The authors regret that there were errors in the affiliations and the funding declaration in the original published version.The affiliations a and b of the original manuscript are"School of Information Engineerin...The authors regret that there were errors in the affiliations and the funding declaration in the original published version.The affiliations a and b of the original manuscript are"School of Information Engineering,Jiangxi Provincial Key Laboratory of Advanced Signal Processing and Intelligent Communications,Nanchang University,Nanchang 330031,China",and"School of Internet of Things Engineering,Jiangnan University,Wuxi 214122,China",respectively.The order of the two affiliations are not correct.展开更多
Intelligent Transportation Systems(ITS)leverage Integrated Sensing and Communications(ISAC)to enhance data exchange between vehicles and infrastructure in the Internet of Vehicles(IoV).This integration inevitably incr...Intelligent Transportation Systems(ITS)leverage Integrated Sensing and Communications(ISAC)to enhance data exchange between vehicles and infrastructure in the Internet of Vehicles(IoV).This integration inevitably increases computing demands,risking real-time system stability.Vehicle Edge Computing(VEC)addresses this by offloading tasks to Road Side Units(RSUs),ensuring timely services.Our previous work,the FLSimCo algorithm,which uses local resources for federated Self-Supervised Learning(SSL),has a limitation:vehicles often can’t complete all iteration tasks.Our improved algorithm offloads partial tasks to RSUs and optimizes energy consumption by adjusting transmission power,CPU frequency,and task assignment ratios,balancing local and RSU-based training.Meanwhile,setting an offloading threshold further prevents inefficiencies.Simulation results show that the enhanced algorithm reduces energy consumption and improves offloading efficiency and accuracy of federated SSL.展开更多
As the rapid development of automotive telematics,modern vehicles are expected to be connected through heterogeneous radio access technologies and are able to exchange massive information with their surrounding enviro...As the rapid development of automotive telematics,modern vehicles are expected to be connected through heterogeneous radio access technologies and are able to exchange massive information with their surrounding environment. By significantly expanding the network scale and conducting both real-time and long-term information processing, the traditional Vehicular AdHoc Networks(VANETs) are evolving to the Internet of Vehicles(Io V), which promises efficient and intelligent prospect for the future transportation system. On the other hand, vehicles are not only consuming but also generating a huge amount and enormous types of data, which is referred to as Big Data. In this article, we first investigate the relationship between Io V and big data in vehicular environment, mainly on how Io V supports the transmission, storage, computing of the big data, and how Io V benefits from big data in terms of Io V characterization,performance evaluation and big data assisted communication protocol design. We then investigate the application of Io V big data in autonomous vehicles. Finally, the emerging issues of the big data enabled Io V are discussed.展开更多
As an indispensable component of the emerging 6G networks,Space-Air-Ground Inte-grated Networks(SAGINs)are envisioned to provide ubiquitous network connectivity and services by integrating satellite networks,aerial ne...As an indispensable component of the emerging 6G networks,Space-Air-Ground Inte-grated Networks(SAGINs)are envisioned to provide ubiquitous network connectivity and services by integrating satellite networks,aerial networks,and terrestrial networks.In 6G SAGINs,a wide variety of network services with the features of diverse requirements,complex mobility,and multi-dimensional resources will pose great challenges to service provisioning,which urges the develop-ment of service-oriented SAGINs.In this paper,we conduct a comprehensive review of 6G SAGINs from a new perspective of service-oriented network.First,we present the requirements of service-oriented networks,and then propose a service-oriented SAGINs management architec-ture.Two categories of critical technologies are presented and discussed,i.e.,heterogeneous resource orchestration technologies and the cloud-edge synergy technologies,which facilitate the interoperability of different network segments and cooperatively orchestrate heterogeneous resources across different domains,according to the service features and requirements.In addition,the potential future research directions are also presented and discussed.展开更多
