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Aldehyde oxidase mediated enantioselective metabolic health risk of dinotefuran

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Science China Chemistry 2024年第6期67卷 2079-2091页

作者： liwei Xu Xinxin Xu Hua Kuang Chuanlai Xu Xiaoling wu State Key Laboratory of Food Science and Resources Jiangnan UniversityWuxi214122China International Joint Research Laboratory for Biointerface and Biodetection and School of Food Science and Technology Jiangnan UniversityWuxi214122China Collaborative Innovation center of Food Safety and Quality Control in Jiangsu Province Jiangnan UniversityWuxi214122China

Chiral pollutants often pose significant differential environmental health risks.In this study,the biotransformation of chiral dinotefuran(DIN)and its enantioselective metabolic toxicity mechanisms have been systemically investigated.Firstly,reversedphase chromatography-high resolution mass spectrometry was developed to quantify the content of DIN R/S chiral enantiomer with pg level sensitivity,revealing a lower elimination rate constant(K_(e))of S-DIN(0.730 h^(-1))than R-DIN(0.746 h^(-1)).Secondly,the interaction mechanism between DIN metabolism and important endogenous bioactive molecules,such as aldehyde oxidase(AOX)and neurotransmitters,was revealed.The DIN nitro-group was converted into a guanidine group by the reducing site of nearby flavin adenine dinucleotide(FAD)in AOX with the preferred higher affinity of S-configuration.Meanwhile,the endogenous tryptophan(Trp)aldehyde metabolic intermediate,5-hydroxyindoleacetaldehyde(5-HIAL),provides a persistent electron donor for DIN reduction via the oxidation-catalyzed site in AOX,resulting in remarkable up-regulation of monoamine neurotransmitters such as serotonin and dopamine.Thirdly,the higher level of neurotransmitters further mediated dysregulation of oxylipin homeostasis via the serotonergic pathway,where S-DIN exhibited more pronounced liver lipid damage and environmental health risk with the accumulated lipid biomarkers,oxidized triglyceride(OxTG)and oxidized sphingomyelin(OxSM).This study elucidates the AOX-mediated enantioselectivity metabolic pathway of DIN,providing a new analytical method for chiral pollutants and paves the way for their health risk assessments.

关键词： neonicotinoid dinotefuran enantiomer aldehyde oxidase metabolomics health risk

A Local-Global Attention Fusion Framework With Tensor Decomposition for Medical Diagnosis

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1536-1538页

作者： Peishu wu Han Li liwei Hu Jirong Ge Nianyin Zeng Department of Instrumental and Electrical Engineering Xiamen UniversityFujian 361005China Key Research Laboratory of Osteoporosis Syndrome Genomics Fujian Academy of Chinese Medical SciencesFuzhou 350003China

Dear Editor,In this letter,a novel hierarchical fusion framework is proposed to address the imperfect data property in complex medical image analysis(MIA)scenes.In particular,by combining the strengths of convolutional neural networks(CNNs)and transformers,the enhanced feature extraction,spatial modeling,and sequential context learning are realized to provide comprehensive insights on the complex data patterns.Integration of information in different level is enabled via a multi-attention fusion mechanism,and the tensor decomposition methods are adopted so that compact and distinctive representation of the underlying and high-dimensional medical image features can be accomplished[1].It is shown from the evaluation results that the proposed framework is competitive and superior as compared with some other advanced algorithms,which effectively handles the imperfect property of inter-class similarity and intra-class differences in diseases,and meanwhile,the model complexity is reduced within an acceptable level,which benefits the deployment in clinic practice.MIA has assumed a pivotal role in numerous critical clinical scenarios,where sophisticated image analysis techniques have proven instrumental in augmenting medical decision-making,facilitating individualized therapeutic interventions,and enhancing patient prognostication[2]−[4].

