金钱草不同溶剂提取物对雷公藤毒性抑制作用的比较

目的 考察金钱草不同提取物对雷公藤主要毒性肝损伤的减毒作用,优选提取溶剂。方法 将90只雄性SPF级昆明种小鼠按体质量随机分为9组,即正常组、金钱草水提物组、金钱草30%乙醇提取物组、雷公藤组、雷公藤配伍金钱草水提取物组、雷公藤配伍金钱草30%乙醇提取物组、雷公藤配伍金钱草60%乙醇提取物组、雷公藤配伍金钱草95%乙醇提取物组、雷公藤配伍金钱草乙酸乙酯提取物组,其中雷公藤与金钱草的剂量均按生药计分别为2,1 g·kg^-1,正常组给予等体积的溶媒,各组均采用灌胃给予,连续14 d,末次给药24 h取血和肝组织,采用酶联免疫吸附测定（ELISA）检测小鼠血清生化指标及肝脂质过氧化/抗氧化指标,同时借助主成分分析方法整体评价金钱草提取物对雷公藤肝损伤的减毒作用及其作用机制。结果 与正常组比较,雷公藤组小鼠血清丙氨酸氨基转移酶（ALT）,天冬氨酸氨基转移酶（AST）,碱性磷酸酶（ALP）,肝丙二醛（MDA）水平,以及由以上4个指标降维产生的肝损伤综合得分（Z值）均显著升高（P<0.01）,肝抗氧化指标总超氧化物歧化酶（T-SOD）,谷胱甘肽-过氧化物酶（GPX）,谷胱甘肽-S转移酶（GST）水平均显著降低（P<0.01）;与雷公藤组比较,分别给予金钱草2种溶剂（水,30%乙醇）提取物干预后,血清ALT,AST,ALP及肝MDA水平均明显降低（P<0.05,P<0.01）,肝T-SOD,GPX,GST水平显著升高（P<0.01）,给予金钱草2种溶剂（60%乙醇,95%乙醇）提取物干预后,血清ALT,AST,ALP水平均显著降低（P<0.01）,肝GPX水平显著升高（P<0.01）,给予金钱草乙酸乙酯提取物干预后,仅能明显降低血清AST水平（P<0.05）,显著升高肝GPX水平（P<0.05）;而给予金钱草不同溶剂（水,30%乙醇,60%乙醇,95%乙醇,乙酸乙酯）提取物干预后均能显著降低肝损伤综合得分（P<0.01）。结论 金钱草不同溶剂（水,30%乙醇,60%乙醇,95%乙醇,乙酸乙酯）提取物均可不同程度逆转雷公藤引起的肝损伤,其中以水和30%乙醇作为溶剂时的减毒作用为优,尤以水作为提取溶剂为更佳,且随着提取溶剂乙醇含量的升高或脂溶性的增强,肝损伤呈下降趋势。     

桡骨远端骨折锁定钢板刚度的拓扑优化研究

目的对桡骨远端骨折锁定钢板结构进行优化设计,以应对骨折内固定个性化刚度需求。方法运用三维建模和计算机辅助设计软件完成桡骨远端骨折模型和常规钢板的模型构建,基于初始有限元分析结果,以轴向刚度下调33.33%且保留扭转刚度的90.00%以上作为优化目标,对常规钢板进行拓扑优化和重设计;通过有限元分析计算,对比常规钢板和优化钢板在轴向压缩和扭转工况下的内固定刚度和产生的骨折区应变。结果所获得的优化钢板轴向刚度为636.5 N/mm,下调幅度为19.7%,基本接近既定的目标刚度,优化后的扭转刚度为634.12 Nmm/°,下调幅度为8.8%,并未超出既定的目标限值;而骨折区应变变化方面,轴向应变相比切向应变呈现出更为显著的增加趋势,与刚度调控效果基本一致。结论通过拓扑优化的方法从钢板结构层面进行重设计,可实现骨折愈合的个性化内固定刚度调控。     

Linear Wavefield Optimization Using a Modified Source

Recorded seismic data are sensitive to the Earth's elastic properties, and thus, they carry information of such properties in their waveforms. The sensitivity of such waveforms to the properties is nonlinear causing all kinds of difficulties to the inversion of such properties. Inverting directly for the components forming the wave equation, which includes the wave equation operator (or its perturbation), and the wavefield, as independent parameters enhances the convexity of the inverse problem. The optimization in this case is provided by an objective function that maximizes the data fitting and the wave equation fidelity, simultaneously. To enhance the practicality and efficiency of the optimization, I recast the velocity perturbations as secondary sources in a modified source function, and invert for the wavefield and the modified source function, as independent parameters. The optimization in this case corresponds to a linear problem. The inverted functions can be used directly to extract the velocity perturbation. Unlike gradient methods, this optimization problem is free of the Born approximation limitations in the update, including single scattering and cross talk that may arise for example in the case of multi sources. These specific features are shown for a simple synthetic example, as well as the Marmousi model.     

