Inclusion of interactions in mathematical modelling of implant assisted magnetic drug targeting

Drug delivery technologies are an important area within biomedicine. Targeted drug delivery aims to reduce the undesired side effects of drug usage by directing or capturing the active agents near a desired site within the body. This is particularly beneficial in, for instance, cancer chemotherapy, where the side effects of general (systemic) drug administration can be severe.One approach to targeted drug delivery uses magnetic nanoparticles as the constituents of carriers for the desired active agent. Once injected into the body, the behaviour of these magnetic carriers can be influenced and controlled by magnetic fields. In implant assisted magnetic drug targeting systems a magnetic implant, typically a stent, wire or spherical seed can be used to target sites deep within the body as the implant acts as a focus for the resulting magnetic force. This can be easily understood as the force depends on the gradient of the magnetic field and the gradient near the implant is large.In designing such a system many factors need to be considered including physical factors such as the size and nature of the implants and carriers, and the fields required. Moreover, the range of applicability of these systems in terms of the regions of the vasculature system, from low blood velocity environments, such as capillary beds to higher velocity arteries, must be considered. Furthermore, assessment criteria for these systems are needed. Mathematical modelling and simulation has a valuable role to play in informing in vitro and in vivo experiments, leading to practical system design.Specifically, the implant assisted magnetic drug targeting systems of Avilés, Ebner and Ritter are considered within this review, and two dimensional mathematical modelling is performed using the open source C++ finite volume library OpenFOAM. In the first system treated, a large ferromagnetic particle is implanted into a capillary bed as a seed to aid collection of single domain nanoparticles (radius 20-100 nm). The Langevin function is used to calculate the magnetic moment of the particles, and the model is further adapted to treat the agglomeration of particles known to occur in these systems. This agglomeration can be attributed to interparticle interactions and here the magnetic dipole-dipole and hydrodynamic interactions for two mutually interacting nanoparticles are modelled, following Mikkelsen et al. who treated two particle interactions in microfluidic systems, with low magnetic field (0.05 T). The resulting predicted performance is found to both increase and decrease significantly depending on initial positions of the particles. Secondly, a ferromagnetic, coiled wire stent is implanted in a large arterial vessel. The magnetic dipole-dipole and hydrodynamic interactions for multiple particles are included. Different initial positions are considered and the system performance is assessed. Inclusion of these interactions yields predictions that are in closer agreement with the experimental results of Avilés et al. We conclude that the discrepancies between the non interacting theoretical predictions and the corresponding experimental results can (as suggested by Avilés et al.) be largely attributed to interparticle interactions and the consequent agglomeration.     

离子液体对β-糖苷酶催化合成红景天苷的影响(英文)

研究了混合溶剂体系中阴离子分别为BF4-,PF6-,Cl-,Br-和I的14种离子液体对来源于黑布林糖苷酶催化合成红景天苷反应的影响.结果表明,在最佳反应条件下,β-糖苷酶的反应初速度和红景天苷的产率分别为3.3mmol/(L·h)和24.5%.离子液体咪唑阳离子的烷基链长(C2~C10)对β-糖苷酶的活性影响较大,当烷基链长为C6时,糖苷酶表现出较高的催化活性.     

基于高光谱图像的玉米种子特征提取与识别

玉米种子的形态特征是玉米品种识别的重要因素之一.采用高光谱成像系统获取9个品种共432粒玉米种子的高光谱反射图像,对图像进行校正和预处理,提取每个样本在563.6～911.4nm共55个波段范围内的形状特征.分别利用单波段、多波段和全波段下的玉米种子形状特征结合偏最小二乘判别法进行模型分类.结果显示,全波段范围内训练集和测试集的平均正确识别率达到98.31%和93.98%,均优于多波段和单波段的正确识别率.研究表明,该方法能充分利用高光谱图像中可见光和近红外区域的有效特征信息,较准确地鉴别玉米品种,为玉米品种的自动识别领域提供了一种新方法.     

