Site-Specific PEGylation of Therapeutic Proteins

The use of proteins as therapeutics has a long history and is becoming ever more common in modern medicine. While the number of protein-based drugs is growing every year, significant problems still remain with their use. Among these problems are rapid degradation and excretion from patients, thus requiring frequent dosing, which in turn increases the chances for an immunological response as well as increasing the cost of therapy. One of the main strategies to alleviate these problems is to link a polyethylene glycol (PEG) group to the protein of interest. This process, called PEGylation, has grown dramatically in recent years resulting in several approved drugs. Installing a single PEG chain at a defined site in a protein is challenging. Recently, there is has been considerable research into various methods for the site-specific PEGylation of proteins. This review seeks to summarize that work and provide background and context for how site-specific PEGylation is performed. After introducing the topic of site-specific PEGylation, recent developments using chemical methods are described. That is followed by a more extensive discussion of bioorthogonal reactions and enzymatic labeling.     

User Interfaces for Complex Engineering Software: Application of Virtual Reality

IT systems for engineers are becoming more numerous and complex and will further proliferate in the future. It is infeasible to expect users to be trained to work with a plethora of systems, especially as many of them will only see occasional use. Therefore, in the near future, systems will need user interfaces that allow intuitive access and usage. This paper examines a new style of user interface based on virtual reality.     

The VLISP verified PreScheme compiler

This paper describes a verified compiler for PreScheme, the implementation language for thevlisp run-time system. The compiler and proof were divided into three parts: A transformational front end that translates source text into a core language, a syntax-directed compiler that translates the core language into a combinator-based tree-manipulation language, and a linearizer that translates combinator code into code for an abstract stored-program machine with linear memory for both data and code. This factorization enabled different proof techniques to be used for the different phases of the compiler, and also allowed the generation of good code. Finally, the whole process was made possible by carefully defining the semantics ofvlisp PreScheme rather than just adopting Scheme's. We believe that the architecture of the compiler and its correctness proof can easily be applied to compilers for languages other than PreScheme.This work was supported by Rome Laboratory of the United States Air Force, contract No. F19628-89-C-0001, through the MITRE Corporation, and by NSF and DARPA under NSF grants CCR-9002253 and CCR-9014603. Author's current address: Department of Computer Science and Engineering, Oregon Graduate Institute, P.O. Box 91000, Portland, OR 97291-1000.The work reported here was supported by Rome Laboratory of the United States Air Force, contract No. F19628-89-C-0001. Preparation of this paper was generously supported by The MITRE Corporation.This work was supported by Rome Laboratory of the United States Air Force, contract No. F19628-89-C-0001, through the MITRE Corporation, and by NSF and DARPA under NSF grants CCR-9002253 and CCR-9014603.     

Anonymity preserving sequential pattern mining

The increasing availability of personal data of a sequential nature, such as time-stamped transaction or location data, enables increasingly sophisticated sequential pattern mining techniques. However, privacy is at risk if it is possible to reconstruct the identity of individuals from sequential data. Therefore, it is important to develop privacy-preserving techniques that support publishing of really anonymous data, without altering the analysis results significantly. In this paper we propose to apply the Privacy-by-design paradigm for designing a technological framework to counter the threats of undesirable, unlawful effects of privacy violation on sequence data, without obstructing the knowledge discovery opportunities of data mining technologies. First, we introduce a k-anonymity framework for sequence data, by defining the sequence linking attack model and its associated countermeasure, a k-anonymity notion for sequence datasets, which provides a formal protection against the attack. Second, we instantiate this framework and provide a specific method for constructing the k-anonymous version of a sequence dataset, which preserves the results of sequential pattern mining, together with several basic statistics and other analytical properties of the original data, including the clustering structure. A comprehensive experimental study on realistic datasets of process-logs, web-logs and GPS tracks is carried out, which empirically shows how, in our proposed method, the protection of privacy meets analytical utility.     

小议JavaScript库——Dojo、jQuery和PrototypeJS的比较

这是一篇小文章,讨论了JavaScript的应用库,JavaScript是最近两年飞速发展的技术领域,希望这篇文章能引发你的兴趣,帮助你进入这个领域。     

理解LINQ-to-SQL

大多数Web应用程序都是以数据驱动的,并且以关系数据库为中心。然而,多年来架构师已经设计了通过对象来建模问题域的应用程序。对象和关系数据库之间的通信一直都不流畅和简单。建立这类通信时遇到的困难通常称为“对象/关系阻抗失配”（O/ RM）。需要一个持久层来保存对象和从关系表载入对象。这些年来,产生了许多设计样式,为从事这项任务的架构师提供指南。现在,开发人员可以自己编写整个持久层,或者借助像NHibernate或Genome等O/RM工具的帮助,进行设计。     

