Applications of protein microarrays for biomarker discovery

The search for new biomarkers for diagnosis, prognosis, and therapeutic monitoring of diseases continues in earnest despite dwindling success at finding novel reliable markers. Some of the current markers in clinical use do not provide optimal sensitivity and specificity, with the prostate cancer antigen (PSA) being one of many such examples. The emergence of proteomic techniques and systems approaches to study disease pathophysiology has rekindled the quest for new biomarkers. In particular the use of protein microarrays has surged as a powerful tool for large-scale testing of biological samples. Approximately half the reports on protein microarrays have been published in the last two years especially in the area of biomarker discovery. In this review, we will discuss the application of protein microarray technologies that offer unique opportunities to find novel biomarkers.     

Quantitative proteomic approaches for biomarker discovery

The rapid advances in proteomic technologies have made possible systematic analysis of hundreds to thousands of proteins in clinical samples with the promise of uncovering novel protein biomarkers for various disease conditions. We will discuss in this review article current MS and protein chip-based quantitative proteomic approaches and their application in biomarker discovery. The emphasis will be placed on new quantification strategies employing stable isotopic labeling coupled with MS/MS, and antibody-based protein chips and nanodevices. The strength and weakness of each technology are briefly highlighted.     

对于网格计算工具包NetSolve的分析与研究

系统地研究了高性能计算的网格应用中间件NetSolve系统的结构和工作原理，并对服务器端进行了深入探讨，指出了现有实现存在的缺陷，对改进方案进行了分析。     

Body fluid proteomics: Prospects for biomarker discovery

Many diseases are caused by perturbations of cellular signaling pathways and related pathway networks as a result of genetic aberrations. These perturbations are manifested by altered cellular protein profiles in the fluids bathing tissue/organs (i.e., the tissue interstitial fluid, TIF). A major challenge of clinical chemistry is to quantitatively map these perturbed protein profiles - the so-called "signatures of disease" - using modern proteomic technologies. This information can be utilized to design protein biomarkers for the early detection of disease, monitoring disease progression and efficacy of drug action. Here, we discuss the use of body fluids in the context of prospective biomarker discovery, and the marked 1000-1500-fold dilution of body fluid proteins, during their passage from TIF to the circulatory system. Further, we discuss proteomics strategies aimed at depleting major serum proteins, especially albumin, in order to focus on low-abundance protein/peptides in plasma. A major limitation of depletion strategies is the removal of low-molecular weight protein/peptides which specifically bind major plasma proteins. We present a prototype model, using albumin, for understanding the multifaceted nature of biomarker research, highlighting the involvement of albumin in Alzheimer's disease. This model underscores the need for a system-level understanding for biomarker research and personalized medicine.     

McEliece公钥密码体制中问题的分析研究

使用线性分组码用于构造M公钥体制本质上就是使用线性分组码构造M公钥体制的安全.研究了其它线性分组码用于构造M公钥体制的可行性;分析了M公钥体制中G、S、P是保密的,实现随机选取G、S、P成为了建立M公钥体制的关键;分析了满秩矩阵S和置换矩阵P的随机产生问题,并得到了一些重要结果;这些结果不仅对M公钥体制是适用的,而且对其它纠错码体制和方案也同样是有用的.     

网络坦克作战系统基于MAS的决策过程分析与研究

网络坦克作战系统的决策过程是一个群组决策过程.系统决策过程实质上是各组成部分协作进行问题求解的过程.基于多Agent系统(MAS)的网络坦克作战系统决策是系统中多个Agent面向作战任务进行协作问题求解的过程.运用MAS技术对系统的决策过程进行了分析,提出了系统基于MAS的群组决策基本框架,给出了分布式的系统决策结构,并对决策过程进行了设计和详细分析.MAS协作规划有利于系统的群组决策.     