By leveraging the 5G enabled vehicular ad hoc network(5G-VANET), it is widely recognized that connected vehicles have the potentials to improve road safety, transportation intelligence and provide in-vehicle entertain...By leveraging the 5G enabled vehicular ad hoc network(5G-VANET), it is widely recognized that connected vehicles have the potentials to improve road safety, transportation intelligence and provide in-vehicle entertainment experience. However, many enabling applications in 5G-VANET rely on the efficient content sharing among mobile vehicles, which is a very challenging issue due to the extremely large data volume, rapid topology change, and unbalanced traffic. In this paper, we investigate content prefetching and distribution in 5G-VANET. We first introduce an edge computing based hierarchical architecture for efficient distribution of large-volume vehicular data. We then propose a multi-place multi-factor prefetching scheme to meet the rapid topology change and unbalanced traffic. The content requests of vehicles can be served by neighbors, which can improve the sharing efficiency and alleviate the burden of networks. Furthermore, we use a graph theory based approach to solve the content distribution by transforming it into a maximum weighted independent set problem. Finally, the proposed scheme is evaluated with a greedy transmission strategy to demonstrate its efficiency.展开更多
In this paper,to deal with the heterogeneity in federated learning(FL)systems,a knowledge distillation(KD)driven training framework for FL is proposed,where each user can select its neural network model on demand and ...In this paper,to deal with the heterogeneity in federated learning(FL)systems,a knowledge distillation(KD)driven training framework for FL is proposed,where each user can select its neural network model on demand and distill knowledge from a big teacher model using its own private dataset.To overcome the challenge of train the big teacher model in resource limited user devices,the digital twin(DT)is exploit in the way that the teacher model can be trained at DT located in the server with enough computing resources.Then,during model distillation,each user can update the parameters of its model at either the physical entity or the digital agent.The joint problem of model selection and training offloading and resource allocation for users is formulated as a mixed integer programming(MIP)problem.To solve the problem,Q-learning and optimization are jointly used,where Q-learning selects models for users and determines whether to train locally or on the server,and optimization is used to allocate resources for users based on the output of Q-learning.Simulation results show the proposed DT-assisted KD framework and joint optimization method can significantly improve the average accuracy of users while reducing the total delay.展开更多
Heterogeneous cellular networks(HCNs)are envisioned as a promising architecture to provide seamless wireless coverage and increase network capacity.However,the densified multi-tier network architecture introduces exce...Heterogeneous cellular networks(HCNs)are envisioned as a promising architecture to provide seamless wireless coverage and increase network capacity.However,the densified multi-tier network architecture introduces excessive intra-and cross-tier interference and makes HCNs vulnerable to eavesdropping attacks.In this article,a dynamic spectrum control(DSC)-assisted transmission scheme is proposed for HCNs to strengthen network security and increase the network capacity.Specifically,the proposed DSC-assisted transmission scheme leverages the idea of block cryptography to generate sequence families,which represent the transmission decisions,by performing iterative and orthogonal sequence transformations.Based on the sequence families,multiple users can dynamically occupy different frequency slots for data transmission simultaneously.In addition,the collision probability of the data transmission is analyzed,which results in closed-form expressions of the reliable transmission probability and the secrecy probability.Then,the upper and lower bounds of network capacity are further derived with given requirements on the reliable and secure transmission probabilities.Simulation results demonstrate that the proposed DSC-assisted scheme can outperform the benchmark scheme in terms of security performance.Finally,the impacts of key factors in the proposed DSC-assisted scheme on the network capacity and security are evaluated and discussed.展开更多
Road traffic congestion can inevitably de-grade road infrastructure and decrease travel efficiency in urban traffic networks,which can be relieved by employing appropriate congestion control.Accord-ing to different de...Road traffic congestion can inevitably de-grade road infrastructure and decrease travel efficiency in urban traffic networks,which can be relieved by employing appropriate congestion control.Accord-ing to different developmental driving forces,in this paper,the evolution of road traffic congestion control is divided into two stages.The ever-growing num-ber of advanced sensing techniques can be seen as the key driving force of the first stage,called the sens-ing stage,in which congestion control strategies ex-perienced rapid growth owing to the accessibility of traffic data.At the second stage,i.e.,the communica-tion stage,communication and computation capabil-ity can be regarded as the