种子注入环形腔人眼安全KTP参变振荡器的研究

利用电光调Q的Nd:YAG激光器抽运非临界相位匹配(θ=90°,φ=0°)环形腔KTP光学参变振荡器(OPO),实现了高能量人眼安全波段的1.57μm激光输出。理论与实验结果表明,减小谐振腔长度和注入种子源激光可以有效降低阈值,提高输出能量。当Nd:YAG激光器抽运能量为88mJ时,注入种子源功率由0mW增加到6mW,输出能量由8.8mJ增加到14mJ。当抽运能量为167.7mJ,注入种子源功率达到6mW时,最大输出能量达到46mJ,峰值功率7.44MW。     

Some discussions about the variable separating method for solving nonlinear models

Through analysing the exact solution of some nonlinear models, the role of the variable separating method in solving nonlinear equations is discussed. We find that rich solution structures of some special fields of these equations come from the nonzero seed solution. However, these nonzero seed solutions is likely to result in the divergent phenomena for the other field component of the same equation. The convergence and the signification of all field components should be discussed when someone solves the nonlinear equation using the variable separating method.     

GC/MS 法测定超临界 CO2 萃取茼蒿籽油

利用GC/MS分析了超临界CO2萃取茼蒿籽油的成分组成,共检出32种成分。茼蒿籽油主要由亚油酸（含量68.32%)、棕榈酸（10.80%)、油酸(6.39%)和长碳链脂肪酸组成;茼蒿籽油还含甾类（4.76%)和丰富的维生素E（3.9mg/g);研究了茼蒿籽油的理化特征。     

薄层色谱法分析葵花仁粕中的绿原酸

 以聚酰胺薄膜为固定相、体积分数为 36 %的乙酸溶液为流动相 ,研究建立了薄层色谱分离测定葵花仁粕中绿原酸的方法。绿原酸样品溶液上行展开 8 5cm ,其Rf 值为 0 6 1。绿原酸的检测量在 0 0 5 μg～ 0 6 μg范围内 ,其斑点的面积与绿原酸的检测量具有良好的线性关系。绿原酸的回收率为 97 5 3 % ,不同薄层板之间的RSD为2 5 7% ,最低检出限为 0 0 2 5 μg。在以体积分数为 70 %的乙醇溶液为萃取剂、搅拌振荡萃取时间为 30min的条件下 ,以该方法测定萃取液中绿原酸的含量和葵花仁粕中绿原酸的残留量 ,确定了最佳萃取次数。     

苦豆籽中总生物碱的含量测定

苦豆籽系槐科植物苦豆子 (Ｓｏｐｈｒａａｌｏｐｅｃａｒｏｉｄｅｓ)的成熟种子。从苦豆籽中分离得到了 2 0余种生物碱[1 ] ,具有广泛的生理活性 ,药用价值很高。苦豆子总生物碱的含量测定有重量法[2 ] ,酸碱滴定法[3] ,因苦豆子生物碱结构多属于喹啉联啶类衍生物 ,可在ｐＨ7.6缓冲液中与溴麝香草酚蓝形成离子对 ,经氯仿提取后于 42 0ｎｍ进行比色测定。我们采用这种酸性染料分光光度法[4] 进行了苦豆籽胶囊中总生物碱的含量测定 ,为其质量标准的测定提供了依据。1　实验部分1 .1　仪器 ,药品72 1型分光光度计、ＰＨ 2Ｓ型酸度计 ,槐果碱(Ｃ…     

大泽山葡萄籽油中脂肪酸成分的GC／MS分析

介绍了用正己烷抽提葡萄籽,然后将油进行皂化,用气相色谱－质谱法测定油中脂肪酸,共检测出１４种脂肪酸,其中亚油酸含量最高,占８６．４８％。     

钛硅沸石的结晶动力学研究

 在TPABr-正丁胺体系中合成了钛硅沸石TS-1, 研究了此体系中的结晶动力学,求出了不同温度下的成核速率、晶体生长速率及表观活化能. 还研究了晶种类型和用量对钛硅沸石晶化的影响. 结果表明,随着晶化温度的升高, TS-1成核诱导期缩短,成核速率及晶体生长速率加快; 加入晶种可明显缩短TS-1成核诱导期,并减小晶粒粒度; TS-1, M, ZSM-11和β沸石等均可作为晶种合成TS-1, 并存在一个最佳晶种用量; 不加晶种时TS-1成核活化能和晶体生长活化能分别为44.4和75.7 kJ/mol.