Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important a...Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important and scarce network resources such as bandwidth and processing power.There have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial losses.This paper draws its motivation from such real network disaster incidents attributed to signaling storms.In this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and countermeasures.We provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding solutions.Another important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a table.This paper presents an update and an extension of our earlier conference publication.To our knowledge,no similar survey study exists on the subject.展开更多
The rapid advancement of 6G communication technologies and generative artificial intelligence(AI)is catalyzing a new wave of innovation at the intersection of networking and intelligent computing.On the one hand,6G en...The rapid advancement of 6G communication technologies and generative artificial intelligence(AI)is catalyzing a new wave of innovation at the intersection of networking and intelligent computing.On the one hand,6G envisions a hyper-connected environment that supports ubiquitous intelligence through ultra-low latency,high throughput,massive device connectivity,and integrated sensing and communication.On the other hand,generative AI,powered by large foundation models,has emerged as a powerful paradigm capable of creating.展开更多
Altermagnets,a class of unconventional antiferromagnets with non-relativistic spin-splitting,offer promising potential for antiferromagnetic spintronic devices.While many altermagnets are limited by either low magneti...Altermagnets,a class of unconventional antiferromagnets with non-relativistic spin-splitting,offer promising potential for antiferromagnetic spintronic devices.While many altermagnets are limited by either low magnetic transition temperatures or weak spin splitting,the recently discovered metal CrSb,with high N′eel temperature(T_(N)=710 K)and significant spin-splitting due to its unique spin space group,provides a robust platform for remarkable tunneling magnetoresistance(TMR)in collinear all-antiferromagnetic tunnel junctions(AATJs).This study systematically investigates the spin-polarized Fermi surface of CrSb and spin-dependent electron transport in CrSb-based AATJs.The CrSb/β-InSe/CrSb junction with a three-monolayer InSe barrier exhibits a TMR ratio of approximately 290%,with energy-dependent analysis revealing TMR ratios that may exceed 850%when considering the shift of the Fermi energy.We also demonstrate the angle-dependent TMR of CrSb-based AATJs by adjusting N′eel vector orientations.Our findings might provide strong theoretical support for CrSb as a versatile building block for all-antiferromagnetic memory devices.展开更多
Osteosarcoma(OS)is the most frequent primary bone sarcomas with high recurrence and poor prognosis.Emerging evidence indicates that membraneless organelles stress granules(SGs),whose assemblies are driven by scaffold ...Osteosarcoma(OS)is the most frequent primary bone sarcomas with high recurrence and poor prognosis.Emerging evidence indicates that membraneless organelles stress granules(SGs),whose assemblies are driven by scaffold protein G3BP1,are extensively involved in tumor,especially in OS.However,how SGs behave and communicate with organelles,particularly nucleoli and mitochondria,during drug challenges remain unknown.This study revealed that chemotherapeutic drugs activated the cysteine protease asparagine endopeptidase(AEP)to specifically cleave the SG core protein G3BP1 at N258/N309 in OS and malignant glioma.tG3BP1-Ns modulated SG dynamics by competitively binding to full-length G3BP1.Strikingly,tG3BP1-Cs,containing a conserved RNA recognition motif CCUBSCUS,sequestered mRNAs of ribosomal proteins and oxidative phosphorylation genes in the nucleoli and mitochondria to repress translation and oxidative stress.Moreover,the inhibition of AEP promoted the tumor-suppressing effect of chemotherapeutic drugs,whereas AEP-cleaved G3BP1 rescue reversed the effect in both OS and glioma models.Cancerous tissues exhibited high levels of AEP and G3BP1 truncations,which were strongly associated with poor prognosis.展开更多
The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-gener...The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.展开更多