Development of a model-based clinical sepsis biomarker for critically ill patients

Sepsis occurs frequently in the intensive care unit (ICU) and is a leading cause of admission, mortality, and cost. Treatment guidelines recommend early intervention, however positive blood culture results may take up to 48 h. Insulin sensitivity (S_I) is known to decrease with worsening condition and could thus be used to aid diagnosis. Some glycemic control protocols are able to accurately identify insulin sensitivity in real-time.Hourly model-based insulin sensitivity S_I values were calculated from glycemic control data of 36 patients with sepsis. The hourly S_I is compared to the hourly sepsis score (ss) for these patients (ss = 0-4 for increasing severity). A multivariate clinical biomarker was also developed to maximize the discrimination between different ss groups. Receiver operator characteristic (ROC) curves for severe sepsis (ss ≥ 2) are created for both S_I and the multivariate clinical biomarker.Insulin sensitivity as a sepsis biomarker for diagnosis of severe sepsis achieves a 50% sensitivity, 76% specificity, 4.8% positive predictive value (PPV), and 98.3% negative predictive value (NPV) at an S_I cut-off value of 0.00013 L/mU/min. Multivariate clinical biomarker combining S_I, temperature, heart rate, respiratory rate, blood pressure, and their respective hourly rates of change achieves 73% sensitivity, 80% specificity, 8.4% PPV, and 99.2% NPV. Thus, the multivariate clinical biomarker provides an effective real-time negative predictive diagnostic for severe sepsis. Examination of both inter- and intra-patient statistical distribution of this biomarker and sepsis score shows potential avenues to improve the positive predictive value.     

A nature-inspired biomarker for mental concentration using a single-channel EEG

Neural Computing and Applications - We developed a system for measuring the attentional process during the performance of specific activities. The proposed biomarker device is able to estimate the...     

面向方面编程的分析与研究

深入地分析了传统面向对象编程方式在项目开发中出现的问题,明确指出了面向对象建模技术的内在局限性,提出了一种新型的,实用的、面向方面的编程方式.在介绍面向方面编程(AOP)原理和思想的基础上深入分析了AOP的实质.详细讨论了采用AOP进行具体开发的步骤和实现过程.通过几个静态指标详细分析和评测了由AOP开发的一个项目实例,体现了采用AOP进行软件开发的强大优势.     

Towards clinical applications of selected reaction monitoring for plasma protein biomarker studies

The widespread clinical adoption of protein biomarkers with diagnostic, prognostic and/or predictive value remains a formidable challenge for the biomedical community. From discovery to validation, the path to biomarkers of clinical relevance abounds with many protein candidates, yet so few concrete examples have been substantiated. In this review, we focus on the recent adoption of selected reaction monitoring (SRM) of plasma proteins in the path to clinical use for a broad range of diseases including cancer, cardiovascular disease, genetic disorders and various metabolic disorders. Recent progress reveals a promising outlook for clinical applications using SRM, which now provides the routine analysis of clinically relevant protein markers at low nanogram per millilitre in plasma.     

GeoPDEs: A research tool for Isogeometric Analysis of PDEs

GeoPDEs (http://geopdes.sourceforge.net) is a suite of free software tools for applications on Isogeometric Analysis (IGA). Its main focus is on providing a common framework for the implementation of the many IGA methods for the discretization of partial differential equations currently studied, mainly based on B-Splines and Non-Uniform Rational B-Splines (NURBS), while being flexible enough to allow users to implement new and more general methods with a relatively small effort. This paper presents the philosophy at the basis of the design of GeoPDEs and its relation to a quite comprehensive, abstract definition of IGA.     

The interface between biomarker discovery and clinical validation: The tar pit of the protein biomarker pipeline

The application of "omics" technologies to biological samples generates hundreds to thousands of biomarker candidates; however, a discouragingly small number make it through the pipeline to clinical use. This is in large part due to the incredible mismatch between the large numbers of biomarker candidates and the paucity of reliable assays and methods for validation studies. We desperately need a pipeline that relieves this bottleneck between biomarker discovery and validation. This paper reviews the requirements for technologies to adequately credential biomarker candidates for costly clinical validation and proposes methods and systems to verify biomarker candidates. Models involving pooling of clinical samples, where appropriate, are discussed. We conclude that current proteomic technologies are on the cusp of significantly affecting translation of molecular diagnostics into the clinic.     