Concomitant Malnutrition and Frailty Are Uncommon,but Significant Risk Factors for Mortality and Complication Following Primary Total Knee Arthroplasty

BackgroundTotal knee arthroplasty (TKA) demand continues to rise, but we are also gaining greater insight into patient risk factors for postoperative complications and excess resource utilization. There has been growing interest in frailty and malnutrition as risk factors, although they are often mistakenly used interchangeably. We aimed at identifying the incidence of their coexistence, and the magnitude of risk they confer to TKA patients.MethodsWe queried the American College of Surgeons-National Surgery Quality Improvement Program database to identify 4 patient cohorts: healthy/normal serum albumin, healthy/hypoalbuminemic patients, normoalbuminemic/medically frail patients (defined by modified frailty index), and hypoalbuminemic/frail patients. We performed both univariate and multivariate analyses to quantify the risk conferred by each condition in isolation, and in coexistence.ResultsOf 179,702 elective TKA cases from 2006 to 2018, 18.6% of patients were frail only, 3.0% were hypoalbuminemic -only, and just 1.2% were both frail and hypoalbuminemic. The raw rate of any complication was highest in frail/hypoalbuminemic patients (8.7%), 5.2% in hypoalbuminemic patients, 4.8% in frail patients, and just 3.4% in healthy patients (P < .001); the multivariate model revealed odds ratio of a complication in frail/hypoalbuminemic group of 2.40 (95% confidence interval = 1.27-1.63; P < .001). Mortality within 30 days was highest in the frail/hypoalbuminemic cohort (1.0%), and just 0.1% in healthy patients, and the multivariate model noted an odds ratio of 9.43 for these patients (95% confidence interval = 5.92-14.93; P < .001). The odds of all studied complications were highest in the frail/hypoalbuminemic group.ConclusionFrailty and hypoalbuminemia represent distinct conditions and are independent risk factors for a complication after TKA. Their coexistence imparts a synergistic association with the risk of post-TKA complications.     

Fractional Chebyshev functional link neural network-optimization method for solving delay fractional optimal control problems with Atangana-Baleanu derivative

In this article, we propose a higher order neural network, namely the functional link neural network (FLNN), for the model of linear and nonlinear delay fractional optimal control problems (DFOCPs) with mixed control-state constraints. We consider DFOCPs using a new fractional derivative with nonlocal and nonsingular kernel that was recently proposed by Atangana and Baleanu. The derivative possesses more important characteristics that are very useful in modelling. In the proposed method, a fractional Chebyshev FLNN is developed. At the first step, the delay problem is transformed to a nondelay problem, using a Padé approximation. The necessary optimality condition is stated in a form of fractional two-point boundary value problem. By applying the fractional integration by parts and by constructing an error function, we then define an unconstrained minimization problem. In the optimization problem, trial solutions for state, co-state and control functions are utilized where these trial solutions are constructed by using single-layer fractional Chebyshev neural network model. We then minimize the error function using an unconstrained optimization scheme based on the gradient descent algorithm for updating the network parameters (weights and bias) associated with all neurons. To show the effectiveness of the proposed neural network, some numerical results are provided.     

Model predictive control of a collaborative manipulator considering dynamic obstacles

Collaborative robots have to adapt its motion plan to a dynamic environment and variation of task constraints. Currently, they detect collisions and interrupt or postpone their motion plan to prevent harm to humans or objects. The more advanced strategy proposed in this article uses online trajectory optimization to anticipate potential collisions, task variations, and to adapt the motion plan accordingly. The online trajectory planner pursues a model predictive control approach to account for dynamic motion objectives and constraints during task execution. The prediction model relates reference joint velocities to actual joint positions as an approximation of built-in robot tracking controllers. The optimal control problem is solved with direct collocation based on a hypergraph structure, which represents the nonlinear program and allows to efficiently adapt to structural changes in the optimization problem caused by moving obstacles. To demonstrate the effectiveness of the approach, the robot imitates pick-and-place tasks while avoiding self-collisions, semistatic, and dynamic obstacles, including a person. The analysis of the approach concerns computation time, constraint violations, and smoothness. It shows that after model identification, order reduction, and validation on the real robot, parallel integrators with compensation for input delays exhibit the best compromise between accuracy and computational complexity. The model predictive controller can successfully approach a moving target configuration without prior knowledge of the reference motion. The results show that pure hard constraints are not sufficient and lead to nonsmooth controls. In combination with soft constraints, which evaluate the proximity of obstacles, smooth and safe trajectories are planned.     