GNAO1-associated disorder is a rare disease and an example of developmental and epileptic encephalopathies.Caused by ca.150 different dominant missense mutations in the gene encoding the major neuronal G protein Gao,i...GNAO1-associated disorder is a rare disease and an example of developmental and epileptic encephalopathies.Caused by ca.150 different dominant missense mutations in the gene encoding the major neuronal G protein Gao,it spans a wide range of neurological clinical manifestations,that may include epileptic seizures,motor dysfunctions,developmental and intellectual delay,and other symptoms(Sáez González et al.,2023).展开更多
The envisioned 6G wireless networks demand advanced Multiple Access (MA) schemes capable of supporting ultra-low latency, massive connectivity, high spectral efficiency, and energy efficiency (EE), especially as the c...The envisioned 6G wireless networks demand advanced Multiple Access (MA) schemes capable of supporting ultra-low latency, massive connectivity, high spectral efficiency, and energy efficiency (EE), especially as the current 5G networks have not achieved the promised 5G goals, including the projected 2000 times EE improvement over the legacy 4G Long Term Evolution (LTE) networks. This paper provides a comprehensive survey of Artificial Intelligence (AI)-enabled MA techniques, emphasizing their roles in Spectrum Sensing (SS), Dynamic Resource Allocation (DRA), user scheduling, interference mitigation, and protocol adaptation. In particular, we systematically analyze the progression of traditional and modern MA schemes, from Orthogonal Multiple Access (OMA)-based approaches like Time Division Multiple Access (TDMA) and Frequency Division Multiple Access (FDMA) to advanced Non-Orthogonal Multiple Access (NOMA) methods, including power domain-NOMA, Sparse Code Multiple Access (SCMA), and Rate Splitting Multiple Access (RSMA). The study further categorizes AI techniques—such as Machine Learning (ML), Deep Learning (DL), Reinforcement Learning (RL), Federated Learning (FL), and Explainable AI (XAI)—and maps them to practical challenges in Dynamic Spectrum Management (DSM), protocol optimization, and real-time distributed decision-making. Optimization strategies, including metaheuristics and multi-agent learning frameworks, are reviewed to illustrate the potential of AI in enhancing energy efficiency, system responsiveness, and cross-layer RA. Additionally, the review addresses security, privacy, and trust concerns, highlighting solutions like privacy-preserving ML, FL, and XAI in 6G and beyond. By identifying research gaps, challenges, and future directions, this work offers a structured resource for researchers and practitioners aiming to integrate AI into 6G MA systems for intelligent, scalable, and secure wireless communications.展开更多
IgG4相关性疾病(immunoglobulin-G4 related disease,IgG4-RD)是一种免疫介导的慢性纤维炎性疾病,可累及多个系统及器官。目前IgG4-RD合并恶性肿瘤且累及同一部位的病例鲜有报道。本文报道1例72岁男性患者,以肾脏肿瘤入院,结合镜检、免...IgG4相关性疾病(immunoglobulin-G4 related disease,IgG4-RD)是一种免疫介导的慢性纤维炎性疾病,可累及多个系统及器官。目前IgG4-RD合并恶性肿瘤且累及同一部位的病例鲜有报道。本文报道1例72岁男性患者,以肾脏肿瘤入院,结合镜检、免疫表型及血清学测定最终诊断为肾透明细胞肾细胞癌合并IgG4-RD。由于IgG4-RD缺少临床特异性,容易在诊治过程中被忽略,本例意在提示IgG4-RD与肿瘤同时存在的可能性,且两者之间的发生可能存在相关性,为诊断及研究提供新的思路,避免漏诊及误诊。展开更多
The 6G smart Fog Radio Access Network(F-RAN)is an integration of 6G network intelligence technologies and the F-RAN architecture.Its aim is to provide low-latency and high-performance services for massive access devic...The 6G smart Fog Radio Access Network(F-RAN)is an integration of 6G network intelligence technologies and the F-RAN architecture.Its aim is to provide low-latency and high-performance services for massive access devices.However,the performance of current 6G network intelligence technologies and its level of integration with the architecture,along with the system-level requirements for the number of access devices and limitations on energy consumption,have impeded further improvements in the 6G smart F-RAN.To better analyze the root causes of the network problems and promote the practical development of the network,this study used structured methods such as segmentation to conduct a review of the topic.The research results reveal that there are still many problems in the current 6G smart F-RAN.Future research directions and difficulties are also discussed.展开更多