identifying symbols for this stage,where the ability of collecting finer-grained in-sight into transportation and mobility reality improves dramatically with advances in vehicular networks,Big Data,and artificial intelligence.Specifically,as the pre-requisite for congestion control,in this paper,ex-isting congestion detection techniques are first elab-orated and classified.Then,a comprehensive survey of the recent advances for current congestion control strategies with a focus on traffic signal control,vehi-cle route guidance,and their combined techniques is provided.In this regard,the evolution of these strate-gies with continuous development of sensing,com-munication,and computation capability are also intro-duced.Finally,the paper concludes with several re-search challenges and trends to fully promote the in-tegration of advanced techniques for traffic congestion mitigation in transportation systems.展开更多
Post-ischemic long-term potentiation （i-LTP） is a pathological form of plasticity that was observed in glutamate receptor-mediated neurotransmission after stroke and may exert a detrimental effect via facilitating e...Post-ischemic long-term potentiation （i-LTP） is a pathological form of plasticity that was observed in glutamate receptor-mediated neurotransmission after stroke and may exert a detrimental effect via facilitating excitotoxic damage. The mechanism underlying i-LTP, however, remains less understood. By employing electrophysiological recording and immunofluorescence assay on hippocampal slices and cultured neurons, we found that protein kinase M（（PKMζ）, an atypical protein kinase C isoform, was involved in enhancing aminomethyl phosphonic acid （AMPA） receptor （AMPAR） expression after i-LTP induction. PKMζ knockdown attenuated postsynaptic expression of AMPA receptors and disrupted i-LTP. Consistently, we observed less neuronal death of cultured hippocampal cells with PKMζ knockdown. Meanwhile, these findings indicate that PKMζ plays an important role in i-LTP by regulating postsynaptic expression of AMPA receptors. This work adds new knowledge to the mechanism of i-LTP, and thus is helpful to find the potential target for clinical therapy of ischemic stroke.展开更多
This paper investigates the tradeoff of the communication link and the eavesdropping link in covert communication in the presence of a full-duplex(FD)receiver.When a warden(Willie)attempts to detect the signal transmi...This paper investigates the tradeoff of the communication link and the eavesdropping link in covert communication in the presence of a full-duplex(FD)receiver.When a warden(Willie)attempts to detect the signal transmitted from a legitimate transmitter(Alice),the controllable FD receiver(Bob)can transmit with random power to impose interference uncertainty to Willie and force it to make an incorrect decision.To maximize the average transmission rate(ATR)of Alice-Bob and the average covert probability(ACP)for Willie,we propose a multi-objective optimization framework to optimize Bob’s power uncertainty range(PUR)and spatial position jointly,subject to the sufficient condition for covert communication and the none-deployed-zone(NDZ).Due to the presence of multiple optimization objectives and nonconvex constraints,the nondominated sorting genetic algorithm II(NSGA-II)is utilized to explore the Pareto front and to give a set of solutions that reflect tradeoffs between the two conflicting objectives.Simulation results reveal that the solutions determined by the NSGA-II have larger values for both ATR and ACP than the other two baselines.Simulations also show the positive effect of the width of the PUR of Bob on the Pareto front.展开更多
Wilson disease(WD),known as hepatolenticular degeneration(HLD),is a treatable autosomal recessive disorder of copper metabolism.Because copper deposits in the liver first,the liver is not only the original defective o...Wilson disease(WD),known as hepatolenticular degeneration(HLD),is a treatable autosomal recessive disorder of copper metabolism.Because copper deposits in the liver first,the liver is not only the original defective organ but also the most affected organ.The liver injury is also one of the main causes of death throughout the course of the disease.Therefore,the treatment of liver injury is the main task of WD treatment,which is of great significance to improve the prognosis of patients.Autophagy is a process that promotes cell survival through degradation,recycling,and absorption in order to maintain the normal physiological function of cells,while excessive autophagy can aggravate cell death.In view of the abnormal damage of liver cells in patients with WD,which may be related to the change of autophagy level,in this study,we established an animal model of WD through toxic milk(TX)mice,observed the change of autophagy level in the liver,and observed the change of liver damage in mice after treatment with autophagy inhibitors.It was found that the mTOR signaling pathway was activated and autophagy was inhibited in Wilson mouse liver.After treatment with rapamycin,the autophagy level of mice liver was upregulated,and the copper content of mice liver was reduced,and the damage was alleviated.TX mouse hepatocytes were isolated,after using siRNA to interfere with mTOR expression,the copper accumulation was significantly reduced,which was the same with RAPA treatment.The results showed that in TX mice,the damage caused by copper accumulation in the liver may be related to the decrease of autophagy level caused by the activation of the mTOR signaling pathway.Our findings suggested that RAPA or the use of siRNA targeting mTOR may have potential applications in the treatment of Wilson’s disease.展开更多
