Nitric oxide(NO)is a second messenger playing crucial roles in the signaling of a variety of cellular functions.Due to its pathophysiological significance,various NO modulators have been developed to explore NO pathwa...Nitric oxide(NO)is a second messenger playing crucial roles in the signaling of a variety of cellular functions.Due to its pathophysiological significance,various NO modulators have been developed to explore NO pathways and some have been used as therapies.These modulators are often used directly to observe pharmacological effects in cell lines,but their actual effect on intracellular NO level is seldom analyzed.Herein,facilitated by a selective and sensitive fluorescence probe,we observed that some NO modulators displayed unexpected behaviors with both NO scavenger carboxy-PTIO and endothelial nitric oxide synthase(eNOS)inhibitor N(u)-nitro-L-arginine methyl ester(L-NAME)failing to decrease intracellular free NO level in EA.hy926 cells while NO donor diethylamine-NONOate(DEA$NONOate)and eNOS activator calcimycin(A23187)failing to increase free NO level in human umbilical vein endothelial cell line(HUV-EC-C),although the reagents were confirmed to work normally in the primary human umbilical vein endothelial cells(primary HUVECs)and RAW 264.7 macrophage cells.Further research suggested that these unusual behaviors might be attributed to the cellular microenvironments including both the NO synthase(NOS)level and the endogenous glutathione(GSH)level.Genetically manipulating eNOS level in both cells restores the expected response,while decreasing GSH level restores the ability of DEA$NONOate to increase NO level in HUV-EC-C.These results reveal that the cellular microenvironment has a profound impact on pharmacological effect.Our study suggests GSH as a reservoir for NO in live cells and highlights the value of chemical probes as valuable tools to reveal microenvironmentdependent pharmacological effects.展开更多
针对退役动力电池规模大、单体筛选复杂、重组后动态特性差异大以及寿命损耗加剧等问题,该文考虑电池模组的功能状态(state of function,SOF)特性,提出基于数字孪生技术的退役电池模组筛选方法。首先,通过电压、电流、荷电状态(state of...针对退役动力电池规模大、单体筛选复杂、重组后动态特性差异大以及寿命损耗加剧等问题,该文考虑电池模组的功能状态(state of function,SOF)特性,提出基于数字孪生技术的退役电池模组筛选方法。首先,通过电压、电流、荷电状态(state of charge,SOC)及健康状态(state of health,SOH)等参量表征SOF特性,估计梯次利用过程中SOF动态安全裕度;其次,搭建耦合物理模型、信息流及数字孪生映射体的电池模组筛选架构,提出基于生成对抗网络(generative adversarial networks,GAN)与长短期记忆网络(long short-term memory,LSTM)的电池数据缺失及偏移预测方法,优化退役动力电池模组表征SOF的多性能参量;最后,采用k-means算法对综合考虑SOH及SOF特性的退役电池模组进行聚类筛选。仿真结果表明:所提筛选方法可以提高退役动力电池动态一致性,并延长梯次利用过程中电池的运行寿命。展开更多
针对退役动力电池梯次用于电力系统等领域存在初始参数不一致、筛选重组复杂等问题,提出一种基于退役动力电池模组静动态特性的阶梯式筛选方法。首先,构建退役动力电池模组端电压、荷电状态(state of charge,SOC)、健康状态(state of he...针对退役动力电池梯次用于电力系统等领域存在初始参数不一致、筛选重组复杂等问题,提出一种基于退役动力电池模组静动态特性的阶梯式筛选方法。首先,构建退役动力电池模组端电压、荷电状态(state of charge,SOC)、健康状态(state of health,SOH)及循环次数等参数间的关联特性,以电池模组内阻、剩余容量作为表征参数,采用密度权重Canopy改进的K-medoids聚类方法对外部特性参数相近的电池模组进行初次筛选;其次,将电池模组SOH动态一致性特性曲线作为表征对象,对其进行再次筛选;最后,采用非参数Bootstrap概率方法解析阶梯式静动态筛选下退役动力SOH估计的置信区间,评估动力电池模组筛选精度。结果表明,该文所提方法可将电池模组的筛选精度至少提高6.2%,为退役动力电池大规模筛选及梯次利用奠定理论基础。展开更多
基金We greatly appreciate the financial support from the National Natural Science Foundations of China(21778048,81673489,31871414,U1703235)the National Key R&D Program of China(2019ZX09201001-003-010)+1 种基金the Natural Science Foundation of Zhejiang Province,China(LR18H300001)Shanghai Science and Technology Development Funds(19YF1457500).
