p53抑癌基因电化学阻抗传感器研究

基于电化学阻抗技术构建了一种检测p53抑癌基因的电化学传感器.首先利用自组装作用将末端带巯基的探针p53抑癌基因(p53-DNA)固定于金电极表面,根据传感器结合前后电子转移阻抗值的变化,对目标p53-DNA进行了测定.以pH =7.4的5mmol/L K3[Fe(CN)6]-5mmol/L K4[Fe(CN)6]平衡电对溶液作为检测液,检测目标p53-DNA的线性浓度范围为1.0×10-8～ 1.0×10-6 mol/L,其检出限为3.0×10-9 mol/L(S/N =3).对5.0×10-8 mol/L的目标p53-DNA进行11次平行测定,其RSD为3.4％.该传感器制作简单、灵敏高、选择性好,且无需标记,易于操作.     

On the performance-driven load distribution for heterogeneous computational grids

Load balancing has been a key concern for traditional multiprocessor systems. The emergence of computational grids extends this challenge to deal with more serious problems, such as scalability, heterogeneity of computing resources and considerable transfer delay. In this paper, we present a dynamic and decentralized load balancing algorithm for computationally intensive jobs on a heterogeneous distributed computing platform. The time spent by a job in the system is considered as the main issue that needs to be minimized. Our main contributions are: (1) Our algorithm uses site desirability for processing power and transfer delay to guide load assignment and redistribution, (2) Our transfer and location policies are a combination of two specific strategies that are performance driven to minimize execution cost. These two policies are the Instantaneous Distribution Policy (IDP) and the Load Adjustment Policy (LAP), (3) The communication overhead involved in information collection is reduced using mutual information feedback. The simulation results show that our proposed algorithm outperforms conventional approaches over a wide range of system parameters.     

Computational screening and design of S100B ligand to block S100B–p53 interaction

The binding of S100B to p53 disables the biological function of p53 as a tumor suppressor and thus causes cancer. It is very important to explore the interaction between S100B and p53 and to develop inhibitors to block the interaction in anti-cancer development. In this work, the interaction of S100B to p53 was studied using molecular dynamics (MD) at the atomic level and organic molecules have been identified as potential inhibitors to block the S100B–p53 interaction. It was indicated in the simulations that S100B residues around GLU45 and GLU46 play an important role in the binding of S100B to p53. The three dimensional structure of S100B obtained from S100B–p53 complex (PDB ID: 1DT7) was used as the target protein receptor. Multiple LUDI screenings for S100B ligands were performed using different searching radii 6.23 Å, 7.23 Å, 8.23 Å, 9.23 Å and 10.23 Å with a searching center which was defined as the geometrical center of S100B residues that are within 5 Å from the p53 C-terminal peptide in the complex. Potential organic compounds were screened from the ZINC database using LUDI program implemented in Cerius2 package and evaluated as potential S100B ligands to block the S100B–p53 interaction. The top-scored compounds were selected for binding affinity calculation. The results show that these top-scored ZINC compounds bind in the location where p53 binds and interact with S100B in a similar fashion as p53, and therefore it is expected that they have the potential to block S100B from binding to p53. The ADME and toxicity properties of the potential S100B ligands were also evaluated.     

A computational environment for the management, processing, and analysis of geological data

The complexity and diversity of data and processing now being used in geoscientific data analysis are increasing at such a pace that it is difficult to maintain a single software package capable of performing all required tasks. A typical solution is to use a number of commercial software packages loosely linked via file format conversion routines or other customized communication paths. Creating and maintaining these paths is made difficult by both the number of distinct packages being used and the evolutionary changes taking place within each package. In this paper we attempt to create a generic model for a geological data processing task, identify some of the difficulties involved in performing these tasks using current technology, and outline a computational architecture that may correct many of the deficiencies of existing technology. Our goal is not to provide a detailed design but to present some key issues and possible solutions as a foundation for discussion and investigation.     

Preparation of an electrochemical PNA biosensor for detection of target DNA sequence and single nucleotide mutation on p53 tumor suppressor gene corresponding oligonucleotide

Development of an electrochemical biosensor based on peptide nucleic acid (PNA) probe for detection of target DNA sequence and single nucleotide mutation in p53 tumor suppressor gene corresponding oligonucleotide using methylene blue (MB) as an electrochemical indicator is described. The interaction between MB and short sequence of p53, one of the most important tumor suppressor genes due to its dysfunction in the majority of human cancers, was studied by differential pulse voltammety (DPV). Probe modified electrode was prepared by self-assembled monolayer (SAM) formation of thiolated PNA molecules on the surface of gold electrode (GE). The hybridization of PNA probe with target DNA was performed in solution to form PNA-DNA hybrid on the surface of the GE. A significant increase in the reduction signal of MB was observed upon hybridization of the probe with the complementary DNA. The selectivity of the biosensor was studied using noncomplementary oligonucleotides. Furthermore, our results confirmed the ability of the sensor to detect single base mismatch in the sample oligonucleotide. The influence of probe concentration on the effective discrimination against noncomplementary sequence and point mutation was also investigated. Diagnostic performance of the biosensor is described and the detection limit is found 6.82 × 10⁻¹⁰ M. The electrochemical impedance spectroscopy was also employed to further investigate the sensor function.     

On the design of global object space for efficient multi-threading Java computing on clusters

The popularity of Java and recent advances in compilation and execution technology for Java are making the language one of the preferred ones in the field of high-performance scientific and engineering computing. A distributed Java Virtual Machine supports transparent parallel execution of multi-threaded Java programs on a cluster of computers. It provides an alternative platform for high-performance scientific computations. In this paper, we present the design of a global object space for a distributed JVM. It virtualizes a single Java object heap across machine boundaries to facilitate transparent object accesses. We leverage runtime object connectivity information to detect distributed shared objects (DSOs) that are reachable from threads at different nodes to facilitate efficient memory management in the distributed JVM. Based on the concept of DSO, we propose a framework to characterize object access patterns, along three orthogonal dimensions. With this framework, we are able to effectively calibrate the runtime memory access patterns and dynamically apply optimized cache coherence protocols to minimize consistency maintenance overhead. The optimization devices include an object home migration method that optimizes the single-writer access pattern, synchronized method migration that allows the execution of a synchronized method to take place remotely at the home node of its locked object, and connectivity-based object pushing that uses object connectivity information to optimize the producer–consumer access pattern. Several benchmark applications in scientific computing have been tested on our distributed JVM. We report the performance results and give an in-depth analysis of the effects of the proposed adaptive solutions.