关键词： handle image property

Integrated Clustering and Routing Design and Triangle Path Optimization for UAV-Assisted Wireless Sensor Networks

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China Communications 2024年第4期21卷 178-192页

作者： Shao liwei Qian Liping wu Mengru wu Yuan College of Information Engineering Zhejiang University of TechnologyHangzhou 310014China State Key Laboratory of Internet of Things for Smart City University of MacaoMacaoChina Department of Computer and Information Science University of MacaoMacaoChina

With the development of the Internet of Things(IoT),it requires better performance from wireless sensor networks(WSNs),such as larger coverage,longer lifetime,and lower latency.However,a large amount of data generated from monitoring and long-distance transmission places a heavy burden on sensor nodes with the limited battery power.For this,we investigate an unmanned aerial vehicles assisted mobile wireless sensor network(UAV-assisted WSN)to prolong the network lifetime in this paper.Specifically,we use UAVs to assist the WSN in collecting data.In the current UAV-assisted WSN,the clustering and routing schemes are determined sequentially.However,such a separate consideration might not maximize the lifetime of the whole WSN due to the mutual coupling of clustering and routing.To efficiently prolong the lifetime of the WSN,we propose an integrated clustering and routing scheme that jointly optimizes the clustering and routing together.In the whole network space,it is intractable to efficiently obtain the optimal integrated clustering and routing scheme.Therefore,we propose the Monte-Las search strategy based on Monte Carlo and Las Vegas ideas,which can generate the chain matrix to guide the algorithm to find the solution faster.Unnecessary point-to-point collection leads to long collection paths,so a triangle optimization strategy is then proposed that finds a compromise path to shorten the collection path based on the geometric distribution and energy of sensor nodes.To avoid the coverage hole caused by the death of sensor nodes,the deployment of mobile sensor nodes and the preventive mechanism design are indispensable.An emergency data transmission mechanism is further proposed to reduce the latency of collecting the latency-sensitive data due to the absence of UAVs.Compared with the existing schemes,the proposed scheme can prolong the lifetime of the UAVassisted WSN at least by 360%,and shorten the collection path of UAVs by 56.24%.

关键词： Monte-Las search strategy triangle path optimization unmanned aerial vehicles wireless sensor networks

Genesis of the Nuri Cu-W-Mo Deposit,Tibet,China:Constraints from in situ Trace Elements and Sr Isotopic Analysis of Scheelite

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Acta Geologica Sinica(English Edition) 2024年第1期98卷 117-131页

作者： WANG Yiyun wu Zhishan CHEN Wenqing DU Qing’an TANG liwei SHI Hongzhao MA Guotao ZHANG Zhi LIANG Wei wu Bo MIAO Hengyi Chengdu Center China Geological Survey(Geoscience Innovation Center of Southwest China)Chengdu 610081China The Second Geological Institute of China’s Metallurgical Geology Bureau Fuzhou 351111China

The Nuri deposit is the only Cu-W-Mo polymetallic deposit with large-scale WO3 resources in the eastern section of the Gangdese metallogenic belt,Tibet,China.However,the genetic type of this deposit has been controversial since its discovery.Based on a study of the geological characteristics of the deposit,this study presents mineralization stages,focusing on the oxide stage and the quartz-sulfide stage where scheelite is mainly formed,referred to as Sch-A and Sch-B,respectively.Through LA-ICP-MS trace element and Sr isotope analyses,the origin,evolutionary process of the oreforming fluid and genesis of the ore deposit are investigated.Scanning Electron Microscope-Cathodoluminescence(SEMCL)observations reveal that Sch-A consists of three generations,with dark gray homogenous Sch-A1 being replaced by relatively lighter and homogeneous Sch-A2 and Sch-A3,with Sch-A2 displaying a gray CL image color with vague and uneven growth bands and Sch-A3 has a light gray CL image color with hardly any growth band.In contrast,Sch-B exhibits a‘core-rim’structure,with the core part(Sch-B1)being dark gray and displaying a uniform growth band,while the rim part(Sch-B2)is light gray and homogeneous.The normalized distribution pattern of rare earth elements in scheelite and Sr isotope data suggest that the early ore-forming fluid in the Nuri deposit originated from granodiorite porphyry and,later on,some country rock material was mixed in,due to strong water-rock interaction.Combining the O-H isotope data further indicates that the ore-forming fluid in the Nuri deposit originated from magmatic-hydrothermal sources,with contributions from metamorphic water caused by water-rock interaction during the mineralization process,as well as later meteoric water.The intense water-rock interaction likely played a crucial role in the precipitation of scheelite,leading to varying Eu anomalies in different generations of scheelite from the oxide stage to the quartz-sulfide stage,while also causing a gradual decrease in oxygen fugacity(fO2)and a sl

关键词： trace elements in situ Sr isotopes tungsten mineralization Gangdese metallogenic belt Tibet