An enhanced Support Vector Machine classification framework by using Euclidean distance function for text document categorization

This paper presents the implementation of a new text document classification framework that uses the Support Vector Machine (SVM) approach in the training phase and the Euclidean distance function in the classification phase, coined as Euclidean-SVM. The SVM constructs a classifier by generating a decision surface, namely the optimal separating hyper-plane, to partition different categories of data points in the vector space. The concept of the optimal separating hyper-plane can be generalized for the non-linearly separable cases by introducing kernel functions to map the data points from the input space into a high dimensional feature space so that they could be separated by a linear hyper-plane. This characteristic causes the implementation of different kernel functions to have a high impact on the classification accuracy of the SVM. Other than the kernel functions, the value of soft margin parameter, C is another critical component in determining the performance of the SVM classifier. Hence, one of the critical problems of the conventional SVM classification framework is the necessity of determining the appropriate kernel function and the appropriate value of parameter C for different datasets of varying characteristics, in order to guarantee high accuracy of the classifier. In this paper, we introduce a distance measurement technique, using the Euclidean distance function to replace the optimal separating hyper-plane as the classification decision making function in the SVM. In our approach, the support vectors for each category are identified from the training data points during training phase using the SVM. In the classification phase, when a new data point is mapped into the original vector space, the average distances between the new data point and the support vectors from different categories are measured using the Euclidean distance function. The classification decision is made based on the category of support vectors which has the lowest average distance with the new data point, and this makes the classification decision irrespective of the efficacy of hyper-plane formed by applying the particular kernel function and soft margin parameter. We tested our proposed framework using several text datasets. The experimental results show that this approach makes the accuracy of the Euclidean-SVM text classifier to have a low impact on the implementation of kernel functions and soft margin parameter C.     

Operator precedence and the visibly pushdown property

Floyd?s operator precedence grammars and languages (FG, FL) are a classical subclass of deterministic context-free (DCF) grammars and languages. We prove that several recently introduced language families motivated by the needs of model checking and of specifying XML-like languages are proper subsets of FL. The main cases considered include visibly pushdown languages (VPL) and balanced languages (BALAN), which are characterized by restricted precedence relations. FL have all the closure properties available for regular languages and generally viewed as necessary for application to model checking: reversal, prefixing and suffixing, concatenation, Kleene star, and boolean operations. All but the last results are new, and some require complex proofs, due to the necessary changes of syntax structure. Thus FL are the largest known subfamily of DCF having the same closure properties as VPL. FG, unlike VPL grammars, which are intended for abstract syntax modelling, are structurally adequate to specify real programming languages.     

Nano and Microtechnologies for the Study of Magnetotactic Bacteria

Magnetotactic bacteria (MTB) naturally synthesize magnetic nanoparticles that are wrapped in lipid membranes. These membrane‐bound particles, which are known as magnetosomes, are characterized by their narrow size distribution, high colloidal stability, and homogenous magnetic properties. These characteristics of magnetosomes confer them with significant value as materials for biomedical and industrial applications. MTB are also a model system to study key biological questions relating to formation of bacterial organelles, metal homeostasis, biomineralization, and magnetoaerotaxis. The similar size scale of nano and microfluidic systems to MTB and ease of coupling to local magnetic fields make them especially useful to study and analyze MTB. In this Review, a summary of nano‐ and microtechnologies that are developed for purposes such as MTB sorting, genetic engineering, and motility assays is provided. The use of existing platforms that can be adapted for large‐scale MTB processing including microfluidic bioreactors is also described. As this is a relatively new field, future synergistic research directions coupling MTB, and nano‐ and microfluidics are also suggested. It is hoped that this Review could start to bridge scientific communities and jump‐start new ideas in MTB research that can be made possible with nano‐ and microfluidic technologies.     

Performance Driven WS Orchestration and Deployment in Service Oriented Infrastructure

Composite Web services (WS) can be seen as software systems designed according to workflow-based orchestration of building blocks or simpler WS. Each block has its own specifications concerning both functional and non-functional properties. While the characteristics of each block have a scope limited to its domain, the WS must guarantee service levels that are usually described by global end-to-end metrics. The problem of relating local to global objectives in WS orchestration is hard to approach. In this context, some WS components have to be deployed in distributed service oriented infrastructure mixing heterogeneous systems belonging to private and/or public providers. In this paper we propose a performance-driven technique for designing and deploying composite WS on heterogeneous service oriented infrastructure. Users having different requirements in terms of resource demands and performance objectives are considered. Several WS deployment alternatives, involving both physical and virtual resources provided by the infrastructure, are evaluated to identify the logical (workflow) and physical (deployment) configuration allowing to meet the requirements. In order to demonstrate the suitability of the proposed approach to the service oriented context, an example of a travel management WS is described and the optimal deployment of the components in a hybrid infrastructure is investigated.