesis of ammonia,which is equipped with a lower barrier.And the study highlighted the potential of CeO_(2)(111)nanosheets with La doping and oxygen vacancy(OV)as a high-performance,controllable material for NO capture at the site of Vo site,and separation the process of hydrogenation.We also reported that the E_(ads) of-1.12 eV with horizontal adsorption and the Bader charge of N increasing of 0.53|e|and O increasing of 0.17|e|at the most active site of reduction-OV predicted.It is worth noting thatΔG of NORR(NO reduction reaction)shows good performance(thermodynamically spontaneous reaction)to synthesize ammonia and water at room temperature in the theoretical calculation. | Chaozheng He Risheng Sun Ling Fu Jinrong Huo Chenxu Zhao Xiuyuan Li Yan Song Sumin Wang | 2022 | Chinese Chemical Letters2022，33，1： | 1 |
| 4 | Sediment geochemistry of Lake Daihai, north-central China: implications for catchment weathering and climate change during the Holocene显示文摘 | Qianli Sun Sumin Wang Jie Zhou Zhongyuan Chen Ji Shen Xiuping Xie Feng Wu Peng Chen | 2009 | Journal of Paleolimnology2009，，1： | 1 |
| 5 | Research on recognition algorithm for gesture page turning based on wireless sensing显示文摘When a human body moves within the coverage range of Wi-Fi signals,the reflected Wi-Fi signals by the various parts of the human body change the propagation path,so analysis of the channel state data can achieve the perception of the human motion.By extracting the Channel State Information(CSI)related to human motion from the Wi-Fi signals and analyzing it with the introduced machine learning classification algorithm,the human motion in the spatial environment can be perceived.On the basis of this theory,this paper proposed an algorithm of human behavior recognition based on CSI wireless sensing to realize deviceless and over-the-air slide turning.This algorithm collects the environmental information containing upward or downward wave in a conference room scene,uses the local outlier factor detection algorithm to segment the actions,and then the time domain features are extracted to train Support Vector Machine(SVM)and eXtreme Gradient Boosting(XGBoost)classification modules.The experimental results show that the average accuracy of the XGBoost module sensing slide flipping can reach 94%,and the SVM module can reach 89%,so the module could be extended to the field of smart classroom and significantly improve speech efficiency. | Lin Tang Sumin Wang Meng Zhou Yinfan Ding Chao Wang Shengbo Wang Zhen Sun Jie Wu | 2023 | Intelligent and Converged Networks2023，4，1： | 0 |
| 6 | Smart nanoparticles for cancer therapy显示文摘Smart nanoparticles,which can respond to biological cues or be guided by them,are emerging as a promising drug delivery platform for precise cancer treatment.The field of oncology,nanotechnology,and biomedicine has witnessed rapid progress,leading to innovative developments in smart nanoparticles for safer and more effective cancer therapy.In this review,we will highlight recent advancements in smart nanoparticles,including polymeric nanoparticles,dendrimers,micelles,liposomes,protein nanoparticles,cell membrane nanoparticles,mesoporous silica nanoparticles,gold nanoparticles,iron oxide nanoparticles,quantum dots,carbon nanotubes,black phosphorus,MOF nanoparticles,and others.We will focus on their classification,structures,synthesis,and intelligent features.These smart nanoparticles possess the ability to respond to various external and internal stimuli,such as enzymes,pH,temperature,optics,and magnetism,making them intelligent systems.Additionally,this review will explore the latest studies on tumor targeting by functionalizing the surfaces of smart nanoparticles with tumor-specific ligands like antibodies,peptides,transferrin,and folic acid.We will also summarize different types of drug delivery options,including small molecules,peptides,proteins,nucleic acids,and even living cells,for their potential use in cancer therapy.While the potential of smart nanoparticles is promising,we will also acknowledge the challenges and clinical prospects associated with their use.Finally,we will propose a blueprint that involves the use of artificial intelligence-powered nanoparticles in cancer treatment applications.By harnessing the potential of smart nanoparticles,this review aims to usher in a new era of precise and personalized cancer therapy,providing patients with individualized treatment options. | Leming Sun Hongmei Liu Yanqi Ye Yang Lei Rehmat Islam Sumin Tan Rongsheng Tong Yang-Bao Miao Lulu Cai | 2023 | Signal Transduction and Targeted Therapy2023，8，12： | 0 |
| 7 | Design Strategy for Vulcanization Accelerator of Diphenylguanidine/Cyclodextrin Inclusion Complex for Natural Rubber Latex Foam with Enhancing Performance显示文摘Vulcanization is an essential process to obtain high-performance rubber products.Diphenylguanidine(DPG)is often used as the secondary accelerator in the vulcanization process of natural rubber(NR)latex.However,DPG would make NR latex emulsion exhibit gelation,resulting in the negative vulcanization efficiency.In addition,exposure to DPG might lead to some physiological diseases during the production process of DPG doped NR latex.Hydroxypropyl-β-cyclodextrin(HP-β-CD)with the hydrophobic interior and hydrophilic exterior has the advantages of good water solubility,high bioavailability,reliable stability,and low toxicity.In this study,the inclusion complex of diphenylguanidine-hydroxypropyl-β-cyclodextrin(DPG-HP-β-CD)is prepared by bali milling with a host-guest molar ratio of 1:1,which has also been applied to the foaming process of NR latex.The mechanical properties of DPG-HP-β-CD inclusion complex/natural rubber latex foam(DPG-HP-β-CD/NRLF)have been significantly improved,including the tensile strength,elongation at break,hardness,compression set,resilience,and antiaging performance.Further,the usage of DPG has been reduced,leading to the reduction of toxicity and environmental hazards. | Wang Zhang Liwei Lin Junqiang Guo Ming Wu Sumin Park Hang Yao Sun Ha Paek Guowang Diao Yuanzhe Piao | 2023 | Research2023，，1： | 0 |