The Gut Microbiome and Ferroptosis in MAFLD

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Journal of Clinical and Translational Hepatology 2023年第1期11卷 174-187页

作者： Jie Ji liwei wu Jue Wei Jianye wu Chuanyong Guo Department of Gastroenterology Putuo People’s HospitalTongji UniversityShanghaiChina Department of Gastroenterology Shanghai Tenth People’s HospitalTongji University School of MedicineShanghaiChina Department of Gastroenterology Shanghai Tongren Hospital Shanghai Jiaotong University School of MedicineShanghaiChina

Metabolic-associated fatty liver disease(MAFLD)is a new disease definition,and is proposed to replace the previous name,nonalcoholic fatty liver disease(NAFLD).Globally,MAFLD/NAFLD is the most common liver disease,with an incidence rate ranging from 6%to 35%in adult populations.The pathogenesis of MAFLD/NAFLD is closely related to insulin resistance(IR),and the genetic susceptibility to acquired metabolic stress-associated liver injury.Similarly,the gut microbiota in MAFLD/NAFLD is being revaluated by scientists,as the gut and liver influence each other via the gut-liver axis.Ferroptosis is a novel form of programmed cell death caused by iron-dependent lipid peroxidation.Emerging evidence suggests that ferroptosis has a key role in the pathological progression of MAFLD/NAFLD,and inhibition of ferroptosis may become a novel therapeutic strategy for the treatment of NAFLD.This review focuses on the main mechanisms behind the promotion of MAFLD/NAFLD occurrence and development by the intestinal microbiota and ferroptosis.It outlines new strategies to target the intestinal microbiota and ferroptosis to facilitate future MAFLD/NAFLD therapies.

关键词： Gut microbiota Ferroptosis Nonalcoholic fatty liver disease Gutliver axis

Li^(+)doping induced zero-thermal quenching in Cs_(3)Zn_(6-x-y)B_(9)O_(21):xEu^(3+),yLi^(+)(0≤x≤0.10,0.06≤y≤0.16)

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Journal of Rare Earths 2023年第10期41卷 1478-1486,I0001页

作者： Yuxing Bai liwei wu Qilin Cheng Li wu Yongfa Kong Yi Zhang Jingjun Xu Key Laboratory of Weak-Light Nonlinear Photonics Ministry of EducationSchool of PhysicsNankai UniversityTianjin300071China College of Science Civil Aviation University of ChinaTianjin300300China Institute of Photo-electronic Thin Film Devices and Technology Nankai UniversityTianjin300071China

Thermal stability is a crucial index to assess application value of high-power LEDs,which is related to lattice defects.Herein,an effective structure-engineering strategy is proposed to achieve excellent properties.Under the 394 nm excitation,Cs_3Zn_(5.94)B_9O_(21):0.06Eu^(3+)possesses two characteristic emissions peaked at 591 and 612 nm with limited thermal stability.By introducing Li^(+)ions into the lattice,the sample exhibits high color purity and excellent zero-thermal quenching because the defect contents of the phosphor can be effectively modulated via charge-compensation effect.Then,under the stimulus of high temperature,the corresponding trap levels with a suitable depth(E=1.27 eV)will release electrons to recombine with the luminescent centers,compensating for the energy loss.The study provides a meaningful guide for optimizing and designing novel functional photoluminescent materials.

关键词： Photoluminescence Charge compensation Lattice defects Thermal stability Rare earths

High-entropy perovskite oxides:An emergent type of photochromic oxides with fast response for handwriting display

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Journal of Advanced Ceramics 2023年第7期12卷 1371-1388页

作者： Xiangyu Wang Tong Wei Yingqiu Xu liwei wu Yingdong Han Jiao Cui College of Science Civil Aviation University of ChinaTianjin 300300China

Stimulus-responsive materials are fundamental to the broad and ever-growing field of intelligence research,which bridge intelligent systems with the Internet of Things(loT)in future lifestyles.Among these materials,writable materials have received great interest;however,carbonization and irreversible writing processes are generally inevitable for extensively investigated organic compounds.Photochromism is a potential mode of composing information.Nevertheless,inorganic materials usually exhibit weak photochromic effects.Here,a novel strategy of designing high-entropy perovskite(HEP)oxides is put forward to develop a new inorganic photochromic system with satisfying performance.A series of HEP oxides are synthesized for the first time.Benefiting from excellent photochromic features,real-time information encoding was achieved.The mechanism-related photochromism is also discussed.Distinct from the previous works,it is believed that the present photochromic-based HEP oxides provide a new and manyfold research space for the future development of conventional writable materials and the disclosing of unprecedented properties and phenomena.

