Structural Insights into the Design of Synthetic Nanobody Libraries

Single domain antibodies from camelids, or nanobodies, are a unique class of antibody fragments with several advantageous characteristics: small monomeric size, high stability and solubility and easy tailoring for multiple applications. Nanobodies are gaining increasing acceptance as diagnostic tools and promising therapeutic agents in cancer and other diseases. While most nanobodies are obtained from immunized animals of the camelid family, a few synthetic nanobody libraries constructed in recent years have shown the capability of generating high quality nanobodies in terms of affinity and stability. Since this synthetic approach has important advantages over the use of animals, the recent advances are indeed encouraging. Here we review over a dozen synthetic nanobody libraries reported so far and discuss the different approaches followed in their construction and validation, with an emphasis on framework and hypervariable loop design as critical issues defining their potential as high-class nanobody sources.     

Apoptolidin: induction of apoptosis by a natural product

Apoptolidin is a natural product that selectively induces apoptosis in several cancer cell lines. Apoptosis, programmed cell death, is a biological key pathway for regulating homeostasis and morphogenesis. Apoptotic misregulations are connected with several diseases, in particular cancer. The extrinsic way to apoptosis leads through death ligands and death receptors to the activiation of the caspase cascade, which results in proteolytic degradation of the cell architecture. The intrinsic pathway transmits signals of internal cellular damage to the mitochondrion, which loses its structural integrity, and forms an apoptosome that initiates the caspase cascade. Compounds which regulate apoptosis are of high medical significance. Many natural products regulate apoptotic pathways, and apoptolidin is one of them. The known synthetic routes to apoptolidin are described and compared in this Review. Selected further natural products which regulate apoptosis are introduced briefly.     

Multi‐responses Methodology Applied in the Electroanalytical Determination of Hair Dye by Using Printed Carbon Electrode Modified with Graphene

This paper describes a rapid and sensitive method for determination of the hair dye Basic Blue 41 in wastewater samples using screen‐printed carbon electrodes modified with graphene (SPCE/Gr). The method is based on the reversible reduction of azo groups of the dye at potential of ?0.23 V/?0.26 V, where both the anodic and cathodic currents increased 1,300 % when compared to screen‐printed carbon (SPCE) and glassy carbon electrodes (GCE). The optimization of a square wave voltammetric method was performed by means of 2³ factorial design, Doehlert matrix and multi‐response assays, and the best parameters were: frequency (54.8 Hz), step potential (6 mV), pulse amplitude (43.7 mV) and pH 4.5. The analytical curve was constructed from 3.00×10^?8 to 2.01×10^?6 mol L^?1, with detection and quantification limits of 5.00×10^?9 and 1.70×10^?8 mol L^?1, respectively. The repeatability of the method evaluated for 10 consecutive measurements at concentrations of 1.70×10^?7 mol L^?1 and 1.70×10^?6 mol L^?1, showed relative standard deviation of 3.56 and 0.57 %, respectively. The sensor based in SPCE/Gr was successfully applied in wastewater samples collected from a drinking water treatment plant and validated by comparison with HPLC‐DAD method with good accuracy.     

隔震结构的研究概况和主要问题

简要概括了国内外隔震技术的应用发展状况.系统总结、评述了隔震结构若干方向的研究进展,包括隔震结构的非线性地震反应分析和非线性动力学性态分析、可靠度分析、优化设计、系统识别、试验研究等内容.指出了隔震技术发展中需要解决的几个主要问题,例如新型隔震元件、隔震体系的开发,隔震结构的经济可行性分析,与隔震技术发展相适应的设计、施工规范等.最后在结束语中探讨了隔震设计与基于功能的设计、分灾设计等结构抗震设计思想的关系.      

Machine Learning Approaches for Metalloproteins

Metalloproteins are a family of proteins characterized by metal ion binding, whereby the presence of these ions confers key catalytic and ligand-binding properties. Due to their ubiquity among biological systems, researchers have made immense efforts to predict the structural and functional roles of metalloproteins. Ultimately, having a comprehensive understanding of metalloproteins will lead to tangible applications, such as designing potent inhibitors in drug discovery. Recently, there has been an acceleration in the number of studies applying machine learning to predict metalloprotein properties, primarily driven by the advent of more sophisticated machine learning algorithms. This review covers how machine learning tools have consolidated and expanded our comprehension of various aspects of metalloproteins (structure, function, stability, ligand-binding interactions, and inhibitors). Future avenues of exploration are also discussed.     

