Identification of peptide-mediated interactions between human PTTG and SH3 domains in pALL gene expression profile

Human pituitary tumor-transforming gene (PTTG) plays an essential role in the development and progression of pediatric acute lymphoblastic leukemia (pALL). PTTG has two SH3-binding peptide motifs that can be recognized by a variety of SH3-containing proteins in the pALL through peptide-mediated interactions. In this study, the gene expression profile of pALL was examined in detail by integrating computational modeling and experimental assay, aiming to identify those potential partner proteins of human PTTG. The binding potency of domain candidates to peptide motifs was ranked using knowledge-based scoring and fluorescence titration. A number of SH3 domains found in a variety of pALL proteins were identified as potent binders with moderate or high affinity for PTTG. It is revealed that the PTTG peptide motifs show different affinity profiles for various candidate proteins, indicating that the PTTG selectivity is optimized across pALL gene expression space. The PTTG peptides were then mutated rationally to target the SH3 domains of identified partner proteins by competing with the native peptide motifs.     

基于最优特征选择与支持向量机的钱塘江涌潮检测算法

以设计一种全新的背景模型算法为目标,依据图像像素特征之间的差异,使用高斯核函数获取像素特征的概率密度,统计不同区间的密度估计值,从特征池中选择适合的像素特征组成特征模板图,以输入视频流中对应位置的像素特征值作为输入量,使用支持向量机训练固定数目的像素特征值,对比分离出前景和背景。该方法应用于钱塘江涌潮检测的结果表明,F-measure值均在65%以上,鲁棒性较强;支持向量机方法选择径向核函数的识别率超过90%,运算速度较高。该方法能减少水面波动的干扰,具有较高的精度,可为河流动力特征描述提供重要工具。     

Discovering and modeling meta-structures in human behavior from city-scale cellular data

For a long time, researchers explore spatio-temporal properties in mobility to understand human behavior. They have discovered many statistical laws about human dynamics. Unfortunately, we still have limited knowledge about the spatio-temporal structure of individuals’ movement at a large scale. In this paper, we studied the unified spatio-temporal structures (i.e., meta-structures) in human mobility. We hereby propose a meta-structure discovery algorithm by coupling both topology and spatio-temporal attributes of mobility graphs. With the construction of individual profiles from meta-structure analyses, we provided a novel mobility model from a process-driven perspective, which reduced the dependence of many existing models on the consistency between local and global mobility statistics. We gained some insights on the dominating meta-structures in human mobility by leveraging mobile data in a large city. The statistical distribution of meta-structures is found to be determined by the intrinsic heterogeneity of spatio-temporal properties in human behavior. Our model evaluation showed that a process with basic rules could demonstrate the key statistical properties in mobility meta-structures. We believe that these approaches and observations would be a good reference for management of human mobility in mobile networks and transportation systems.     

CFD Modeling of Micromixing and Velocity Distribution in a 1.7‐MHz Tubular Sonoreactor

The effect of high‐frequency (1.7 MHz) ultrasound waves on the mixing rate in a new continuous tubular sonoreactor was investigated by CFD modeling. Modeling of piezoelectric transducer (PZT) vibrations was done based on the dynamic mesh model. Results indicate that the acoustic streams were in the direction of wave propagation and their maximum velocity near the PZT surface agreed well with experimental measurements. The micromixing efficiency of the sonoreactor was studied by adopting the Villermaux/Dushman reaction in the modeling. Comparison of the calculated relative segregation index from modeling results with experimental data revealed reasonable accordance.     

Computational Fluid Dynamics modeling of micromixing performance in presence of microparticles in a tubular sonoreactor

This paper reports the results of CFD modeling for evaluating micromixing efficiency in presence of polymeric microparticles in a continuous tubular sonoreactor. The studied tubular sonoreactor was equipped with four 1.7 MHz ultrasound transducers and micromixing efficiency was analyzed using Villermaux/Dushman reaction. The main objective of this study is to illustrate the simultaneous effects of 1.7 MHz ultrasound waves and polymeric microparticles on micromixing performance from the fluid dynamics point of view. In order to model the presence of these microparticles, the Eulerian multiphase model was applied based on kinetic theory of granular flow. The dynamic mesh method was used to model the vibration of 1.7 MHz piezoelectric transducers. CFD modeling results indicate the positive effects of the presence of microparticles on micromixing efficiency and more efficient velocity distribution inside the sonoreactor. This was interpreted as the ability of high frequency ultrasound waves (1.7 MHz) to move and disperse the microparticles.     

