Anti prostate cancer using PEGylated bombesin containing,cabazitaxel loading nano-sized drug delivery system

Context: Prostate cancer (PCa) is the second most-frequently diagnosed cancer in men. Cabazitaxel was approved for the treatment of patients with hormone-refractory metastatic prostate cancer previously treated with a docetaxel-containing regimen.

Objective: In this study, bombesin (BN), a ligand reported to specifically target GRP overexpressing prostate tumor, was applied for the construction of lipid-polymer hybrid nanoparticles (LPNs), and used for the targeted delivery of cabazitaxel (CAB) to prostate cancer.

Methods: BN-polyethylene glycol-1,2-Distearoyl-sn-glycero-3-phosphoethanolamine (BN-PEG-DSPE) was synthesized. CAB loaded, BN-PEG-DSPE contained LPNs (BN-CAB-LPNs) were prepared. Their particle size, zeta potential and drug encapsulation efficiency (EE) were evaluated. In vitro cytotoxicity study of BN-CAB-LPNs was tested in LNCaP human prostatic cancer cell line (LNCaP cells). In vivo anti-tumor efficacy of the carriers was evaluated on mice bearing prostate cancer model.

Results: The optimum BN-CAB-LPNs formulations had a particle size of 184.9?nm and a 26.5?mV positive surface charge. The growth of LNCaP cells in vitro was obviously inhibited. BN-CAB-LPNs also displayed better anti-tumor activity than the other formulations in vivo.

Conclusion: The results demonstrated that BN-CAB-LPNs can sufficiently deliver CAB to the cancer cells and enhance the anti-tumor capacity. Thus, BN-CAB-LPNs can be proved to be a superior nanomedicine which can achieve better therapeutic efficacy of prostate tumor.     

Application potential of bone marrow mesenchymal stem cell (BMSCs) based tissue-engineering for spinal cord defect repair in rat fetuses with spina bifida aperta

Spina bifida aperta are complex congenital malformations resulting from failure of fusion in the spinal neural tube during embryogenesis. Despite surgical repair of the defect, most patients who survive with spina bifida aperta have a multiple system handicap due to neuron deficiency of the defective spinal cord. Tissue engineering has emerged as a novel treatment for replacement of lost tissue. This study evaluated the prenatal surgical approach of transplanting a chitosan–gelatin scaffold seeded with bone marrow mesenchymal stem cells (BMSCs) in the healing the defective spinal cord of rat fetuses with retinoic acid induced spina bifida aperta. Scaffold characterisation revealed the porous structure, organic and amorphous content. This biomaterial promoted the adhesion, spreading and in vitro viability of the BMSCs. After transplantation of the scaffold combined with BMSCs, the defective region of spinal cord in rat fetuses with spina bifida aperta at E20 decreased obviously under stereomicroscopy, and the skin defect almost closed in many fetuses. The transplanted BMSCs in chitosan–gelatin scaffold survived, grew and expressed markers of neural stem cells and neurons in the defective spinal cord. In addition, the biomaterial presented high biocompatibility and slow biodegradation in vivo. In conclusion, prenatal transplantation of the scaffold combined with BMSCs could treat spinal cord defect in fetuses with spina bifida aperta by the regeneration of neurons and repairmen of defective region.     

An Influence Maximization Algorithm Based on Improved K-Shell in Temporal Social Networks

