Computational Investigation Identified Potential Chemical Scaffolds for Heparanase as Anticancer Therapeutics

Heparanase (Hpse) is an endo-β-D-glucuronidase capable of cleaving heparan sulfate side chains. Its upregulated expression is implicated in tumor growth, metastasis and angiogenesis, thus making it an attractive target in cancer therapeutics. Currently, a few small molecule inhibitors have been reported to inhibit Hpse, with promising oral administration and pharmacokinetic (PK) properties. In the present study, a ligand-based pharmacophore model was generated from a dataset of well-known active small molecule Hpse inhibitors which were observed to display favorable PK properties. The compounds from the InterBioScreen database of natural (69,034) and synthetic (195,469) molecules were first filtered for their drug-likeness and the pharmacophore model was used to screen the drug-like database. The compounds acquired from screening were subjected to molecular docking with Heparanase, where two molecules used in pharmacophore generation were used as reference. From the docking analysis, 33 compounds displayed higher docking scores than the reference and favorable interactions with the catalytic residues. Complex interactions were further evaluated by molecular dynamics simulations to assess their stability over a period of 50 ns. Furthermore, the binding free energies of the 33 compounds revealed 2 natural and 2 synthetic compounds, with better binding affinities than reference molecules, and were, therefore, deemed as hits. The hit compounds presented from this in silico investigation could act as potent Heparanase inhibitors and further serve as lead scaffolds to develop compounds targeting Heparanase upregulation in cancer.     

虚实结合的可穿戴产品适合性检验研究

目的 为了更科学地研究和检验可穿戴产品的适合性,提出一种适合性检验方法,能够精确保留现实环境中的产品佩戴关系,并能将现实与虚拟的适合性检验研究相结合,得到合理的适合性检验结果.方法 以虚拟现实眼镜的适合性检验为例,通过高精度的三维测量技术将现实环境中的人、产品以及人—产品佩戴关系转化为三维虚拟信息,并以人—产品佩戴三维模型为参考基准对齐人和产品的虚拟模型,得到保留现实佩戴关系的人—产品佩戴模型组,再应用偏差分析法得出人—机佩戴区域的可视化适合性结果和统计数据,结合主观评价方法进一步分析产品的适合性.结论 虚实结合的产品适合性检验方法可在虚拟环境中高精度地保留现实环境中的人—产品佩戴关系,并能得到可视化的适合性检验结果,为检验和指导产品的适合性提供依据.     

Sounds Stimulation on In Vitro HL1 Cells: A Pilot Study and a Theoretical Physical Model

Mechanical vibrations seem to affect the behaviour of different cell types and the functions of different organs. Pressure waves, including acoustic waves (sounds), could affect cytoskeletal molecules via coherent changes in their spatial organization and mechano-transduction signalling. We analyzed the sounds spectra and their fractal features. Cardiac muscle HL1 cells were exposed to different sounds, were stained for cytoskeletal markers (phalloidin, beta-actin, alpha-tubulin, alpha-actinin-1), and studied with multifractal analysis (using FracLac for ImageJ). A single cell was live-imaged and its dynamic contractility changes in response to each different sound were analysed (using Musclemotion for ImageJ). Different sound stimuli seem to influence the contractility and the spatial organization of HL1 cells, resulting in a different localization and fluorescence emission of cytoskeletal proteins. Since the cellular behaviour seems to correlate with the fractal structure of the sound used, we speculate that it can influence the cells by virtue of the different sound waves’ geometric properties that we have photographed and filmed. A theoretical physical model is proposed to explain our results, based on the coherent molecular dynamics. We stress the role of the systemic view in the understanding of the biological activity.     