Osteoarthritis(OA)is a prevalent degenerative joint disorder marked by chronic pain,inflammation,and cartilage loss,with current treatments limited to symptom relief.G protein-coupled receptors(GPCRs)play a pivotal ro...Osteoarthritis(OA)is a prevalent degenerative joint disorder marked by chronic pain,inflammation,and cartilage loss,with current treatments limited to symptom relief.G protein-coupled receptors(GPCRs)play a pivotal role in OA progression by regulating inflammation,chondrocyte survival,and matrix homeostasis.However,their multifaceted signaling,via G proteins orβ-arrestins,poses challenges for precise therapeutic targeting.Biased agonism,where ligands selectively activate specific GPCR pathways,emerges as a promising approach to optimize efficacy and reduce side effects.This review examines biased signaling in OAassociated GPCRs,including cannabinoid receptors(CB1,CB2),chemokine receptors(CCR2,CXCR4),protease-activated receptors(PAR-2),adenosine receptors(A1R,A2AR,A2BR,A3R),melanocortin receptors(MC1R,MC3R),bradykinin receptors(B2R),prostaglandin E2 receptors(EP-2,EP-4),and calcium-sensing receptors(CaSR).We analyze ligands in clinical trials and explore natural products from Traditional Chinese Medicine as potential biased agonists.These compounds,with diverse structures and bioactivities,offer novel therapeutic avenues.By harnessing biased agonism,this review underscores the potential for developing targeted,safer OA therapies that address its complex pathology,bridging molecular insights with clinical translation.展开更多
We work within a Winterberg framework where space, i.e., the vacuum, consists of a two component superfluid/super-solid made up of a vast assembly (sea) of positive and negative mass Planck particles, called planckion...We work within a Winterberg framework where space, i.e., the vacuum, consists of a two component superfluid/super-solid made up of a vast assembly (sea) of positive and negative mass Planck particles, called planckions. These material particles interact indirectly, and have very strong restoring forces keeping them a finite distance apart from each other within their respective species. Because of their mass compensating effect, the vacuum appears massless, charge-less, without pressure, net energy density or entropy. In addition, we consider two varying G models, where G, is Newton’s constant, and G<sup>-1</sup>, increases with an increase in cosmological time. We argue that there are at least two competing models for the quantum vacuum within such a framework. The first follows a strict extension of Winterberg’s model. This leads to nonsensible results, if G increases, going back in cosmological time, as the length scale inherent in such a model will not scale properly. The second model introduces a different length scale, which does scale properly, but keeps the mass of the Planck particle as, ± the Planck mass. Moreover we establish a connection between ordinary matter, dark matter, and dark energy, where all three mass densities within the Friedman equation must be interpreted as residual vacuum energies, which only surface, once aggregate matter has formed, at relatively low CMB temperatures. The symmetry of the vacuum will be shown to be broken, because of the different scaling laws, beginning with the formation of elementary particles. Much like waves on an ocean where positive and negative planckion mass densities effectively cancel each other out and form a zero vacuum energy density/zero vacuum pressure surface, these positive mass densities are very small perturbations (anomalies) about the mean. This greatly alleviates, i.e., minimizes the cosmological constant problem, a long standing problem associated with the vacuum.展开更多
Dear Editor,This letter proposes a dynamic switching soft slicing strategy for industrial mixed traffic in 5G networks. Considering two types of traffic, periodic delay-sensitive (PDS) traffic and sporadic delay-toler...Dear Editor,This letter proposes a dynamic switching soft slicing strategy for industrial mixed traffic in 5G networks. Considering two types of traffic, periodic delay-sensitive (PDS) traffic and sporadic delay-tolerant (SDT) traffic, we design a dynamic switching strategy based on a traffic-Qo S-aware soft slicing (TQASS) scheme and a resource-efficiency-aware soft slicing (REASS) scheme.展开更多
The G20 Leaders’Summit will be held in South Africa in late November.As the presiding nation,South Africa has held or will host a total of 132 o"cial meetings this year,aiming to address the most pressing challe...The G20 Leaders’Summit will be held in South Africa in late November.As the presiding nation,South Africa has held or will host a total of 132 o"cial meetings this year,aiming to address the most pressing challenges facing the world,particularly those a!ecting countries in the Global South.In recent years,hunger and poverty have remained persistent challenges globally.Despite impressive economic growth in many countries,millions still su!er from food insecurity,malnutrition,and extreme poverty,particularly in the Global South.Recognising this,the G20 has launched a key initiative,the Global Alliance Against Hunger and Poverty(GAAHP),aimed at accelerating progress towards the United Nations Sustainable Development Goals(SDGs),specifically SDG 1(no poverty),SDG 2(zero hunger),and related goals focused on reducing inequality and fostering global partnerships.展开更多