Influence maximization of temporal social networks (IMT) is a problem that aims to find the most influential set of nodes in the temporal network so that their information can be the most widely spread. To solve the IMT problem, we propose an influence maximization algorithm based on an improved K-shell method, namely improved K-shell in temporal social networks (KT). The algorithm takes into account the global and local structures of temporal social networks. First, to obtain the kernel value Ks of each node, in the global scope, it layers the network according to the temporal characteristic of nodes by improving the K-shell method. Then, in the local scope, the calculation method of comprehensive degree is proposed to weigh the influence of nodes. Finally, the node with the highest comprehensive degree in each core layer is selected as the seed. However, the seed selection strategy of KT can easily lose some influential nodes. Thus, by optimizing the seed selection strategy, this paper proposes an efficient heuristic algorithm called improved K-shell in temporal social networks for influence maximization (KTIM). According to the hierarchical distribution of cores, the algorithm adds nodes near the central core to the candidate seed set. It then searches for seeds in the candidate seed set according to the comprehensive degree. Experiments show that KTIM is close to the best performing improved method for influence maximization of temporal graph (IMIT) algorithm in terms of effectiveness, but runs at least an order of magnitude faster than it. Therefore, considering the effectiveness and efficiency simultaneously in temporal social networks, the KTIM algorithm works better than other baseline algorithms.     

基于PXI的飞控襟翼仿真系统的设计与实现

为了真实仿真飞控襟翼系统部件的功能和接口,替代系统真件参与试验,探查飞控襟翼操纵系统的组成结构和工作原理,设计并实现了基于PXI的飞控襟翼仿真系统;根据真件相关资料,建立了完整的襟翼操纵系统闭环控制模型,建设了襟翼硬件仿真测试平台,编制了仿真测试软件;仿真系统硬件采用模块化结构设计,提高了稳定性和可靠性;系统软件基于QNX实时操作系统编制,保证了仿真测试过程中事件响应的实时性;成果在实际工作中成功应用于飞控系统联测,满足了仿真系统的功能需求和技术指标.     

“主导·主体”教学模式在配置路由选择协议实验中的应用

针对多数计算机网络实验课以学生为中心的实际情况,在分析其缺点的基础上,文章提出将"主导.主体"教学模式应用于计算机网络原理实验课中,并以配置路由选择协议为实验案例,探讨"主导.主体"教学模式在其中的应用,为该教学模式在计算机网络其他实验中的应用提供借鉴意义。     

证券行业信息系统备份能力现状浅析

为了发挥备份能力建设在证券行业信息系统业务连续性中的重要作用,本文结合行业信息系统备份能力标准,信息系统备份能力分级,以及行业备份能力建设实践,分析证券行业信息系统备份能力现状与标准的差距,建设中存在的难点,进一步提出备份能力建设的建议。     

A relativistic extension of the complex scaling method using oscillator basis functions

We develop the complex scaling method within the relativistic framework by expanding the Dirac spinors in the complete set of eigensolutions of a harmonic oscillator potential, and present the theoretical formalism of describing the discrete bound and resonant states on the same footing. Based on a well established and frequently used model, we demonstrate the utility and applicability of the extended method and examine the stability of the results with respect to the variations of the parameters of the model. Satisfactory agreements are found for all the calculated results in comparison with some other calculations in references. Especially, the present calculation in the nonrelativistic limit gives a consistent result with that in the nonrelativistic calculation.     

A graph-theoretical clustering method based on two rounds of minimum spanning trees

Many clustering approaches have been proposed in the literature, but most of them are vulnerable to the different cluster sizes, shapes and densities. In this paper, we present a graph-theoretical clustering method which is robust to the difference. Based on the graph composed of two rounds of minimum spanning trees (MST), the proposed method (2-MSTClus) classifies cluster problems into two groups, i.e. separated cluster problems and touching cluster problems, and identifies the two groups of cluster problems automatically. It contains two clustering algorithms which deal with separated clusters and touching clusters in two phases, respectively. In the first phase, two round minimum spanning trees are employed to construct a graph and detect separated clusters which cover distance separated and density separated clusters. In the second phase, touching clusters, which are subgroups produced in the first phase, can be partitioned by comparing cuts, respectively, on the two round minimum spanning trees. The proposed method is robust to the varied cluster sizes, shapes and densities, and can discover the number of clusters. Experimental results on synthetic and real datasets demonstrate the performance of the proposed method.