Abrogation of p53 function affects gadd gene responses to DNA base-damaging agents and starvation

The tumor suppressor p53 is required for induction of its downstream effector genes such as GADD45 and CIP1/WAF1 by ionizing radiation (IR). This response is probably mediated through defined p53 binding sites located in the promoter of CIP1/WAF1 and in the third intron of GADD45. In contrast, the gadd gene stress response to base-damaging agents, such as methylmethane sulfonate (MMS) or UV radiation, or medium depletion (starvation) occurs in all mammalian cells examined to date regardless of p53 status for both GADD45 and also GADD153, which is not IR-responsive in many lines with functional p53. These agents strongly induce the p53 protein and raise the possibility that, although p53 is not required for the typical "gadd" response to these agents, p53 may contribute to these non-IR stress responses. This possibility was confirmed by the finding that disruption of p53 function by transfection with dominant-negative vectors expressing HPV E6, mutant p53, or SV40 T Ag reduced the induction of GADD45 and GADD153 as measured by increases in mRNA and protein levels in human lines with wild-type p53. Similarly, induction of these genes by MMS or UV radiation was consistently stronger in the parental mouse embryo fibroblasts compared to cells derived from mice where both p53 alleles had been deleted. Similar qualitative responses were also seen for CIP1/WAF1. In agreement with reduced induction of p53-regulated genes, the G1 checkpoint activated by MMS or UV radiation was markedly abrogated in p53-wt human MCF-7 breast carcinoma cells by E6 expression. Interestingly, induction of reporter constructs driven by the GADD45 or GADD153 promoters was substantially reduced in human cells transfected with mutant p53 or E6 expression vectors or in cells lacking p53 following treatment with MMS, UV radiation, or starvation. Because neither promoter is inducible by IR, and neither contains a strong p53 binding site, these results indicate that p53 has a synergistic or cooperative role in these non-IR stress responses for both GADD45 and GADD153, and that this role is not mediated through identifiable p53-binding sites.     

Dependency mining-based causal message logging

In fault-tolerant computing, the approach of causal message logging provides on-demand stable logging and enables the independent recovery of nodes. It imposes the requirement that the dependency between non-deterministic events needs to be known for nodes. The dependency information is disseminated through messages. A central problem in traditional causal message logging is that if the message logging progress of nodes cannot be effectively tracked, some redundant dependency information will be piggybacked on the messages. In this paper, a dependency mining based approach is proposed. It tries to detect the message logging progress of nodes only from the dependency between non-deterministic events, without needing to piggyback an additional dependency vector or dependency matrix on each message.     

企业对标管理信息系统的应用研究

对某炼化企业的对标管理信息系统的应用进行研究分析,从系统模型、逻辑流程、系统功能设计等进行了深入的分析,并对此系统为企业管理带来的影响进行了全面讨论,肯定了该系统在企业对标管理过程中的重要作用.     

Model Transduction for Triangle Meshes

This paper proposes a novel method, called model transduction, to directly transfer pose between different meshes, without the need of building the skeleton configurations for meshes. Different from previous retargetting methods, such as deformation transfer, model transduction does not require a reference source mesh to obtain the source deformation, thus effectively avoids unsatisfying results when the source and target have different reference poses. Moreover, we show other two applications of the model ...     

一种基于边界约束的流形展开方法

在流形学习的谱方法中, 流形展开被表述为优化问题. 这些优化问题的解是退化的, 即所有的样本将被嵌入到同一个点. 为了避免退化解, 谱方法对嵌入坐标人为地强加了一个单位协方差矩阵约束. 然而, 该约束往往导致流形展开的失真非常明显. 本文提出一种新的流形学习方法, 彻底抛弃了人为的单位协方差矩阵约束. 主要思路是先对流形边界进行嵌入, 然后再求流形内部的嵌入; 流形边界的嵌入位置被确定后, 流形内部样本的嵌入位置将被边界拉开, 使得它们不会都收缩到一个点上, 从而避免了退化解的出现. 将流形边界的嵌入位置作为边界条件, 求解一个线性方程组来得到内部样本的嵌入; 该线性方程组反映了尽量保持邻近样本间距离不变的要求. 流形边界的嵌入由简化流形的嵌入求出; 为此, 本文还设计了一种流形边界检测算法以及一种流形简化算法. 与目前代表性的几种流形学习方法进行了比较实验, 结果表明了本文方法的有效性, 其展开失真比谱方法明显要小.     