Magnetic resonance imaging(MRI)plays an important role in medical diagnosis,generating petabytes of image data annually in large hospitals.This voluminous data stream requires a significant amount of network bandwidth...Magnetic resonance imaging(MRI)plays an important role in medical diagnosis,generating petabytes of image data annually in large hospitals.This voluminous data stream requires a significant amount of network bandwidth and extensive storage infrastructure.Additionally,local data processing demands substantial manpower and hardware investments.Data isolation across different healthcare institutions hinders crossinstitutional collaboration in clinics and research.In this work,we anticipate an innovative MRI system and its four generations that integrate emerging distributed cloud computing,6G bandwidth,edge computing,federated learning,and blockchain technology.This system is called Cloud-MRI,aiming at solving the problems of MRI data storage security,transmission speed,artificial intelligence(AI)algorithm maintenance,hardware upgrading,and collaborative work.The workflow commences with the transformation of k-space raw data into the standardized Imaging Society for Magnetic Resonance in Medicine Raw Data(ISMRMRD)format.Then,the data are uploaded to the cloud or edge nodes for fast image reconstruction,neural network training,and automatic analysis.Then,the outcomes are seamlessly transmitted to clinics or research institutes for diagnosis and other services.The Cloud-MRI system will save the raw imaging data,reduce the risk of data loss,facilitate inter-institutional medical collaboration,and finally improve diagnostic accuracy and work efficiency.展开更多
基金the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2024-9/1).
文摘Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important and scarce network resources such as bandwidth and processing power.There have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial losses.This paper draws its motivation from such real network disaster incidents attributed to signaling storms.In this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and countermeasures.We provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding solutions.Another important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a table.This paper presents an update and an extension of our earlier conference publication.To our knowledge,no similar survey study exists on the subject.
文摘The rapid advancement of 6G communication technologies and generative artificial intelligence(AI)is catalyzing a new wave of innovation at the intersection of networking and intelligent computing.On the one hand,6G envisions a hyper-connected environment that supports ubiquitous intelligence through ultra-low latency,high throughput,massive device connectivity,and integrated sensing and communication.On the other hand,generative AI,powered by large foundation models,has emerged as a powerful paradigm capable of creating.
基金supported by the National Natural Science Foundation of China(Grant Nos.T2394475,T2394470,T2394471,and 12174129)the China Postdoctoral Science Foundation(Grant No.2023M741269).
文摘Altermagnets,a class of unconventional antiferromagnets with non-relativistic spin-splitting,offer promising potential for antiferromagnetic spintronic devices.While many altermagnets are limited by either low magnetic transition temperatures or weak spin splitting,the recently discovered metal CrSb,with high N′eel temperature(T_(N)=710 K)and significant spin-splitting due to its unique spin space group,provides a robust platform for remarkable tunneling magnetoresistance(TMR)in collinear all-antiferromagnetic tunnel junctions(AATJs).This study systematically investigates the spin-polarized Fermi surface of CrSb and spin-dependent electron transport in CrSb-based AATJs.The CrSb/β-InSe/CrSb junction with a three-monolayer InSe barrier exhibits a TMR ratio of approximately 290%,with energy-dependent analysis revealing TMR ratios that may exceed 850%when considering the shift of the Fermi energy.We also demonstrate the angle-dependent TMR of CrSb-based AATJs by adjusting N′eel vector orientations.Our findings might provide strong theoretical support for CrSb as a versatile building block for all-antiferromagnetic memory devices.