Adaptive optimal tracking control for multi-joint manipulator on space robot

This paper aims to address the tracking control problem for the multi-joint manipulator on a space robot subject to model uncertainties and external disturbances. A Gauss-Newton interactive optimization algorithm is used to obtain the desired joint angle for each joint. In order to formulate the optimization problem, the Denaait-Hartenberg (D-H) method is employed to describe the model of the multi-joint manipulator. Subsequently, an adaptive controller is developed to achieve tracking control, where controller parameters updated in real time are introduced to handle the nondeterminacy of the multi-joint manipulator. Moreover, a fuzzy control strategy is composed such that our designed controller is robust against the complex environment as well. The controller design is performed by means of the Lyapunov techniques. Meanwhile, its effectiveness is verified through numerical simulations. Finally, some concluding remarks close the paper.     

基于身体质量指数优化管电流降低 256 层螺旋 CT 的冠状动脉成像辐射剂量的研究简

目的 探讨基于身体质量指数（BMI）优化管电流在256层螺旋极速CT冠状动脉检查降低辐射剂量中的可行性与应用价值,即常规回顾性心电门控技术与基于BMI优化管电流回顾性心电门控术的对比研究.方法 按拟定的标准将120例病例纳入本研究,随机分为A、B两组,每组60例.A组：常规回顾性心电门控组（对照组）;B组：基于BMI优化管电流回顾性心电门控组（实验组）.记录每例患者的性别、年龄、体重、身高、BMI、平均心率及扫描长度,测量并计算出原始轴位冠状动脉增强图像的图像噪声、信号噪声比和对比噪声比,同时进行图像质量评价,并计算出有效辐射剂量.然后对客观与主观图像质量评估指标及有效辐射剂量进行统计学分析.结果 ①A、B两组患者的图像噪声分别为：30.48±5.60、32.08±3.56,组间比较无显著差异（P＞0.05）.A、B两组患者的图像信噪比分别为：15.42±3.73、14.47±2.72,组间比较无显著差异（P＞0.05）.A、B两组患者的图像对比噪声比分别为：13.29±3.52、12.40±2.60,组间比较无显著差异（P＞0.05）.A、B两组患者的图像总评分分别为：（3.63±0.41）分、（3.58±0.44）分,组间比较无显著差异（P＞0.05）.②A、两组患者的有效辐射剂量分别为：（14.34±0.92）mSv、（7.16±1.40）mSv,组间比较有显著差异（P＜0.05）.结论 基于BMI优化管电流回顾性心电门控与常规回顾性心电门控技术相比,前者在满足诊断要求的图像质量的同时,可有效地降低辐射剂量.     

Fast track surgery and preoperative optimization

Enhanced recovery pathways have been rapidly embraced by surgeons as a mechanism for improving patient care and driving down complications and costs. They seek to employ a holistic approach, reviewing all aspects of patient management, to improve care. Many components are dissimilar to traditional surgical teaching, involving early mobilization and enteral nutrition, as well as a strong emphasis on fluid balance and pain management. By addressing all components of the patient pathway from preoperative through to post-surgery, significant improvement in outcomes can be achieved for a range of surgical procedures.     

向量评估遗传算法优化聚乳酸载药微球工艺

目的:研究向量评估遗传算法(VEGA)优化聚乳酸载药微球的制备工艺,寻求同时使药物包封率最大及产物平均粒径最小的两目标最佳工艺体系。方法:对均匀设计试验制备聚乳酸载药微球的药物包封率和平均粒径两目标采用VEGA进行优化,影响因素有内水相体积(x1)、二氯甲烷(DCM)的质量浓度(x2)、聚乙烯醇(PVA)的质量浓度(x3)、搅拌速度(x4)及氯化钠的质量分数(x5),通过搜索最优制备工艺,比较VEGA搜索载药微球最优处方结果;利用Matlab 2009a外挂SGALAB工具箱Beta 5008完成遗传算法寻优,利用SPSS 17.0软件进行统计分析;并对其处方优化效果进行评价。结果:VEGA进行两目标优化后,最佳工艺中影响因素有x2、x4、x5,分别为86.68 mg/ml、1 499.48 r/min、0.04%,x1和x3因素影响不显著;目标值药物包封率最大达到95.99%,平均粒径最小达到20.80μm。结论:VEGA搜索的Pareto非劣解是合理的,确定的最优提取工艺的效果较好,均高于均匀设计中的试验方案。