Climate change and the growing world population leading to agriculture and food safety are global challenges facing humanity,while biosensors have long been regarded as one of the powerful tools for providing solution...Climate change and the growing world population leading to agriculture and food safety are global challenges facing humanity,while biosensors have long been regarded as one of the powerful tools for providing solutions.Biosensors can aid in sustainable agriculture by providing continuous monitoring or early detection of disease outbreaks that can be averted.It also plays an important role in monitoring food risk factors such as pesticides,veterinary medications,heavy metals,pathogens,poisons,and illegal additions.Currently,this field includes a series of reviews covering the topic,but surprisingly,there tend to focus more on a single level and ignore the role across the food value chain.In this Perspective,we emphasized on the importance of all sectors from farm to fork for developing better biosensors.展开更多
Objective Elevated serum uric acid predicts poor outcomes in patients with cardiovascular disease.We aimed to examine associations between hyperuricemia and clinical outcomes among very elderly patients with non-valvu...Objective Elevated serum uric acid predicts poor outcomes in patients with cardiovascular disease.We aimed to examine associations between hyperuricemia and clinical outcomes among very elderly patients with non-valvular atrial fibrillation(NVAF).Methods Elderly patients(≥80 years)with NVAF admitted to our hospital from January 2009 to December 2015 were retrospectively studied and were followed up until April 2017.展开更多
文摘The authors regret that there were errors in the affiliations and the funding declaration in the original published version.The affiliations a and b of the original manuscript are"School of Information Engineering,Jiangxi Provincial Key Laboratory of Advanced Signal Processing and Intelligent Communications,Nanchang University,Nanchang 330031,China",and"School of Internet of Things Engineering,Jiangnan University,Wuxi 214122,China",respectively.The order of the two affiliations are not correct.
文摘Intelligent Transportation Systems(ITS)leverage Integrated Sensing and Communications(ISAC)to enhance data exchange between vehicles and infrastructure in the Internet of Vehicles(IoV).This integration inevitably increases computing demands,risking real-time system stability.Vehicle Edge Computing(VEC)addresses this by offloading tasks to Road Side Units(RSUs),ensuring timely services.Our previous work,the FLSimCo algorithm,which uses local resources for federated Self-Supervised Learning(SSL),has a limitation:vehicles often can’t complete all iteration tasks.Our improved algorithm offloads partial tasks to RSUs and optimizes energy consumption by adjusting transmission power,CPU frequency,and task assignment ratios,balancing local and RSU-based training.Meanwhile,setting an offloading threshold further prevents inefficiencies.Simulation results show that the enhanced algorithm reduces energy consumption and improves offloading efficiency and accuracy of federated SSL.
基金supported by the National Natural Science Foundation of China(91638204)Natural Sciences and Engineering Research Council(NSERC)
文摘As the rapid development of automotive telematics,modern vehicles are expected to be connected through heterogeneous radio access technologies and are able to exchange massive information with their surrounding environment. By significantly expanding the network scale and conducting both real-time and long-term information processing, the traditional Vehicular AdHoc Networks(VANETs) are evolving to the Internet of Vehicles(Io V), which promises efficient and intelligent prospect for the future transportation system. On the other hand, vehicles are not only consuming but also generating a huge amount and enormous types of data, which is referred to as Big Data. In this article, we first investigate the relationship between Io V and big data in vehicular environment, mainly on how Io V supports the transmission, storage, computing of the big data, and how Io V benefits from big data in terms of Io V characterization,performance evaluation and big data assisted communication protocol design. We then investigate the application of Io V big data in autonomous vehicles. Finally, the emerging issues of the big data enabled Io V are discussed.
