目的探究N-乙酰半胱氨酸对支气管哮喘大鼠CXC趋化因子配体(CXCL)8-CXC趋化因子受体(CXCR)1/2及瞬时受体电位通道蛋白(TRP)V1神经元敏感性的影响。方法选取80只SPF级SD雄性大鼠,随机分为正常(NO)组、模型(MO)组、N-乙酰半胱氨酸(NAC)组...目的探究N-乙酰半胱氨酸对支气管哮喘大鼠CXC趋化因子配体(CXCL)8-CXC趋化因子受体(CXCR)1/2及瞬时受体电位通道蛋白(TRP)V1神经元敏感性的影响。方法选取80只SPF级SD雄性大鼠,随机分为正常(NO)组、模型(MO)组、N-乙酰半胱氨酸(NAC)组、急支糖浆(ES)组,每组20只,对MO组、NAC组、ES组进行支气管哮喘建模,建模成功后,NAC组、ES组每天分别于腹腔内注射2 ml N-乙酰半胱氨酸注射液、急支糖浆灌胃10 g/kg剂量,NO组、MO组同期灌胃同体积生理盐水,通过苏木素-伊红(HE)染色法检测肺组织病理形态、酶联免疫吸附试验(ELISA)、实时荧光定量聚合酶链反应(RT-PCR)、Western印迹检测血清及肺组织中CXCL8、CXCR1、CXCR2、TRPV1含量、mRNA及蛋白表达,并分析N-乙酰半胱氨酸对支气管哮喘大鼠CXCL8-CXCR1/2及TRPV1神经元敏感性。结果与NO组相比,MO组咳嗽次数明显增加(P<0.05),而NAC组、ES组与MO组相比,其咳嗽次数明显降低(P<0.05),且NAC组比ES组降低明显(P<0.05);与NO组相比,MO组细支气管管腔、肺泡腔内可见渗出液、脱落的上皮细胞等,远端肺泡可见局部肺不张及周围肺大泡,且肺间质明显增厚,炎性细胞浸润明显,而与MO组比较,ES组、NAC组症状明显减少,部分肺间质的组织结构趋向正常,部分肺泡轻度扩张,且NAC组比ES组明显降低(P<0.05);与NO组对比,MO组CXCL8、CXCR1、CXCR2、TRPV1含量、mRNA及蛋白表达均明显升高(P<0.05),NAC组、ES组与MO组相比均显著降低(P<0.05),且NAC组比ES组明显降低(P<0.05)。结论N-乙酰半胱氨酸可以显著降低咳嗽次数,减少支气管哮喘症状,可使CXCL8-CXCR1/2及TRPV1神经元敏感性显著降低。展开更多
城市电网涵盖多个电压等级,调度操作复杂,为降低城市电网N-1后的运行风险,同时解决N-1-1发生时导致大面积停电的问题,提出一种转供区域识别方法,并结合研究场景对其进行分区处理,在保证求解准确度的前提下提高问题求解效率。提出降低城...城市电网涵盖多个电压等级,调度操作复杂,为降低城市电网N-1后的运行风险,同时解决N-1-1发生时导致大面积停电的问题,提出一种转供区域识别方法,并结合研究场景对其进行分区处理,在保证求解准确度的前提下提高问题求解效率。提出降低城市电网N-1-1运行风险拓扑重构双层优化模型,综合考虑了N-1-1时的负荷损失量和N-1后节点电压偏移量与设备负载率均衡度,使用二进制蝙蝠算法(Binary Bat Algorithm,BBA)对模型进行求解。最后通过某地区实际城市电网算例分析,验证了所提模型的有效性。展开更多
The N-1 criterion is a critical factor for ensuring the reliable and resilient operation of electric power distribution networks.However,the increasing complexity of distribution networks and the associated growth in ...The N-1 criterion is a critical factor for ensuring the reliable and resilient operation of electric power distribution networks.However,the increasing complexity of distribution networks and the associated growth in data size have created a significant challenge for distribution network planners.To address this issue,we propose a fast N-1 verification procedure for urban distribution networks that combines CIM file data analysis with MILP-based mathematical modeling.Our proposed method leverages the principles of CIM file analysis for distribution network N-1 analysis.We develop a mathematical model of distribution networks based on CIM data and transfer it into MILP.We also take into account the characteristics of medium voltage distribution networks after a line failure and select the feeder section at the exit of each substation with a high load rate to improve the efficiency of N-1 analysis.We validate our approach through a series of case studies and demonstrate its scalability and superiority over traditional N-1 analysis and heuristic optimization algorithms.By enabling online N-1 analysis,our approach significantly improves the work efficiency of distribution network planners.In summary,our proposed method provides a valuable tool for distribution network planners to enhance the accuracy and efficiency of their N-1 analyses.By leveraging the advantages of CIM file data analysis and MILP-based mathematical modeling,our approach contributes to the development of more resilient and reliable electric power distribution networks.展开更多
