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1.
Shraddha Parate Vikas Kumar Danishuddin Jong Chan Hong Keun Woo Lee 《International journal of molecular sciences》2021,22(10)
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. 相似文献
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The ability to trap precise quantities of cells or particles into confined areas has numerous applications for biological purposes. In particular, single cell trapping has received considerable attention because it permits the study of heterogeneity in a population, while trapping larger groups of cells have been used to form aggregates. Among several methods, the use of microwell offers a simple platform to capture cells or particles using hydrodynamic forces. This review examines the use of microwells in both static and microfluidic environments, and the application of microfluidic geometric arrays for trapping. This paper discusses the design and fabrication methods of microwells and compares the trapping and release techniques used in both static and microfluidics‐integrated microwells. Finally, we will summarize novel microfluidic geometric arrays used to capture cells or particles through hydrodynamic trapping. 相似文献
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在电网调度运行的实际生产中,需要综合多个业务系统中的数据,并从中挖掘出有价值的电力运行信息。当前,省地县调度业务多通过调度电话或者邮件联系,同时业务系统分布在不同安全分区,缺乏有效的管理措施。文章阐述了电网省地县调度数据一体化管理平台,其具备提供数据收集、存储、自定义报表、数据加工等功能,使省地县调的纵向数据传输能力得到显著改善。 相似文献
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双臂机器人系统是当前机器人领域的研究热点,特别是随着单臂机器人在操作能力、控制等方面的局限性不断凸显,最近的研究集中在拥有协调操作能力的冗余双臂机器人。对双臂操作进行分类,然后从双臂协调运动方式、双臂协调控制问题、感知传感器、模仿学习、人机交互五个方面进行分析;综述从运动学、动力学现状入手,分析了双臂协调控制与单臂控制方式在约束关系、运动规划、协调控制方式等方面的不同与发展,结合感知传感器、模仿学习等方法在双臂协调控制中的应用;对人机协作中的交互方式进行了分析,并对双臂机器人的未来研究方向进行了展望。 相似文献
8.
分析了混合型有源滤波器HAPF(hybrid active power filter)在高压直流系统应用时的稳定性问题,其中HAPF采用H桥级联变换器与LC滤波器组合的方案,对高压直流系统的特征谐波电流进行滤波。为了分析在电网阻抗变化时HAPF出现的谐波谐振现象,对HAPF进行了阻抗建模,基于阻抗模型的分析结果,采用了具有延时补偿功能的谐振调节器对阻抗特性进行修正,并从提高稳定性角度提出了相应的控制参数设计方法。阻抗模型分析结果表明,控制系统延时产生的负阻尼是引发稳定性问题的主要原因,采用改进后的控制方法可以将延时产生的负阻尼修正为正阻尼,能够有效避免谐波谐振。在PSCAD中进行仿真建模,并通过阻抗扫描验证了有源滤波器的阻抗特性。仿真案例证实了控制方法的有效性。 相似文献
9.
Makoto Yamaguchi 《应用聚合物科学杂志》2021,138(14):50172
Perfluorosulfonic acid ionomer membranes have been widely used as proton conducting membranes in various electrochemical processes such as polymer electrolyte fuel cells and water electrolysis. While their thermal stability has been studied by thermogravimetry and analysis of low molecular weight products, their decomposition mechanism is little understood. In this study a newly developed methodology of thermal desorption and pyrolysis in combination with direct analysis in real time mass spectrometry is applied for Nafion membrane. An ambient ionization source and a high-resolution time-of-flight mass spectrometer enabled unambiguous assignment of gaseous products. Thermal decomposition is initiated by side chain detachment above 350°C, which leaves carbonyls on the main chain at the locations of the side chains. Perfluoroalkanes are released above 400°C by main chain scission and their further decomposition products dominate above 500 °C. DFT calculation of reaction energies and barrier heights of model compounds support proposed decomposition reactions. 相似文献
10.
Xiaonan Lu Irmak Sargin John D. Vienna 《Journal of the American Ceramic Society》2021,104(11):5636-5647
Nepheline precipitation in nuclear waste glasses during vitrification can be detrimental due to the negative effect on chemical durability often associated with its formation. Developing models to accurately predict nepheline precipitation from compositions is important for increasing waste loading since existing models can be overly conservative. In this study, an expanded dataset of 955 glasses, including 352 high-level waste glasses, was compiled from literature data. Previously developed submixture models were refitted using the new dataset, where a misclassification rate of 7.8% was achieved. In addition, nine machine learning (ML) algorithms (k-nearest neighbor, Gaussian process regression, artificial neural network, support vector machine, decision tree, etc.) were applied to evaluate their ability to predict nepheline precipitation from glass compositions. Model accuracy, precision, recall/sensitivity, and F1 scores were systemically compared between different ML algorithms and modeling protocols. Model prediction with an accuracy of ~0.9 (misclassification rate of ~10%) was observed for different algorithms under certain protocols. This study evaluated various ML models to predict nepheline precipitation in waste glasses, highlighting the importance of data preparation and modeling protocol, and their effect on model stability and reproducibility. The results provide insights into applying ML to predict glass properties and suggest areas for future research on modeling nepheline precipitation. 相似文献