基金supported by the National Key Research and Development Program of China(No.2020YFB1807700).
文摘As an indispensable component of the emerging 6G networks,Space-Air-Ground Inte-grated Networks(SAGINs)are envisioned to provide ubiquitous network connectivity and services by integrating satellite networks,aerial networks,and terrestrial networks.In 6G SAGINs,a wide variety of network services with the features of diverse requirements,complex mobility,and multi-dimensional resources will pose great challenges to service provisioning,which urges the develop-ment of service-oriented SAGINs.In this paper,we conduct a comprehensive review of 6G SAGINs from a new perspective of service-oriented network.First,we present the requirements of service-oriented networks,and then propose a service-oriented SAGINs management architec-ture.Two categories of critical technologies are presented and discussed,i.e.,heterogeneous resource orchestration technologies and the cloud-edge synergy technologies,which facilitate the interoperability of different network segments and cooperatively orchestrate heterogeneous resources across different domains,according to the service features and requirements.In addition,the potential future research directions are also presented and discussed.
基金the support of National Science and Technology Major Project of the Ministry of Science and Technology of China under Grant No.2016ZX03001025003the Natural Science Foundation of Beijing under Grant No.4181002+2 种基金the Natural Science Foundation of China under Grant No.91638204BUPT Excellent Ph.D. Students Foundation under Grant No.CX2018210Natural Sciences and Engineering Research Council (NSERC),Canada
文摘By leveraging the 5G enabled vehicular ad hoc network(5G-VANET), it is widely recognized that connected vehicles have the potentials to improve road safety, transportation intelligence and provide in-vehicle entertainment experience. However, many enabling applications in 5G-VANET rely on the efficient content sharing among mobile vehicles, which is a very challenging issue due to the extremely large data volume, rapid topology change, and unbalanced traffic. In this paper, we investigate content prefetching and distribution in 5G-VANET. We first introduce an edge computing based hierarchical architecture for efficient distribution of large-volume vehicular data. We then propose a multi-place multi-factor prefetching scheme to meet the rapid topology change and unbalanced traffic. The content requests of vehicles can be served by neighbors, which can improve the sharing efficiency and alleviate the burden of networks. Furthermore, we use a graph theory based approach to solve the content distribution by transforming it into a maximum weighted independent set problem. Finally, the proposed scheme is evaluated with a greedy transmission strategy to demonstrate its efficiency.
基金supported by the National Key Research and Development Program of China (2020YFB1807700)the National Natural Science Foundation of China (NSFC)under Grant No.62071356the Chongqing Key Laboratory of Mobile Communications Technology under Grant cqupt-mct202202。
文摘In this paper,to deal with the heterogeneity in federated learning(FL)systems,a knowledge distillation(KD)driven training framework for FL is proposed,where each user can select its neural network model on demand and distill knowledge from a big teacher model using its own private dataset.To overcome the challenge of train the big teacher model in resource limited user devices,the digital twin(DT)is exploit in the way that the teacher model can be trained at DT located in the server with enough computing resources.Then,during model distillation,each user can update the parameters of its model at either the physical entity or the digital agent.The joint problem of model selection and training offloading and resource allocation for users is formulated as a mixed integer programming(MIP)problem.To solve the problem,Q-learning and optimization are jointly used,where Q-learning selects models for users and determines whether to train locally or on the server,and optimization is used to allocate resources for users based on the output of Q-learning.Simulation results show the proposed DT-assisted KD framework and joint optimization method can significantly improve the average accuracy of users while reducing the total delay.
