Transforming growth factor-beta 1(TGF-β1)has been extensively studied for its pleiotropic effects on central nervous system diseases.The neuroprotective or neurotoxic effects of TGF-β1 in specific brain areas may de...Transforming growth factor-beta 1(TGF-β1)has been extensively studied for its pleiotropic effects on central nervous system diseases.The neuroprotective or neurotoxic effects of TGF-β1 in specific brain areas may depend on the pathological process and cell types involved.Voltage-gated sodium channels(VGSCs)are essential ion channels for the generation of action potentials in neurons,and are involved in various neuroexcitation-related diseases.However,the effects of TGF-β1 on the functional properties of VGSCs and firing properties in cortical neurons remain unclear.In this study,we investigated the effects of TGF-β1 on VGSC function and firing properties in primary cortical neurons from mice.We found that TGF-β1 increased VGSC current density in a dose-and time-dependent manner,which was attributable to the upregulation of Nav1.3 expression.Increased VGSC current density and Nav1.3 expression were significantly abolished by preincubation with inhibitors of mitogen-activated protein kinase kinase(PD98059),p38 mitogen-activated protein kinase(SB203580),and Jun NH2-terminal kinase 1/2 inhibitor(SP600125).Interestingly,TGF-β1 significantly increased the firing threshold of action potentials but did not change their firing rate in cortical neurons.These findings suggest that TGF-β1 can increase Nav1.3 expression through activation of the ERK1/2-JNK-MAPK pathway,which leads to a decrease in the firing threshold of action potentials in cortical neurons under pathological conditions.Thus,this contributes to the occurrence and progression of neuroexcitatory-related diseases of the central nervous system.展开更多
近年来,三维数字底座在城市空间监测和城市规划中的应用越来越广泛,如何快速构建大场景三维底座成为研究重点。本文研究了一种基于多源数据的建筑物LoD1.3级模型快速构建方法,通过建筑物DLG数据约束提取建筑物点云数据,计算顶部高程,基...近年来,三维数字底座在城市空间监测和城市规划中的应用越来越广泛,如何快速构建大场景三维底座成为研究重点。本文研究了一种基于多源数据的建筑物LoD1.3级模型快速构建方法,通过建筑物DLG数据约束提取建筑物点云数据,计算顶部高程,基于DEM数据提取建筑物底部高程,基于DLG、底部高程、顶部高程进行三维拉伸建模,实现了城市大场景建筑物LoD1.3级模型快速构建。实验表明:本文构建0.8 km 2建筑物密集区LoD1.3级三维模型耗时56.11 s,三维模型高程中误差为2.19 m,且具备属性信息。本文提出的基于多源数据的建筑物LoD1.3级模型快速构建方法已在实景三维常州建设中得到应用,有效提升了全域建筑三维模型建设效率。展开更多
基金supported by the Natural Science Foundation of Guangdong Province,Nos.2019A1515010649(to WC),2022A1515012044(to JS)the China Postdoctoral Science Foundation,No.2018M633091(to JS).
文摘Transforming growth factor-beta 1(TGF-β1)has been extensively studied for its pleiotropic effects on central nervous system diseases.The neuroprotective or neurotoxic effects of TGF-β1 in specific brain areas may depend on the pathological process and cell types involved.Voltage-gated sodium channels(VGSCs)are essential ion channels for the generation of action potentials in neurons,and are involved in various neuroexcitation-related diseases.However,the effects of TGF-β1 on the functional properties of VGSCs and firing properties in cortical neurons remain unclear.In this study,we investigated the effects of TGF-β1 on VGSC function and firing properties in primary cortical neurons from mice.We found that TGF-β1 increased VGSC current density in a dose-and time-dependent manner,which was attributable to the upregulation of Nav1.3 expression.Increased VGSC current density and Nav1.3 expression were significantly abolished by preincubation with inhibitors of mitogen-activated protein kinase kinase(PD98059),p38 mitogen-activated protein kinase(SB203580),and Jun NH2-terminal kinase 1/2 inhibitor(SP600125).Interestingly,TGF-β1 significantly increased the firing threshold of action potentials but did not change their firing rate in cortical neurons.These findings suggest that TGF-β1 can increase Nav1.3 expression through activation of the ERK1/2-JNK-MAPK pathway,which leads to a decrease in the firing threshold of action potentials in cortical neurons under pathological conditions.Thus,this contributes to the occurrence and progression of neuroexcitatory-related diseases of the central nervous system.
文摘近年来,三维数字底座在城市空间监测和城市规划中的应用越来越广泛,如何快速构建大场景三维底座成为研究重点。本文研究了一种基于多源数据的建筑物LoD1.3级模型快速构建方法,通过建筑物DLG数据约束提取建筑物点云数据,计算顶部高程,基于DEM数据提取建筑物底部高程,基于DLG、底部高程、顶部高程进行三维拉伸建模,实现了城市大场景建筑物LoD1.3级模型快速构建。实验表明:本文构建0.8 km 2建筑物密集区LoD1.3级三维模型耗时56.11 s,三维模型高程中误差为2.19 m,且具备属性信息。本文提出的基于多源数据的建筑物LoD1.3级模型快速构建方法已在实景三维常州建设中得到应用,有效提升了全域建筑三维模型建设效率。
