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
Healthcare security and privacy breaches are occurring in the United States (US), and increased substantially during the pandemic. This paper reviews the National Institute of Standards and Technology (NIST) publicati...Healthcare security and privacy breaches are occurring in the United States (US), and increased substantially during the pandemic. This paper reviews the National Institute of Standards and Technology (NIST) publication base as an effective solution. The NIST Special Publication 800-66 Revision 1 was an essential standard in US healthcare, which was withdrawn in February 2024 and superseded by SP 800-66 Revision 2. This review investigates the academic papers concerning the application of the NIST SP 800-66 Revision 1 standard in the US healthcare literature. A systematic review method was used in this study to determine current knowledge gaps of the SP 800-66 Revision 1. Some limitations were employed in the search to enforce validity. A total of eleven articles were found eligible for the study. Consequently, this study suggests the necessity for additional academic papers pertaining to SP 800-66 Revision 2 in the US healthcare literature. In turn, it will enhance awareness of safeguarding electronic protected health information (ePHI), help to mitigate potential future risks, and eventually reduce breaches.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.
文摘Healthcare security and privacy breaches are occurring in the United States (US), and increased substantially during the pandemic. This paper reviews the National Institute of Standards and Technology (NIST) publication base as an effective solution. The NIST Special Publication 800-66 Revision 1 was an essential standard in US healthcare, which was withdrawn in February 2024 and superseded by SP 800-66 Revision 2. This review investigates the academic papers concerning the application of the NIST SP 800-66 Revision 1 standard in the US healthcare literature. A systematic review method was used in this study to determine current knowledge gaps of the SP 800-66 Revision 1. Some limitations were employed in the search to enforce validity. A total of eleven articles were found eligible for the study. Consequently, this study suggests the necessity for additional academic papers pertaining to SP 800-66 Revision 2 in the US healthcare literature. In turn, it will enhance awareness of safeguarding electronic protected health information (ePHI), help to mitigate potential future risks, and eventually reduce breaches.