| 8 | Wearable and stretchable conductive polymer composites for strain sensors:How to design a superior one?显示文摘Wearable and stretchable strain sensors have potential values in the fields of human motion and health monitoring,flexible electronics,and soft robotic skin.The wearable and stretchable strain sensors can be directly attached to human skin,providing visualized detection for human motions and personal healthcare.Conductive polymer composites(CPC)composed of conductive fillers and flexible polymers have the advantages of high stretchability,good flexibility,superior durability,which can be used to prepare flexible strain sensors with large working strain and outstanding sensitivity.This review has put forward a comprehensive summary on the fabrication methods,advanced mechanisms and strain sensing abilities of CPC strain sensors reported in recent years,especially the sensors with superior performance.Finally,the structural design,bionic function,integration technology and further application of CPC strain sensors are prospected. | Liwei Lin Sumin Park Yuri Kim Minjun Bae Jeongyeon Lee Wang Zhang Jiefeng Gao Sun Ha Paek Yuanzhe Piao | 2023 | Nano Materials Science2023，5，4： | 0 |
| 9 | Methionine metabolism in chronic liver diseases:an update on molecular mechanism and therapeutic implication显示文摘As one of the bicyclic metabolic pathways of one-carbon metabolism,methionine metabolism is the pivot linking the folate cycle to the transsulfuration pathway.In addition to being a precursor for glutathione synthesis,and the principal methyl donor for nucleic acid,phospholipid,histone,biogenic amine,and protein methylation,methionine metabolites can participate in polyamine synthesis.Methionine metabolism disorder can aggravate the damage in the pathological state of a disease.In the occurrence and development of chronic liver diseases(CLDs),changes in various components involved in methionine metabolism can affect the pathological state through various mechanisms.A methionine-deficient diet is commonly used for building CLD models.The conversion of key enzymes of methionine metabolism methionine adenosyltransferase(MAT)1 A and MAT2A/MAT2B is closely related to fibrosis and hepatocellular carcinoma.In vivo and in vitro experiments have shown that by intervening related enzymes or downstream metabolites to interfere with methionine metabolism,the liver injuries could be reduced.Recently,methionine supplementation has gradually attracted the attention of many clinical researchers.Most researchers agree that adequate methionine supplementation can help reduce liver damage.Retrospective analysis of recently conducted relevant studies is of profound significance.This paper reviews the latest achievements related to methionine metabolism and CLD,from molecular mechanisms to clinical research,and provides some insights into the future direction of basic and clinical research. | Zhanghao Li Feixia Wang Baoyu Liang Ying Su Sumin Sun Siwei Xia Jiangjuan Shao Zili Zhang Min Hong Feng Zhang Shizhong Zheng | 2021 | Signal Transduction and Targeted Therapy2021，6，1： | 0 |
| 10 | Temporal and spatial distribution characteristics of nutrients in Clarion-Clipperton Fracture Zone in the Pacific in 2017显示文摘This research investigated eight stations in Clarion-Clipperton Fracture Zone(CCFZ)in the eastern tropical Pacific in 2017 to study the spatial distribution characteristics of nutrients and chlorophyll a(Chi a)concentration,and compared nutrient concentrations and molar ratios with those of other investigations 20 years ago in the same area.The study found that dissolved inorganic nutrient(N,P and Si)concentrations were lowest in the upper layer,and increased from surface to some depths,then they decreased a little to the bottom.N was the limited nutrient factor for the growth of phytoplankton community.Although nutrient concentrations and molar ratios have no obvious changes in 2017 comparing those in 1998-2003,supplemented from the equatorial Pacific,nutrient concentrations in the study area were higher than those in seamounts in the North Pacific and Station ALOHA.Furthermore,this study used Generalized Additive Models(GAMs)to infer the underlying bottom-up factors controlling phytoplankton abundance(Chi a concentration),showing that depth,salinity and PO^-P concentration were major factors controlling the growth of phytoplankton community.Furthermore,this study can provide basic data and theoretical support for the development of polymetallic nodule area and its long-term impact assessment on the environment. | Baohong Chen Kaiwen Zhou Kang Wang Jigang Wang Sumin Wang Xiuwu Sun Jinmin Chen Cai Lin Hui Lin | 2022 | Acta Oceanologica Sinica2022，41，1： | 0 |
| 11 | Enhanced E-commerce Fraud Prediction Based on a Convolutional Neural Network Model显示文摘The rapidly escalating sophistication of e-commerce fraud in recent years has led to an increasing reliance on fraud detection methods based on machine learning.However,fraud detection methods based on conventional machine learning approaches suffer from several problems,including an excessively high number of network parameters,which decreases the efficiency and increases the difficulty of training the network,while simultaneously leading to network overfitting.In addition,the sparsity of positive fraud incidents relative to the overwhelming proportion of negative incidents leads to detection failures in trained networks.The present work addresses these issues by proposing a convolutional neural network(CNN)framework for detecting ecommerce fraud,where network training is conducted using historical market transaction data.The number of network parameters reduces via the local perception field and weight sharing inherent in the CNN framework.In addition,this deep learning framework enables the use of an algorithmiclevel approach to address dataset imbalance by focusing the CNN model on minority data classes.The proposed CNN model is trained and tested using a large public e-commerce service dataset from 2018,and the test results demonstrate that the model provides higher fraud prediction accuracy than existing state-of-the-art methods. | Sumin Xie Ling Liu Guang Sun Bin Pan Lin Lang Peng Guo | 2023 | Computers, Materials & Continua2023，，4： | 0 |
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