Panel‐based stratified cluster sampling and analysis for photovoltaic outdoor measurements

We study a stratified multisite cluster‐sampling panel time series approach in order to analyse and evaluate the quality and reliability of produced items, motivated by the problem to sample and analyse multisite outdoor measurements from photovoltaic systems. The specific stratified sampling in spatial clusters reduces sampling costs and allows for heterogeneity as well as for the analysis of spatial correlations due to defects and damages that tend to occur in clusters. The analysis is based on weighted least squares using data‐dependent weights. We show that this does not affect consistency and asymptotic normality of the least squares estimator under the proposed sampling design under general conditions. The estimation of the relevant variance–covariance matrices is discussed in detail for various models including nested designs and random effects. The strata corresponding to damages or manufacturers are modelled via a quality feature by means of a threshold approach. The analysis of outdoor electroluminescence images shows that spatial correlations and local clusters may arise in such photovoltaic data. Further, relevant statistics such as the mean pixel intensity cannot be assumed to follow a Gaussian law. We investigate the proposed inferential tools in detail by simulations in order to assess the influence of spatial cluster correlations and serial correlations on the test's size and power. ©2016 The Authors. Applied Stochastic Models in Business and Industry published by John Wiley & Sons, Ltd.     

红外双波段双层谐衍射光学系统设计

将谐衍射透镜应用在传统红外单波段佩茨瓦尔(Petzval)物镜上,设计得到工作波段处于3.4~4.2μm和8~11μm的红外双波段单层谐衍射光学系统。但单层谐衍射元件的衍射效率只在设计波长处衍射效率最高,随着波长相对设计中心波长向两侧偏离,主衍射级次的衍射效率逐渐下降。为提高含单层谐衍射元件光学系统的衍射效率,基于双层衍射元件衍射效率表达式研究了双层谐衍射元件的结构优化,给出了优化方法。设计出佩茨瓦尔型红外双波段双层谐衍射光学系统,其在3.4~4.2μm和8~11μm两个工作波段的衍射效率均达到90%以上,相比含有单层谐衍射面的光学系统衍射效率有了很大提升,提高了像面衬比度,完善了系统成像质量。     

综合性设计性实验的教学思路探讨

介绍了北京科技大学近年来面向低年级本科生开设综合性设计性实验的教学思路.在实验项目的设置上,根据实验室条件重点考虑可操作性;在实验内容方面重点考虑渐进性,让学生力所能及;在教学方式上强调引导,激发学生的研究兴趣.     

2.45GHz ECR 强流等离子体源核心部件设计与实验研究

电子回旋共振(Electron Cyclotron Resonance,ECR)等离子体源能产生高电荷态离子、高流强的单电荷态离子,提供稳定的束流和良好的重复性.核心部件的设计对ECR等离子体源是至关重要的,磁场对等离子体的生成和分布有直接影响,良好的磁场可以提高等离子体的性能和效率.采用有限元分析方法对ECR等离子体源磁场进行分析与设计,得到了满足设计需求与目标的磁场位形,通过高斯计对设计的永磁环轴向磁场精确测量,发现磁场仿真结果与实验结果吻合比较好,只是轴向磁场最大值及对应位置上有点偏差.通过集成实验,研究核心部件对离子源引出束流强度的影响,引出束流稳定且强度达到7 m A.     

KBA显微镜成像系统的成像模拟及X光成像实验的研究

KBA显微镜是一种非轴对称、非共轴的掠入射成像系统。其结构复杂,调节精度要求很高,在实际成像实验操作中难以掌握其成像特性。利用光学设计软件模拟其成像,对系统的调节和成像分析提供有益的参考。利用光学设计软件ZEMAX模拟了KBA显微镜对点源的成像过程,给出了KBA显微镜成像系统的焦深约为1 mm,景深为50 mm左右。并且由模拟可知,掠入射角对成像的影响很大。对像素尺寸约10μm的探测设备,模拟得出KBA成像系统的空间分辨力上限为3μm左右。基于星光Ⅱ装置对周期为20μm的网格靶成像,获得了KBA显微镜较为清晰的X光图像。该项工作为进一步开展掠入射成像系统的研究奠定了基础。