基金supported by the National Key R&D Program of China(grant number 2023ZD0502206,2024YFB3213200,Topic No.2024YFB3213204)National Natural Science Foundation of China(nos.82273278,82373514,82373202,82272728,82002630,81772654)+5 种基金the National Key Research and Development Program of China(grant number 2022YFC2404602)Shanghai Hospital Development Center Foundation(grant number SHDC12023108)Scientific and Technological Innovation Action Plan of Shanghai Science and Technology Committee(grant number 22Y31900103)Beijing Science and Technology Innovation Medical Development Foundation(grant number KC2021-JX-0170-9)the Shanghai Association for Science and Technology(nos.201409003000,201409002400,20YF1426200)Shanghai Science and Technology Innovation Action Plan(grant number 23Y41900100).
文摘Osteosarcoma(OS)is the most frequent primary bone sarcomas with high recurrence and poor prognosis.Emerging evidence indicates that membraneless organelles stress granules(SGs),whose assemblies are driven by scaffold protein G3BP1,are extensively involved in tumor,especially in OS.However,how SGs behave and communicate with organelles,particularly nucleoli and mitochondria,during drug challenges remain unknown.This study revealed that chemotherapeutic drugs activated the cysteine protease asparagine endopeptidase(AEP)to specifically cleave the SG core protein G3BP1 at N258/N309 in OS and malignant glioma.tG3BP1-Ns modulated SG dynamics by competitively binding to full-length G3BP1.Strikingly,tG3BP1-Cs,containing a conserved RNA recognition motif CCUBSCUS,sequestered mRNAs of ribosomal proteins and oxidative phosphorylation genes in the nucleoli and mitochondria to repress translation and oxidative stress.Moreover,the inhibition of AEP promoted the tumor-suppressing effect of chemotherapeutic drugs,whereas AEP-cleaved G3BP1 rescue reversed the effect in both OS and glioma models.Cancerous tissues exhibited high levels of AEP and G3BP1 truncations,which were strongly associated with poor prognosis.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2025-00559546)supported by the IITP(Institute of Information&Coummunications Technology Planning&Evaluation)-ITRC(Information Technology Research Center)grant funded by the Korea government(Ministry of Science and ICT)(IITP-2025-RS-2023-00259004).
文摘The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.
文摘GNAO1-associated disorder is a rare disease and an example of developmental and epileptic encephalopathies.Caused by ca.150 different dominant missense mutations in the gene encoding the major neuronal G protein Gao,it spans a wide range of neurological clinical manifestations,that may include epileptic seizures,motor dysfunctions,developmental and intellectual delay,and other symptoms(Sáez González et al.,2023).
文摘The envisioned 6G wireless networks demand advanced Multiple Access (MA) schemes capable of supporting ultra-low latency, massive connectivity, high spectral efficiency, and energy efficiency (EE), especially as the current 5G networks have not achieved the promised 5G goals, including the projected 2000 times EE improvement over the legacy 4G Long Term Evolution (LTE) networks. This paper provides a comprehensive survey of Artificial Intelligence (AI)-enabled MA techniques, emphasizing their roles in Spectrum Sensing (SS), Dynamic Resource Allocation (DRA), user scheduling, interference mitigation, and protocol adaptation. In particular, we systematically analyze the progression of traditional and modern MA schemes, from Orthogonal Multiple Access (OMA)-based approaches like Time Division Multiple Access (TDMA) and Frequency Division Multiple Access (FDMA) to advanced Non-Orthogonal Multiple Access (NOMA) methods, including power domain-NOMA, Sparse Code Multiple Access (SCMA), and Rate Splitting Multiple Access (RSMA). The study further categorizes AI techniques—such as Machine Learning (ML), Deep Learning (DL), Reinforcement Learning (RL), Federated Learning (FL), and Explainable AI (XAI)—and maps them to practical challenges in Dynamic Spectrum Management (DSM), protocol optimization, and real-time distributed decision-making. Optimization strategies, including metaheuristics and multi-agent learning frameworks, are reviewed to illustrate the potential of AI in enhancing energy efficiency, system responsiveness, and cross-layer RA. Additionally, the review addresses security, privacy, and trust concerns, highlighting solutions like privacy-preserving ML, FL, and XAI in 6G and beyond. By identifying research gaps, challenges, and future directions, this work offers a structured resource for researchers and practitioners aiming to integrate AI into 6G MA systems for intelligent, scalable, and secure wireless communications.