Adjoint-based estimation and optimization for column liquid chromatography models

Simulation and optimization of chromatographic processes are continuously gaining practical importance, as they allow for faster and cheaper process development. Although a lot of effort has been put into developing numerical schemes for simulation, fast optimization and estimation algorithms also are of importance. To determine parameters for an a priori defined model, a suited approach is the inverse method that fits the measurement data to the model response.This paper presents an adjoint method to compute model parameter derivatives for a wide range of differentiable liquid chromatography models and provides practical information for the implementation in a generic simulation framework by the example of ion-exchange chromatography.The example shows that the approach is effective for parameter estimation of model proteins and superior to forward sensitivities in terms of computational effort. An optimization of peak separation in salt step elution demonstrates that the method is not restricted to inverse parameter estimation.     

Parametric virtual laboratory development: A hydropower case study with student perspectives

In order to take advantage of trends such as genetic-design students need to be familiar, and comfortable, with the concept of parametric computer models and how their parameters relate to physical-forms. Virtual learning software can aid in creating that understanding and help support studies at all undergraduate levels in engineering design disciplines. As an example, hydropower rotors are complex and largely rely on computational analysis of geometries for single rotor types. That problem can be significantly overcome using a parametric algorithm capable of creating an almost-infinite variety of computer models. Therefore, this paper investigates the shared parametric properties of common crossflow hydropower rotor geometries, resulting in a generic model that is then used to illustrate application in real-time interactive virtual learning software capable of producing accurate stereoscopic images and stereolithography files for 3D printing, as well as linking to constructive solid geometry software for slower, but more detailed, analysis. A pilot survey of student attitudes to the virtual learning prototype and resulting geometries is then discussed, illustrating the potential for 3D graphics as an effective addition to virtual learning of parametric design methods, and giving initial direction for future work.     

In vitro inhibition of dipeptidyl peptidase IV by peptides derived from the hydrolysis of amaranth (Amaranthus hypochondriacus L.) proteins

Bioactive compounds present in foods could potentially have beneficial effects on human health. In this study we report the in vitro inhibitory capacity of peptides released from amaranth seed proteins after enzymatic digestion, against dipeptidyl peptidase IV (DPPIV); an enzyme known to deactivate incretins, hormones involved in insulin secretion. Other seeds, such as soybean, black bean, and wheat were also tested. The highest inhibition of DPPIV was observed with amaranth peptides released after simulated gastrointestinal digestion, showing an IC₅₀ of 1.1 mg/mL in a dose-dependent manner. In silico tryptic digestion of amaranth globulins was carried out releasing peptides larger than 13 residues. Some of these peptides were used for the in silico prediction of their binding modes with DPPIV. Docking models showed that the possible mechanism of globulin peptides to inhibit DPPIV was through blocking the active dimer formation. Peptides were also found inside the major cavity where the natural substrates reach the catalytic site of the enzyme. This is the first report of the identification of inhibitory DPPIV peptides from amaranth hydrolysates and the prediction of their binding modes at the molecular level, leading to their possible use as functional food ingredients in the prevention of diabetes.     

Selection of injection conditions for aluminum particles as a raw material by numerical analysis in the synthesis of ultrafine particles with transferred type arc plasma

We investigated by numerical analysis the dependence of vaporization behavior of aluminum particles injected into transferred type arc plasma on injection conditions in synthesis of aluminum nitride ultra fine particles. On the basis of calculation results, we chose one proper injection condition where aluminum particles vaporized more. © 2009 Wiley Periodicals, Inc. Electr Eng Jpn, 170(2): 46–52, 2010; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20852