以IL-1α、TNF-α、PGE2、TRPV1、透明质酸酶为指标,采用体外试验对β-葡聚糖,5种不同分子质量透明质酸钠(HA)(400 Da、800 Da、<10 k Da、200~400 k Da、1000~1300 k Da)及β-葡聚糖分别与5种不同分子质量HA组合物的舒缓功效进行评...以IL-1α、TNF-α、PGE2、TRPV1、透明质酸酶为指标,采用体外试验对β-葡聚糖,5种不同分子质量透明质酸钠(HA)(400 Da、800 Da、<10 k Da、200~400 k Da、1000~1300 k Da)及β-葡聚糖分别与5种不同分子质量HA组合物的舒缓功效进行评价,并以金氏公式计算组合物的协同舒缓作用。结果显示,单一β-葡聚糖、5种不同分子质量HA均具有显著舒缓功效,其中400 Da HA舒缓功效最为显著,对透明质酸酶、IL-1α、TNF-α、PGE2、TRPV1抑制率分别为16.94%、27.60%、34.36%、62.53%、44.90%。组合物功效结果显示,β-葡聚糖与400 Da HA在抑制IL-1α、TRPV1试验中表现出协同作用,q值分别为1.38、1.28,为功效显著的舒缓组合物。展开更多
In 6th Generation Mobile Networks(6G),the Space-Integrated-Ground(SIG)Radio Access Network(RAN)promises seamless coverage and exceptionally high Quality of Service(QoS)for diverse services.However,achieving this neces...In 6th Generation Mobile Networks(6G),the Space-Integrated-Ground(SIG)Radio Access Network(RAN)promises seamless coverage and exceptionally high Quality of Service(QoS)for diverse services.However,achieving this necessitates effective management of computation and wireless resources tailored to the requirements of various services.The heterogeneity of computation resources and interference among shared wireless resources pose significant coordination and management challenges.To solve these problems,this work provides an overview of multi-dimensional resource management in 6G SIG RAN,including computation and wireless resource.Firstly it provides with a review of current investigations on computation and wireless resource management and an analysis of existing deficiencies and challenges.Then focusing on the provided challenges,the work proposes an MEC-based computation resource management scheme and a mixed numerology-based wireless resource management scheme.Furthermore,it outlines promising future technologies,including joint model-driven and data-driven resource management technology,and blockchain-based resource management technology within the 6G SIG network.The work also highlights remaining challenges,such as reducing communication costs associated with unstable ground-to-satellite links and overcoming barriers posed by spectrum isolation.Overall,this comprehensive approach aims to pave the way for efficient and effective resource management in future 6G networks.展开更多
文摘以IL-1α、TNF-α、PGE2、TRPV1、透明质酸酶为指标,采用体外试验对β-葡聚糖,5种不同分子质量透明质酸钠(HA)(400 Da、800 Da、<10 k Da、200~400 k Da、1000~1300 k Da)及β-葡聚糖分别与5种不同分子质量HA组合物的舒缓功效进行评价,并以金氏公式计算组合物的协同舒缓作用。结果显示,单一β-葡聚糖、5种不同分子质量HA均具有显著舒缓功效,其中400 Da HA舒缓功效最为显著,对透明质酸酶、IL-1α、TNF-α、PGE2、TRPV1抑制率分别为16.94%、27.60%、34.36%、62.53%、44.90%。组合物功效结果显示,β-葡聚糖与400 Da HA在抑制IL-1α、TRPV1试验中表现出协同作用,q值分别为1.38、1.28,为功效显著的舒缓组合物。
基金supported by the National Key Research and Development Program of China(No.2021YFB2900504).
文摘In 6th Generation Mobile Networks(6G),the Space-Integrated-Ground(SIG)Radio Access Network(RAN)promises seamless coverage and exceptionally high Quality of Service(QoS)for diverse services.However,achieving this necessitates effective management of computation and wireless resources tailored to the requirements of various services.The heterogeneity of computation resources and interference among shared wireless resources pose significant coordination and management challenges.To solve these problems,this work provides an overview of multi-dimensional resource management in 6G SIG RAN,including computation and wireless resource.Firstly it provides with a review of current investigations on computation and wireless resource management and an analysis of existing deficiencies and challenges.Then focusing on the provided challenges,the work proposes an MEC-based computation resource management scheme and a mixed numerology-based wireless resource management scheme.Furthermore,it outlines promising future technologies,including joint model-driven and data-driven resource management technology,and blockchain-based resource management technology within the 6G SIG network.The work also highlights remaining challenges,such as reducing communication costs associated with unstable ground-to-satellite links and overcoming barriers posed by spectrum isolation.Overall,this comprehensive approach aims to pave the way for efficient and effective resource management in future 6G networks.