文摘IgG4相关性疾病(immunoglobulin-G4 related disease,IgG4-RD)是一种免疫介导的慢性纤维炎性疾病,可累及多个系统及器官。目前IgG4-RD合并恶性肿瘤且累及同一部位的病例鲜有报道。本文报道1例72岁男性患者,以肾脏肿瘤入院,结合镜检、免疫表型及血清学测定最终诊断为肾透明细胞肾细胞癌合并IgG4-RD。由于IgG4-RD缺少临床特异性,容易在诊治过程中被忽略,本例意在提示IgG4-RD与肿瘤同时存在的可能性,且两者之间的发生可能存在相关性,为诊断及研究提供新的思路,避免漏诊及误诊。
基金supported by the National Natural Science Foundation of China(62202215)Liaoning Province Applied Basic Research Program(Youth Special Project,2023JH2/101600038)+2 种基金Shenyang Youth Science and Technology Innovation Talent Support Program(RC220458)Guangxuan Program of Shenyang Ligong University(SYLUGXRC202216)Basic Research Special Funds for Undergraduate Universities in Liaoning Province(LJ212410144067).
文摘The 6G smart Fog Radio Access Network(F-RAN)is an integration of 6G network intelligence technologies and the F-RAN architecture.Its aim is to provide low-latency and high-performance services for massive access devices.However,the performance of current 6G network intelligence technologies and its level of integration with the architecture,along with the system-level requirements for the number of access devices and limitations on energy consumption,have impeded further improvements in the 6G smart F-RAN.To better analyze the root causes of the network problems and promote the practical development of the network,this study used structured methods such as segmentation to conduct a review of the topic.The research results reveal that there are still many problems in the current 6G smart F-RAN.Future research directions and difficulties are also discussed.
基金supported by the National Key R&D Program of the Ministry of Science and Technology(2023YFC2509900)National Natural Science Foundation of China(82374106)+3 种基金National Natural Science Foundation of China(U22A20371)the Basic and Applied Basic Research Fund of Guangdong Province(2021B1515120061)the Shenzhen Science and Technology Innovation Committee(JCYJ20210324102006017)SZ-HK Joint Laboratory for Innovative Biomaterials under CAS-HK Joint Laboratories(2024-2028).
文摘Osteoarthritis(OA)is a prevalent degenerative joint disorder marked by chronic pain,inflammation,and cartilage loss,with current treatments limited to symptom relief.G protein-coupled receptors(GPCRs)play a pivotal role in OA progression by regulating inflammation,chondrocyte survival,and matrix homeostasis.However,their multifaceted signaling,via G proteins orβ-arrestins,poses challenges for precise therapeutic targeting.Biased agonism,where ligands selectively activate specific GPCR pathways,emerges as a promising approach to optimize efficacy and reduce side effects.This review examines biased signaling in OAassociated GPCRs,including cannabinoid receptors(CB1,CB2),chemokine receptors(CCR2,CXCR4),protease-activated receptors(PAR-2),adenosine receptors(A1R,A2AR,A2BR,A3R),melanocortin receptors(MC1R,MC3R),bradykinin receptors(B2R),prostaglandin E2 receptors(EP-2,EP-4),and calcium-sensing receptors(CaSR).We analyze ligands in clinical trials and explore natural products from Traditional Chinese Medicine as potential biased agonists.These compounds,with diverse structures and bioactivities,offer novel therapeutic avenues.By harnessing biased agonism,this review underscores the potential for developing targeted,safer OA therapies that address its complex pathology,bridging molecular insights with clinical translation.
