还原型谷胱甘肽对肝硬化患者上消化道大出血前后血中GSH-Px/LPO比值的影响

目的　观察肝硬化患者上消化道大出血前后血中谷胱甘肽 (GSH)水平和谷胱甘肽过氧化物酶 (Se GSH Px)活性与过氧化脂质 (LPO)比值的动态变化及还原型谷胱甘肽治疗的影响。方法　 57例患者随机分为常规治疗和还原型谷胱甘肽防治两组 ,前者给常规止血、保肝治疗 ,后者在常规治疗基础上加用还原型谷胱甘肽静滴 (1.2g·d- 1,连用3～ 4周 )。定时空腹采血 ,测定血中GSH水平、Se GSH Px活性和LPO含量 ,并观察记录两组患者发生腹水或腹水增多、黄疸或黄疸加深、肝性脑病和病死 4个病情恶化指标的累计频次数。结果　上消化道出血后常规治疗组患者血中GSH水平、Se GSH Px/LPO比值均明显下降 ,72h达最低点 ,2周后开始回升。还原型谷胱甘肽防治组上述损伤改变较小 ,回升快 ,2周后显著恢复 ,4周后即可达到出血前水平。还原型谷胱甘肽防治组患者 4个病情恶化指标的累计频次数明显低于常规治疗组 (2 4/ 2 7;41/ 3 0 ,P <0 .0 1) ,且与Child Pugh分级有关 ,B级优于C级 (6/ 12 ;17/ 7,P <0 .0 1)。结论　肝硬化患者上消化道大出血后体内抗氧化能力降低 ,致患者的病情恶化。抗氧化治疗有积极意义     

成人界嵴形态与组织结构的观察

目的　观察和测量人右心房界嵴和梳状肌的形态和组织结构 ,以探讨其可能的功能。方法　肉眼观察、测量界嵴与梳状肌的有关形态学数据。利用光学显微镜 ,通过HE、Masson和磷钨酸 苏木素染色 ,对界嵴的细胞形态和纤维方向等进行细致观察。结果　①根据界嵴的隆起状况 ,界嵴可分为 4类 :A .全程隆起 (18.6 % ) ;B .上 2 / 3隆起 ,下1/ 3平坦 (2 7.9% ) ;C .上 1/ 3隆起 ,下 2 / 3平坦 (34.88% ) ;D .全程平坦 (18.6 % )。②界嵴的肌纤维可分深、浅两层 ,深层肌纤维纵行 ,与界嵴长轴平行 ;浅层纤维横行 ,仅见于界嵴的中、下部 ,深 浅层纤维之间互相联系。在界嵴各处可见P样细胞。③根据梳状肌的起止和走行 ,梳状肌可分为 3型 :汇聚型、网状型和混合型。结论　窦房结上、下及其深面借过渡纤维与界嵴的普通肌纤维相互联系 ,界嵴纤维可能与结间冲动传导有关。梳状肌走行方向的多样性 ,可能与临床上心脏电流传导的多向异性有关     

白细胞介素-12对哮喘患者Th细胞的作用

目的　观察白细胞介素 12 (IL 12 )对哮喘患者辅助性T淋巴细胞 (Th)的分化和细胞因子分泌的影响 ,探讨IL 12对哮喘治疗的机制及应用。方法　从哮喘患者外周血分离出单核细胞和CD4 + T(Th)细胞 ,单核细胞被尘螨变应原刺激活化后同CD4 + T细胞分别与 1μg·L-1和 5 μg·L-1IL 12共培养 ,对照组不加IL 12。 72h后收集培养上清 ,ELISA法检测IL 4、IL 5和IFN γ的生成量。培养细胞用荧光标记的单克隆抗体染色 ,流式细胞仪 (FCM)检测细胞内特异性细胞因子。结果　与对照组相比 ,实验组IL 4、IL 5的产生量明显减少 ,IFN γ的产生量显著增加 (P <0 .0 1) ,而且这种变化趋势在 1μg·L-1、5 μg·L-1IL 12间也有统计学差异 (P <0 .0 5 )。实验组Th1/Th2向Th1方向漂移 ,Th1/Th2增加 (P<0 .0 1)。结论　IL 12可调节Th的分化方向及不同类型细胞因子的分泌 ,并在一定浓度范围内呈量效依赖性。提示IL 12可作为一种新的哮喘治疗途径     

THE GENE EXPRESSION OF BDNF IN NORMAL RABBIT RETINA

Objective To investigate the distribution of brain-derived neurotrophic factor(BDNF) protein in the rabbit retina. Methods Immune response material in the retina was observed using BDNF antibody by the method of immunohistochemistry. Results BDNF gene expression was mainly found in the RGCs, also in innernuclei cells and outernuclei cells in rabbit retina. Conclusion RGC is not only the target cell of BDNF, but also express the BDNF protein. BDNF from multi-sources participates in the regulation of RGCs.     