网络图形最短路径算法分析与研究

着重对求网络图上每一对节点之间最短路径的矩阵算法及Floyed算法进行分析与比较,详述它们的功能、原理及异同点,以求在实际应用中合理选择恰当的算法。     

基于ARM-WINCE系统的EVC图像处理界面开发

基于ARM-WINCE的嵌入式图像分析与处理系统与基于PC计算机的图像处理系统相比,具有速度更快、体积更小、应用灵活及成本更低等特点。介绍基于ARM-WINCE平台,在EVC(Embedded Visual C++)环境下开发静态图像处理用户界面,进行图像分析和算法实现。实验结果表明用EVC开发的图像用户界面应用于嵌入式图像处理系统效果良好。     

Gaussian kernel optimization: Complex problem and a simple solution

The Gaussian kernel function implicitly defines the feature space of an algorithm and plays an essential role in the application of kernel methods. The parameter of Gaussian kernel function is a scalar that has significant influences on final results. However, until now, it is still unclear how to choose an optimal kernel parameter. In this paper, we propose a novel data-driven method to optimize the Gaussian kernel parameter, which only depends on the original dataset distribution and yields a simple solution to this complex problem. The proposed method is task irrelevant and can be used in any Gaussian kernel-based approach, including supervised and unsupervised machine learning. Simulation experiments demonstrate the efficacy of the obtained results. A user-friendly online calculator is implemented at: www.csbio.sjtu.edu.cn/bioinf/kernel/ for public use.     

Structural reliability assessment based on probability and convex set mixed model

This paper investigates the reliability assessment of structures exhibiting both stochastic and bounded uncertainties by using a probability and convex set mixed model. The safety measure of a structure is quantified by a reliability index defined by a nested minimization problem. An iterative procedure is developed for seeking the worst-case point and the most probable failure point in the standard uncertainty space. Numerical examples are given to demonstrate the applicability of the probability and convex set mixed model representation in the structural reliability assessment, as well as to illustrate the validity and effectiveness of the proposed numerical method.     

Nonlinear Dimensionality Reduction by Local Orthogonality Preserving Alignment

We present a new manifold learning algorithm called Local Orthogonality Preserving Alignment (LOPA). Our algorithm is inspired by the Local Tangent Space Alignment (LTSA) method that aims to align multiple local neighborhoods into a global coordinate system using affine transformations. However, LTSA often fails to preserve original geometric quantities such as distances and angles. Although an iterative alignment procedure for preserving orthogonality was suggested by the authors of LTSA, neither the corresponding initialization nor the experiments were given. Procrustes Subspaces Alignment (PSA) implements the orthogonality preserving idea by estimating each rotation transformation separately with simulated annealing. However, the optimization in PSA is complicated and multiple separated local rotations may produce globally contradictive results. To address these difficulties, we first use the pseudo-inverse trick of LTSA to represent each local orthogonal transformation with the unified global coordinates. Second the orthogonality constraints are relaxed to be an instance of semi-definite programming (SDP). Finally a two-step iterative procedure is employed to further reduce the errors in orthogonal constraints. Extensive experiments show that LOPA can faithfully preserve distances, angles, inner products, and neighborhoods of the original datasets. In comparison, the embedding performance of LOPA is better than that of PSA and comparable to that of state-of-the-art algorithms like MVU and MVE, while the runtime of LOPA is significantly faster than that of PSA, MVU and MVE.