关键词： stimulus-responsive materials inorganic materials high-entropy perovskite(HEP)oxides photochromism

从信号到知识——基于人工智能的医学影像裸数据诊断价值初探

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Engineering 2024年第3期34卷 60-69页

作者： Bingxi He Yu Guo Yongbei Zhu Lixia Tong Boyu Kong Kun Wang Caixia Sun Hailin Li Feng Huang liwei wu Meng Wang Fanyang Meng Le Dou Kai Sun Tong Tong Zhenyu Liu Ziqi Wei Wei Mu Shuo Wang Zhenchao Tang Shuaitong Zhang Jingwei Wei Lizhi Shao Mengjie Fang Juntao Li Shouping Zhu Lili Zhou Shuo Wang Di Dong Huimao Zhang Jie Tian Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Engineering MedicineBeihang UniversityBeijing 100191China Key Laboratory of Big Data-Based Precision Medicine Beihang UniversityMinistry of Industry and Information TechnologyBeijing 100191China CAS Key Laboratory of Molecular Imaging Institute of AutomationChinese Academy of SciencesBeijing 100190China Department of Radiology The First Hospital of Jilin UniversityChangchun 130021China Neusoft Medical Systems Co.Ltd. Shenyang 110167China Neusoft Research of Intelligent Healthcare Technology Co.Ltd. Shenyang 110167China School of Life Science and Technology Xidian UniversityXi’an 710126China Engineering Research Center of Molecular and Neuro Imaging Ministry of EducationXi’an 710126China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China

Encouraging and astonishing developments have recently been achieved in image-based diagnostic technology.Modern medical care and imaging technology are becoming increasingly inseparable.However,the current diagnosis pattern of signal to image to knowledge inevitably leads to information distortion and noise introduction in the procedure of image reconstruction(from signal to image).Artificial intelligence(AI)technologies that can mine knowledge from vast amounts of data offer opportunities to disrupt established workflows.In this prospective study,for the first time,we develop an AI-based signal-toknowledge diagnostic scheme for lung nodule classification directly from the computed tomography(CT)raw data(the signal).We find that the raw data achieves almost comparable performance with CT,indicating that it is possible to diagnose diseases without reconstructing images.Moreover,the incorporation of raw data through three common convolutional network structures greatly improves the performance of the CT models in all cohorts(with a gain ranging from 0.01 to 0.12),demonstrating that raw data contains diagnostic information that CT does not possess.Our results break new ground and demonstrate the potential for direct signal-to-knowledge domain analysis.

关键词： Computed tomography Diagnosis Deep learning Lung cancer Raw data

A Flight Trajectory Prediction Method Based on Internal Relationships between Attributes

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计算机科学与技术汇刊（中英文版） 2023年第1期10卷 1-10页

作者： liwei wu Yuqi Fan School of Computer Science and Information Engineering/Hefei University of Technology HefeiAnhui230000China

The rapid development of the aviation industry urgently requires airspace traffic management,and flight trajectory prediction is a core component of airspace traffic management.Flight trajectory is a multidimensional time series with rich spatio-temporal characteristics,and existing flight trajectory prediction methods only target the trajectory point temporal relationships,but not the implicit interrelationships among the trajectory point attributes.In this paper,a graph convolutional network(AR-GCN)based on the intra-attribute relationships is proposed for solving the flight track prediction problem.First,the network extracts the temporal features of each attribute and fuses them with the original features of the attribute to obtain the enhanced attribute features,then extracts the implicit relationships between attributes as inter-attribute relationship features.Secondly,the enhanced attribute features are used as nodes and the inter-attribute relationship features are used as edges to construct the inter-attribute relationship graph.Finally,the graph convolutional network is used to aggregate the attribute features.Based on the full fusion of the above features,we achieved high accuracy prediction of the trajectory.In this paper,experiments are conducted on ADS-B historical track data.We compare our method with the classical method and the proposed method.Experimental results show that our method achieves significant improvement in prediction accuracy.

关键词： Deep Learning Graph Convolution Neural Network Flight Trajectory Prediction