文摘Nitric oxide(NO)is a second messenger playing crucial roles in the signaling of a variety of cellular functions.Due to its pathophysiological significance,various NO modulators have been developed to explore NO pathways and some have been used as therapies.These modulators are often used directly to observe pharmacological effects in cell lines,but their actual effect on intracellular NO level is seldom analyzed.Herein,facilitated by a selective and sensitive fluorescence probe,we observed that some NO modulators displayed unexpected behaviors with both NO scavenger carboxy-PTIO and endothelial nitric oxide synthase(eNOS)inhibitor N(u)-nitro-L-arginine methyl ester(L-NAME)failing to decrease intracellular free NO level in EA.hy926 cells while NO donor diethylamine-NONOate(DEA$NONOate)and eNOS activator calcimycin(A23187)failing to increase free NO level in human umbilical vein endothelial cell line(HUV-EC-C),although the reagents were confirmed to work normally in the primary human umbilical vein endothelial cells(primary HUVECs)and RAW 264.7 macrophage cells.Further research suggested that these unusual behaviors might be attributed to the cellular microenvironments including both the NO synthase(NOS)level and the endogenous glutathione(GSH)level.Genetically manipulating eNOS level in both cells restores the expected response,while decreasing GSH level restores the ability of DEA$NONOate to increase NO level in HUV-EC-C.These results reveal that the cellular microenvironment has a profound impact on pharmacological effect.Our study suggests GSH as a reservoir for NO in live cells and highlights the value of chemical probes as valuable tools to reveal microenvironmentdependent pharmacological effects.
文摘针对退役动力电池规模大、单体筛选复杂、重组后动态特性差异大以及寿命损耗加剧等问题,该文考虑电池模组的功能状态(state of function,SOF)特性,提出基于数字孪生技术的退役电池模组筛选方法。首先,通过电压、电流、荷电状态(state of charge,SOC)及健康状态(state of health,SOH)等参量表征SOF特性,估计梯次利用过程中SOF动态安全裕度;其次,搭建耦合物理模型、信息流及数字孪生映射体的电池模组筛选架构,提出基于生成对抗网络(generative adversarial networks,GAN)与长短期记忆网络(long short-term memory,LSTM)的电池数据缺失及偏移预测方法,优化退役动力电池模组表征SOF的多性能参量;最后,采用k-means算法对综合考虑SOH及SOF特性的退役电池模组进行聚类筛选。仿真结果表明:所提筛选方法可以提高退役动力电池动态一致性,并延长梯次利用过程中电池的运行寿命。
文摘针对退役动力电池梯次用于电力系统等领域存在初始参数不一致、筛选重组复杂等问题,提出一种基于退役动力电池模组静动态特性的阶梯式筛选方法。首先,构建退役动力电池模组端电压、荷电状态(state of charge,SOC)、健康状态(state of health,SOH)及循环次数等参数间的关联特性,以电池模组内阻、剩余容量作为表征参数,采用密度权重Canopy改进的K-medoids聚类方法对外部特性参数相近的电池模组进行初次筛选;其次,将电池模组SOH动态一致性特性曲线作为表征对象,对其进行再次筛选;最后,采用非参数Bootstrap概率方法解析阶梯式静动态筛选下退役动力SOH估计的置信区间,评估动力电池模组筛选精度。结果表明,该文所提方法可将电池模组的筛选精度至少提高6.2%,为退役动力电池大规模筛选及梯次利用奠定理论基础。