文摘目的探究N-乙酰半胱氨酸对支气管哮喘大鼠CXC趋化因子配体(CXCL)8-CXC趋化因子受体(CXCR)1/2及瞬时受体电位通道蛋白(TRP)V1神经元敏感性的影响。方法选取80只SPF级SD雄性大鼠,随机分为正常(NO)组、模型(MO)组、N-乙酰半胱氨酸(NAC)组、急支糖浆(ES)组,每组20只,对MO组、NAC组、ES组进行支气管哮喘建模,建模成功后,NAC组、ES组每天分别于腹腔内注射2 ml N-乙酰半胱氨酸注射液、急支糖浆灌胃10 g/kg剂量,NO组、MO组同期灌胃同体积生理盐水,通过苏木素-伊红(HE)染色法检测肺组织病理形态、酶联免疫吸附试验(ELISA)、实时荧光定量聚合酶链反应(RT-PCR)、Western印迹检测血清及肺组织中CXCL8、CXCR1、CXCR2、TRPV1含量、mRNA及蛋白表达,并分析N-乙酰半胱氨酸对支气管哮喘大鼠CXCL8-CXCR1/2及TRPV1神经元敏感性。结果与NO组相比,MO组咳嗽次数明显增加(P<0.05),而NAC组、ES组与MO组相比,其咳嗽次数明显降低(P<0.05),且NAC组比ES组降低明显(P<0.05);与NO组相比,MO组细支气管管腔、肺泡腔内可见渗出液、脱落的上皮细胞等,远端肺泡可见局部肺不张及周围肺大泡,且肺间质明显增厚,炎性细胞浸润明显,而与MO组比较,ES组、NAC组症状明显减少,部分肺间质的组织结构趋向正常,部分肺泡轻度扩张,且NAC组比ES组明显降低(P<0.05);与NO组对比,MO组CXCL8、CXCR1、CXCR2、TRPV1含量、mRNA及蛋白表达均明显升高(P<0.05),NAC组、ES组与MO组相比均显著降低(P<0.05),且NAC组比ES组明显降低(P<0.05)。结论N-乙酰半胱氨酸可以显著降低咳嗽次数,减少支气管哮喘症状,可使CXCL8-CXCR1/2及TRPV1神经元敏感性显著降低。
文摘城市电网涵盖多个电压等级,调度操作复杂,为降低城市电网N-1后的运行风险,同时解决N-1-1发生时导致大面积停电的问题,提出一种转供区域识别方法,并结合研究场景对其进行分区处理,在保证求解准确度的前提下提高问题求解效率。提出降低城市电网N-1-1运行风险拓扑重构双层优化模型,综合考虑了N-1-1时的负荷损失量和N-1后节点电压偏移量与设备负载率均衡度,使用二进制蝙蝠算法(Binary Bat Algorithm,BBA)对模型进行求解。最后通过某地区实际城市电网算例分析,验证了所提模型的有效性。
基金supported by the National Natural Science Foundation of China(52207105)。
文摘The N-1 criterion is a critical factor for ensuring the reliable and resilient operation of electric power distribution networks.However,the increasing complexity of distribution networks and the associated growth in data size have created a significant challenge for distribution network planners.To address this issue,we propose a fast N-1 verification procedure for urban distribution networks that combines CIM file data analysis with MILP-based mathematical modeling.Our proposed method leverages the principles of CIM file analysis for distribution network N-1 analysis.We develop a mathematical model of distribution networks based on CIM data and transfer it into MILP.We also take into account the characteristics of medium voltage distribution networks after a line failure and select the feeder section at the exit of each substation with a high load rate to improve the efficiency of N-1 analysis.We validate our approach through a series of case studies and demonstrate its scalability and superiority over traditional N-1 analysis and heuristic optimization algorithms.By enabling online N-1 analysis,our approach significantly improves the work efficiency of distribution network planners.In summary,our proposed method provides a valuable tool for distribution network planners to enhance the accuracy and efficiency of their N-1 analyses.By leveraging the advantages of CIM file data analysis and MILP-based mathematical modeling,our approach contributes to the development of more resilient and reliable electric power distribution networks.