基金supported by the National Natural Science Foundation of China(61825104 and 91638204)the China Scholarship Council(CSC)+1 种基金the Natural Sciences and Engineering Research Council(NSERC)of CanadaUniversity Innovation Platform Project(2019921815KYPT009JC011)。
文摘Heterogeneous cellular networks(HCNs)are envisioned as a promising architecture to provide seamless wireless coverage and increase network capacity.However,the densified multi-tier network architecture introduces excessive intra-and cross-tier interference and makes HCNs vulnerable to eavesdropping attacks.In this article,a dynamic spectrum control(DSC)-assisted transmission scheme is proposed for HCNs to strengthen network security and increase the network capacity.Specifically,the proposed DSC-assisted transmission scheme leverages the idea of block cryptography to generate sequence families,which represent the transmission decisions,by performing iterative and orthogonal sequence transformations.Based on the sequence families,multiple users can dynamically occupy different frequency slots for data transmission simultaneously.In addition,the collision probability of the data transmission is analyzed,which results in closed-form expressions of the reliable transmission probability and the secrecy probability.Then,the upper and lower bounds of network capacity are further derived with given requirements on the reliable and secure transmission probabilities.Simulation results demonstrate that the proposed DSC-assisted scheme can outperform the benchmark scheme in terms of security performance.Finally,the impacts of key factors in the proposed DSC-assisted scheme on the network capacity and security are evaluated and discussed.
基金the National Key R&D Program of China(2019YFB1600100)National Nat-ural Science Foundation of China(U1801266)the Youth Innovation Team of Shaanxi Universities.
文摘Road traffic congestion can inevitably de-grade road infrastructure and decrease travel efficiency in urban traffic networks,which can be relieved by employing appropriate congestion control.Accord-ing to different developmental driving forces,in this paper,the evolution of road traffic congestion control is divided into two stages.The ever-growing num-ber of advanced sensing techniques can be seen as the key driving force of the first stage,called the sens-ing stage,in which congestion control strategies ex-perienced rapid growth owing to the accessibility of traffic data.At the second stage,i.e.,the communica-tion stage,communication and computation capabil-ity can be regarded as the identifying symbols for this stage,where the ability of collecting finer-grained in-sight into transportation and mobility reality improves dramatically with advances in vehicular networks,Big Data,and artificial intelligence.Specifically,as the pre-requisite for congestion control,in this paper,ex-isting congestion detection techniques are first elab-orated and classified.Then,a comprehensive survey of the recent advances for current congestion control strategies with a focus on traffic signal control,vehi-cle route guidance,and their combined techniques is provided.In this regard,the evolution of these strate-gies with continuous development of sensing,com-munication,and computation capability are also intro-duced.Finally,the paper concludes with several re-search challenges and trends to fully promote the in-tegration of advanced techniques for traffic congestion mitigation in transportation systems.
基金supported by grants to W.L.From the Major State Basic Research Program of China(2013CB733801)the Priority Academic Program Development of Jiangsu Higher Education Institutions and the Open Research Fund of State Key Laboratory of Bioelectronics,Southeast University
文摘Post-ischemic long-term potentiation （i-LTP） is a pathological form of plasticity that was observed in glutamate receptor-mediated neurotransmission after stroke and may exert a detrimental effect via facilitating excitotoxic damage. The mechanism underlying i-LTP, however, remains less understood. By employing electrophysiological recording and immunofluorescence assay on hippocampal slices and cultured neurons, we found that protein kinase M（（PKMζ）, an atypical protein kinase C isoform, was involved in enhancing aminomethyl phosphonic acid （AMPA） receptor （AMPAR） expression after i-LTP induction. PKMζ knockdown attenuated postsynaptic expression of AMPA receptors and disrupted i-LTP. Consistently, we observed less neuronal death of cultured hippocampal cells with PKMζ knockdown. Meanwhile, these findings indicate that PKMζ plays an important role in i-LTP by regulating postsynaptic expression of AMPA receptors. This work adds new knowledge to the mechanism of i-LTP, and thus is helpful to find the potential target for clinical therapy of ischemic stroke.