基于GA-BP的汽车风振噪声声品质预测模型

目前对于汽车风振噪声的优化研究主要以声压级（Sound pressure level，SPL）作为单一评价指标，既不能全面反映噪声的物理属性，也无法考虑人耳对噪声的主观认知过程。为准确评价风振噪声，引入声品质，运用大涡模拟（Large eddy simulation，LES）对风振噪声进行数值仿真，根据实车道路试验判断仿真的准确性；对仿真结果进行声品质客观评价与主观评价，综合声品质客观评价参数与声品质主观评价试验结果建立BP神经网络预测模型；利用遗传算法（Genetic algorithm，GA），进一步对BP神经网络的结构参数进行优化，建立GA-BP声品质预测模型。研究结果表明，GA-BP声品质预测模型在训练速度和预测精度上都优于BP神经网络预测模型。预测模型基于声品质主客观评价结果，其预测值可以代替传统的声压级评价指标，为风振噪声提供更为准确合理的评价。     

基于PBFT区块链技术的电网企业仓储系统

提出了一种基于实用拜占庭容错(PBFT)算法的区块链技术,首先对传统的实用拜占庭容错算法原理进行了阐述,该传统算法包含前期、需求、预准备、准备、确认、答复6个阶段,但传统算法具有实时性差、缺乏惩罚机制、带宽高的缺点。针对出现的这些问题,又对传统算法进行了改进,具体涉及记账节点、共识过程以及视图切换过程。通过测试进一步证明了该改进算法的实用性,并将该算法应用于电网企业中,构建的虚拟仓库实现了联储联备,降低了库存资金的耗费,并且提高了电网企业库存管理的效率。     

基于虚拟元-有限元耦合的隧道内道床干缩裂缝细观研究

为解释道床与盾构隧道管片产生脱空的现象，研究新混凝土在浇筑后由干燥收缩产生的裂缝机理。基于虚拟元推导任意多边形骨料的刚度矩阵格式，利用UEL子程序实现有限元与虚拟元的耦合计算，纯弯梁数值试验结果表明耦合法较有限元法计算效率明显提升，且具有较好的稳定性。在此基础上，建立细观尺度下新老混凝土的干缩数值模型，并通过圆盘干缩模型验证了模型参数。研究骨料和砂浆的应力分布、内部湿度与裂缝发展的对应关系以及新老混凝土表面和界面的应力发展。结果表明：①收缩过程中，骨料主要承受压应力作用，砂浆沿骨料边界的切线方向受骨料约束作用易形成收缩裂缝，在新混凝土表面首先出现大量微小裂缝，随后界面两端发生剥离; ②受表面下骨料的约束作用，新混凝土表面拉应力呈现“驼峰”分布。开裂后表面被划分为多个收缩区，收缩区边界受拉应力，内部受压应力；③界面的拉伸和剪切应力由两侧开始增加，并且随着界面剥离的增加不断内移。在界面内部未剥离区域内存在由界面附近骨料约束导致的局部压应力和剪切应力增大。     

改进的CAGAN在虚拟试衣中的应用

针对CAGAN（Conditional Analogy GAN）换衣后效果模糊，在目标衣服与原始衣服长短不一致时效果一般，相对目标衣服保留过少的细节等问题做了相关研究并对CAGAN进行了改进，提出了新的虚拟试衣方式。经过改进的CAGAN生成一个粗糙的结果，由该结果得到目标衣服穿在模特身上改变形状后的mask，接下来利用mask对目标衣服进行变形，综合变形的衣服和第一步的结果便得到最终的试衣图像。实验结果表明，该方法解决了前面存在的问题，而且取得了非常好的效果。     

基于PolyWorks虚拟装配间隙面差计算分析研究

随着当今社会汽车制造业的迅猛发展,高标准和高需求已经是消费者对汽车制造凯歌的主旋律。而这其中,汽车钣金件的间隙面差就是其中一个重要因素。快速检测间隙面差是否满足设计要求直接关系到汽车白车身的生产精度和企业的工作效率。传统计算间隙面差大多利用量具,易划伤被测物且在零件实际装配后才可测量,降低生产效率,而非接触测量造价昂贵。本课题基于实物的汽车钣金件虚拟装配,对间隙面差的计算方法进行分类与参数调整,提出一种高效率、高标准的间隙面差计算流程。