基于SOM的我国民用机场分类研究

科学准确地对民用机场分类可以将机场自身定位,为机场发展及评估提供可靠依据,具有重要的现实意义。本文选用了15个影响我国机场分类的关键因素,运用神经网络技术中的自组织映射(Self-Organizing Map,文中简称SOM)将我国民用机场进行了细分,并分析了各类机场的特点。结果表明,SOM能很好地应用于我国民用机场分类,是一种科学、有效的分类方法。     

天津西站公交车场轻质泡沫混凝土换填工程设计及应用

轻质泡沫混凝土是一项新技术、新材料、新工艺,目前国内外都非常重视泡沫混凝土的研究与开发,在建筑工程和市政工程领域的应用越来越广。针对天津西站南广场公交车场轻质泡沫混凝土换填工程施工特点,在基坑抗隆起检算的基础上,对轻质泡沫混凝土换填设计、压缩力学性能分析、轻质泡沫混凝土换填施工工艺以及换填效果等进行了详细阐述,可为类似工程施工提供一定的参考价值。     

城市道路沥青路面补强设计方案浅析

抚顺市城市道路建设近年来有了很大发展,但城市道路使用到一定年限后,如果使用性能降低,就要及时进行补强。以抚顺市城市道路沥青路面补强设计的现状为基础,探讨了合理的沥青路面补强设计方案。     

不确定箱重下内河集装箱班轮航线配载决策

与集装箱海运相比内河集装箱班轮运输具有其独特性,同时对于内贸箱而言,货主订舱时箱重信息的不确定性导致其航线配载决策变得更加复杂.本文考虑不确定箱重影响,以最小化航线班轮堆栈占用数量为目标,构建内河集装箱班轮航线配载决策的随机规划模型.为实现求解,基于随机规划理论,采用机会约束描述随机约束,将随机规划模型转化为随机机会约束规划模型,并设计混合邻域搜索算法求解.算法由蒙特卡罗随机模拟、神经元网络训练及邻域搜索启发式3个部分组成.算例研究表明,混合邻域搜索算法的鲁棒性较好,可实现配载计划对不确定因素的有效吸收.     

Adaptive Multi-Objective Optimization of Bionic Shoulder Joint Based on Particle Swarm Optimization

To get the movement mode and driving mechanism similar to human shoulder joint, a six degrees of freedom (DOF) serial-parallel bionic shoulder joint mechanism driven by pneumatic muscle actuators (PMAs) was designed. However, the structural parameters of the shoulder joint will affect various performances of the mechanism. To obtain the optimal structure parameters, the particle swarm optimization (PSO) was used. Besides, the mathematical expressions of indexes of rotation ranges, maximum bearing torque, discrete dexterity and muscle shrinkage of the bionic shoulder joint were established respectively to represent its many-sided characteristics. And the multi-objective optimization problem was transformed into a single-objective optimization problem by using the weighted-sum method. The normalization method and adaptive-weight method were used to determine each optimization index’s weight coefficient; then the particle swarm optimization was used to optimize the integrated objective function of the bionic shoulder joint and the optimal solution was obtained. Compared with the average optimization generations and the optimal target values of many experiments, using adaptive-weight method to adjust weights of integrated objective function is better than using normalization method, which validates superiority of the adaptive-weight method.     

Structural Optimization of Hatch Cover Based on Bi-directional Evolutionary Structure Optimization and Surrogate Model Method

Weight reduction has attracted much attention among ship designers and ship owners. In the present work, based on an improved bi-directional evolutionary structural optimization (BESO) method and surrogate model method, we propose a hybrid optimization method for the structural design optimization of beam-plate structures, which covers three optimization levels: dimension optimization, topology optimization and section optimization. The objective of the proposed optimization method is to minimize the weight of design object under a group of constraints. The kernel optimization procedure (KOP) uses BESO to obtain the optimal topology from a ground structure. To deal with beam-plate structures, the traditional BESO method is improved by using cubic box as the unit cell instead of solid unit to construct periodic lattice structure. In the first optimization level, a series of ground structures are generated based on different dimensional parameter combinations, the KOP is performed to all the ground structures, the response surface model of optimal objective values and dimension parameters is created, and then the optimal dimension parameters can be obtained. In the second optimization level, the optimal topology is obtained by using the KOP according to the optimal dimension parameters. In the third optimization level, response surface method (RSM) is used to determine the section parameters. The proposed method is applied to a hatch cover structure design. The locations and shapes of all the structural members are determined from an oversized ground structure. The results show that the proposed method leads to a greater weight saving, compared with the original design and genetic algorithm (GA) based optimization results.