基金This work was supported by the National Natural Science Foundation of China under Grant 62101403,61825104,and 61901328by the University Innovation Platform Project under Grant 2019921815KYPT009JC011by the Industry-University-Academy Cooperation Program of Xidian University-Chongqing IC Innovation Research Institute under grant CQIRI-2021CXY-Z07.
文摘This paper investigates the tradeoff of the communication link and the eavesdropping link in covert communication in the presence of a full-duplex(FD)receiver.When a warden(Willie)attempts to detect the signal transmitted from a legitimate transmitter(Alice),the controllable FD receiver(Bob)can transmit with random power to impose interference uncertainty to Willie and force it to make an incorrect decision.To maximize the average transmission rate(ATR)of Alice-Bob and the average covert probability(ACP)for Willie,we propose a multi-objective optimization framework to optimize Bob’s power uncertainty range(PUR)and spatial position jointly,subject to the sufficient condition for covert communication and the none-deployed-zone(NDZ).Due to the presence of multiple optimization objectives and nonconvex constraints,the nondominated sorting genetic algorithm II(NSGA-II)is utilized to explore the Pareto front and to give a set of solutions that reflect tradeoffs between the two conflicting objectives.Simulation results reveal that the solutions determined by the NSGA-II have larger values for both ATR and ACP than the other two baselines.Simulations also show the positive effect of the width of the PUR of Bob on the Pareto front.
基金supported by Natural Science Foundation of Anhui Province(1908085MH266)National Natural Science Foundation of China(81673948).
文摘Wilson disease(WD),known as hepatolenticular degeneration(HLD),is a treatable autosomal recessive disorder of copper metabolism.Because copper deposits in the liver first,the liver is not only the original defective organ but also the most affected organ.The liver injury is also one of the main causes of death throughout the course of the disease.Therefore,the treatment of liver injury is the main task of WD treatment,which is of great significance to improve the prognosis of patients.Autophagy is a process that promotes cell survival through degradation,recycling,and absorption in order to maintain the normal physiological function of cells,while excessive autophagy can aggravate cell death.In view of the abnormal damage of liver cells in patients with WD,which may be related to the change of autophagy level,in this study,we established an animal model of WD through toxic milk(TX)mice,observed the change of autophagy level in the liver,and observed the change of liver damage in mice after treatment with autophagy inhibitors.It was found that the mTOR signaling pathway was activated and autophagy was inhibited in Wilson mouse liver.After treatment with rapamycin,the autophagy level of mice liver was upregulated,and the copper content of mice liver was reduced,and the damage was alleviated.TX mouse hepatocytes were isolated,after using siRNA to interfere with mTOR expression,the copper accumulation was significantly reduced,which was the same with RAPA treatment.The results showed that in TX mice,the damage caused by copper accumulation in the liver may be related to the decrease of autophagy level caused by the activation of the mTOR signaling pathway.Our findings suggested that RAPA or the use of siRNA targeting mTOR may have potential applications in the treatment of Wilson’s disease.
基金supported by funding from the Natural Science Foundation of China(Grant No.32001787)the 2115 Talent Development Program of China Agricultural University.
文摘Climate change and the growing world population leading to agriculture and food safety are global challenges facing humanity,while biosensors have long been regarded as one of the powerful tools for providing solutions.Biosensors can aid in sustainable agriculture by providing continuous monitoring or early detection of disease outbreaks that can be averted.It also plays an important role in monitoring food risk factors such as pesticides,veterinary medications,heavy metals,pathogens,poisons,and illegal additions.Currently,this field includes a series of reviews covering the topic,but surprisingly,there tend to focus more on a single level and ignore the role across the food value chain.In this Perspective,we emphasized on the importance of all sectors from farm to fork for developing better biosensors.
文摘Objective Elevated serum uric acid predicts poor outcomes in patients with cardiovascular disease.We aimed to examine associations between hyperuricemia and clinical outcomes among very elderly patients with non-valvular atrial fibrillation(NVAF).Methods Elderly patients(≥80 years)with NVAF admitted to our hospital from January 2009 to December 2015 were retrospectively studied and were followed up until April 2017.
