In Silico/In Vitro Hit-to-Lead Methodology Yields SMYD3 Inhibitor That Eliminates Unrestrained Proliferation of Breast Carcinoma Cells

SMYD3 is a lysine methyltransferase that regulates the expression of over 80 genes and is required for the uncontrolled proliferation of most breast, colorectal, and hepatocellular carcinomas. The elimination of SMYD3 restores normal expression patterns of these genes and halts aberrant cell proliferation, making it a promising target for small molecule inhibition. In this study, we sought to establish a proof of concept for our in silico/in vitro hit-to-lead enzyme inhibitor development platform and to identify a lead small molecule candidate for SMYD3 inhibition. We used Schrodinger^® software to screen libraries of small molecules in silico and the five compounds with the greatest predicted binding affinity within the SMYD3 binding pocket were purchased and assessed in vitro in direct binding assays and in breast cancer cell lines. We have confirmed the ability of one of these inhibitors, Inhibitor-4, to restore normal rates of cell proliferation, arrest the cell cycle, and induce apoptosis in breast cancer cells without affecting wildtype cell behavior. Our results provide a proof of concept for this fast and affordable small molecule hit-to-lead methodology as well as a promising candidate small molecule SMYD3 inhibitor for the treatment of human cancer.     

Histometric study of meat products. A literature review

In the present paper, the literature on the development of methods for histometric monitoring the quality of meats is reviewed. The value of specific techniques, statistical interpretation of results and the practicability of automation of histometric analysis are examined more closely. It is concluded from the study of the literature that histometric examination of meats allows an objective assessment of volume percentages of tissue components. When a distinct difference in contrast between various tissues is achieved by specific staining methods, developments in the field of image analysis systems will allow automation of the quantitative histological examination of meats.     

An algebraic theory of object-oriented systems

The paper presents an algebraic specification of net objects. By net objects we mean those that are defined in object-oriented paradigms and those defined with nested relations in complex database models. An algebraic specification is set up that involves structures of net objects, accesses of net objects, and some features of object-oriented programming, such as multiple inheritance and polymorphism. Objects and their relationships are then characterized formally in the modeling, which utilizes the hierarchical approach in the algebraic theory of abstract data types, and is further developed by adding mechanisms from existing object systems. Categories of net objects are presented with the properties of accesses among them     

Probabilistic assessment of loss in revenue generation in demand-driven production

In Demand-driven Production with Just-in-Time inputs, there are several sources of uncertainty which impact on the manufacturer??s ability to meet the required customer??s demand within the given time frame. This can result in a loss of revenue and customers, which will have undesirable impacts on the financial aspects and on the viability of the manufacturer. Hence, a key concern for manufacturers in just-in-time production is to determine whether they can meet a specific level of demand within a given time frame, to meet the customers?? orders and also to achieve the required revenue target for that period of time. In this paper, we propose a methodology by which a manufacturer can ascertain the probability of not meeting the required demand within a given period by considering the uncertainties in the availability of production units and raw materials, and the loss of financial revenue that it would experience as a result.     

Incorporating Prior Knowledge in the Form of Production Rules into Neural Networks Using Boolean-Like Neurons

At present, nearly all neural networks are formulated by learning only from examples or patterns. For a real-word problem, some forms of prior knowledge in a non-example form always exist. Incorporation of prior knowledge will benefit the formulation of neural networks. Prior knowledge could be in several forms. Production rule is one form in which the prior knowledge is frequently represented. This paper proposes an approach to incorporate production rules into neural networks. A newly defined neuron architecture, Boolean-like neuron, is proposed. With this Boolean-like neuron, production rules can be encoded into the neural network during the network initialization period. Experiments are described in this paper. The results show that the incorporation of this prior knowledge can not only increase the training speed, but also the explainability of the neural networks.     

多壁碳纳米管湿敏传感器的研究

传感器的基底为Al板电化学氧化成Al2O3绝缘层模板,上面真空溅射了叉指金电极,在电极之间旋涂微量多壁碳纳米管的水悬浊液,干燥后作为敏感膜.室温下测试传感器暴露在不同湿度的电阻变化,发现吸附了H2O后传感器的导电能力降低,且下降的幅度与被测湿度有良好的梯度关系.同时该多壁碳纳米管再经缩合剂EDC修饰后旋涂于电极上形成的敏感膜对湿度呈指数级变化.对它们的湿敏响应的机理进行了一些初步的探讨.     

Privacy Ontology Support for E-Commerce

Privacy is becoming increasingly important due to the advent of e-commerce. E-commerce applications frequently require customers to divulge many personal details about themselves that must be protected carefully in accordance with privacy principles and regulations. Here, the authors define a privacy ontology to support the provision of privacy and help derive the level of privacy associated with e-commerce transactions and applications. The privacy ontology provides a framework against which e-commerce sites can benchmark their privacy policies and implementations.     

基于WebGIS的城市供水管网系统的设计与实现

介绍了基于WebGIS的城市供水管网信息系统的体系结构、功能组成以及供水管网建模技术.城市供水管网系统主要包括管网建模、查询统计、爆管事故分析、运行状态监控、漏损分析、系统维护等六个方面.城市供水管网建模是进行城市供水系统规划、设计、分析与优化调度的重要支撑技术,充分发挥WebGIS的分布式与可视化地理空间信息分析的优势,结合城市供水管网的管理需求,将WebGIS技术应用到城市供水管网的建模中.该系统可为城市供水部门的高效管理提供决策依据.     

Software complexity and its impact on software reliability

To produce reliable software, its complexity must be controlled by suitably decomposing the software system into smaller subsystems. A software complexity metric is developed that includes both the internal and external complexity of a module. This allows analysis of a software system during its development and provides a guide to system decomposition. The basis of this complexity metric is in the development of an external complexity measure that characterizes module interaction