文摘We work within a Winterberg framework where space, i.e., the vacuum, consists of a two component superfluid/super-solid made up of a vast assembly (sea) of positive and negative mass Planck particles, called planckions. These material particles interact indirectly, and have very strong restoring forces keeping them a finite distance apart from each other within their respective species. Because of their mass compensating effect, the vacuum appears massless, charge-less, without pressure, net energy density or entropy. In addition, we consider two varying G models, where G, is Newton’s constant, and G<sup>-1</sup>, increases with an increase in cosmological time. We argue that there are at least two competing models for the quantum vacuum within such a framework. The first follows a strict extension of Winterberg’s model. This leads to nonsensible results, if G increases, going back in cosmological time, as the length scale inherent in such a model will not scale properly. The second model introduces a different length scale, which does scale properly, but keeps the mass of the Planck particle as, ± the Planck mass. Moreover we establish a connection between ordinary matter, dark matter, and dark energy, where all three mass densities within the Friedman equation must be interpreted as residual vacuum energies, which only surface, once aggregate matter has formed, at relatively low CMB temperatures. The symmetry of the vacuum will be shown to be broken, because of the different scaling laws, beginning with the formation of elementary particles. Much like waves on an ocean where positive and negative planckion mass densities effectively cancel each other out and form a zero vacuum energy density/zero vacuum pressure surface, these positive mass densities are very small perturbations (anomalies) about the mean. This greatly alleviates, i.e., minimizes the cosmological constant problem, a long standing problem associated with the vacuum.
基金supported by the Liaoning Revitalization Talents Program(XLYC2203148)
文摘Dear Editor,This letter proposes a dynamic switching soft slicing strategy for industrial mixed traffic in 5G networks. Considering two types of traffic, periodic delay-sensitive (PDS) traffic and sporadic delay-tolerant (SDT) traffic, we design a dynamic switching strategy based on a traffic-Qo S-aware soft slicing (TQASS) scheme and a resource-efficiency-aware soft slicing (REASS) scheme.
文摘The G20 Leaders’Summit will be held in South Africa in late November.As the presiding nation,South Africa has held or will host a total of 132 o"cial meetings this year,aiming to address the most pressing challenges facing the world,particularly those a!ecting countries in the Global South.In recent years,hunger and poverty have remained persistent challenges globally.Despite impressive economic growth in many countries,millions still su!er from food insecurity,malnutrition,and extreme poverty,particularly in the Global South.Recognising this,the G20 has launched a key initiative,the Global Alliance Against Hunger and Poverty(GAAHP),aimed at accelerating progress towards the United Nations Sustainable Development Goals(SDGs),specifically SDG 1(no poverty),SDG 2(zero hunger),and related goals focused on reducing inequality and fostering global partnerships.
基金supported by the National Natural Science Foundation of China(62122064,62331021,62371410)the Natural Science Foundation of Fujian Province of China(2023J02005 and 2021J011184)+1 种基金the President Fund of Xiamen University(20720220063)the Nanqiang Outstanding Talents Program of Xiamen University.
文摘Magnetic resonance imaging(MRI)plays an important role in medical diagnosis,generating petabytes of image data annually in large hospitals.This voluminous data stream requires a significant amount of network bandwidth and extensive storage infrastructure.Additionally,local data processing demands substantial manpower and hardware investments.Data isolation across different healthcare institutions hinders crossinstitutional collaboration in clinics and research.In this work,we anticipate an innovative MRI system and its four generations that integrate emerging distributed cloud computing,6G bandwidth,edge computing,federated learning,and blockchain technology.This system is called Cloud-MRI,aiming at solving the problems of MRI data storage security,transmission speed,artificial intelligence(AI)algorithm maintenance,hardware upgrading,and collaborative work.The workflow commences with the transformation of k-space raw data into the standardized Imaging Society for Magnetic Resonance in Medicine Raw Data(ISMRMRD)format.Then,the data are uploaded to the cloud or edge nodes for fast image reconstruction,neural network training,and automatic analysis.Then,the outcomes are seamlessly transmitted to clinics or research institutes for diagnosis and other services.The Cloud-MRI system will save the raw imaging data,reduce the risk of data loss,facilitate inter-institutional medical collaboration,and finally improve diagnostic accuracy and work efficiency.