无尺度网络分析与研究

讲述了无尺度网络的发现及其特性,介绍了无尺度网络对于科学研究的意义,并指出了其面临的挑战。     

证书撤销机制的分析与研究

数字证书是实现电子政务和电子商务中实体的信任及信任验证的关键元素.CA实际可能会根据不同的情况而导致证书的意外作废或撤销,那么应使要使用证书的用户尽可能获知最新的证书情况,这对于实现PKI系统的可信性至关重要.通过分析国内外通常采用的CRL和OCSP这两种基本的证书撤销、查询方法,总结了它们的优缺点以及在实际应用过程中遇到的难点.最后提出了相应的改进措施,使用户能及时获得最新的证书状况,为电子政务和电子商务提供更可靠的安全性.     

Analysis of keyword networks in MIS research and implications for predicting knowledge evolution

New concepts and ideas build on older ones. This path dependence in knowledge evolution has promoted research to identify important knowledge elements, research trends, and opportunities by analyzing publication data. In our study, keyword networks formed from published academic articles were analyzed to examine how keywords are associated with each other and to identify important keywords and their change over time. Based on MIS publication data from 1999 to 2008, our analysis provided several notable findings. First, while the MIS field has changed rapidly, resulting in many new keywords, the connectivity among them is highly clustered. Second, the keyword networks show clear power-law distribution, which implies that the more popular a keyword, the more likely it is selected by new researchers and used in follow-on studies. In addition, a strong hierarchical structure is identified in the network. Third, the network-based perspective reveals interdisciplinary keywords which are different from popular ones and have the potential to lead research in the MIS field.     

A mechanical biomarker of cell state in medicine

The mechanical properties of cells have been shown to be useful markers of cell state by the biophysics community. Here, I highlight clinical and research problems that this label-free, potentially inexpensive cellular biomarker can address and discuss technical challenges to realize automated instruments to achieve robust and high-throughput mechanical measurements. Important features found in traditional fluorescence-based flow cytometry that can enable cytometry based on mechanical properties (i.e., deformability cytometry) are emphasized, especially the need for throughput, simple operation, multidimensional data visualization, and internal controls. Next-generation approaches to automate deformability measurements of cells are surveyed, and future directions are outlined that promise to bring low-cost mechanical measurements to medicine and biological research.     

1394总线关键协议分析与研究

在新一代飞机安全关键/任务关键系统中,对总线的实时性、确定性、可靠性提出更高的要求。1394总线协议通过规范强制根节点、静态分配通道号、纵向奇偶校验、STOF同步、异步流包通信及发送/接收端电气特性指标等约束,保证了总线传输的高实时、高确定及高可靠性。针对1394总线在安全关键/任务关键系统中的应用需求,分别从总线拓扑结构、总线包格式和总线可靠性三方面对1394总线关键协议进行详细分析与研究,为1394总线设计、实现及系统应用奠定了理论基础。     

MIMO系统多包接收性能分析

多包接收MPR(Muhi-Packet Reception)技术能够极大地提高无线网络吞吐量,它可以同时接收多个数据包并进行有效的分离.多输入多输出系统MIMO (Multiple-Input Multiple-Output)是一种实现MPR的高效技术,对提高无线通信系统性能具有重要意义.文章对4×4天线配置下的MIMO系统MPR进行仿真并分析其误码性能.仿真分析表明,MIMO不仅能获得分集和复用增益,而且能实现一种多包接收功能并能同时正确分离多个数据包.     

面向模式分析与设计方法应用研究

随着软件系统复杂程度的增加,一个完整的系统已不能由一个单独的模式建立起来,它将是多个模式的组合。面向模式的分析与设计关注于模式作为类的合成体的组合技术,将模式作为设计单元,通过对模式的合成和精练来优化程序设计,有利于快速的开发出更具有可扩展性和可维护性的软件系统。