Effect of trehalose accumulation on response to saline stress in Saccharomyces cerevisiae

To examine the effect of trehalose accumulation on response to saline stress in Saccharomyces cerevisiae, we constructed deletion strains of all combinations of the trehalase genes ATH1, NTH1 and NTH2 and examined their growth behaviour and intracellular trehalose accumulation under non‐stress and saline‐stress conditions. Saline stress was induced in yeast cells by NaCl addition at the exponential growth phase. All deletion strains showed similar specific growth rates and trehalose accumulation to their parent strain under non‐stress conditions. However, under the saline stress condition, one single deletion strain, nth1Δ, two double deletion strains, nth1Δ ath1Δ and nth1Δ nth2Δ, and the triple deletion strain nth1Δnth2Δ ath1Δ, all of which carry the nth1Δ deletion, showed increased trehalose accumulation as compared to the parent and other deletion strains. In particular, our statistical analysis revealed that the triple deletion strain showed a higher growth rate under the saline stress condition than the parent strain. Moreover, some deletion strains showed further trehalose accumulation under non‐stress conditions by overexpression of the TPS1 or TPS2 genes encoding the enzymes related to trehalose biosynthesis at the mid‐exponential phase. Such increased trehalose accumulation prior to NaCl addition could improve the growth of these strains under saline stress. Our results indicate that high trehalose accumulation prior to NaCl addition, rather than after NaCl addition, is necessary to achieve high growth activity under stress conditions. Copyright © 2009 John Wiley & Sons, Ltd.     

Relationship between noise characteristics in protein expressions and regulatory structures of amino acid biosynthesis pathways

Gene regulatory dynamics involves several stochastic chemical reactions. As a consequence, the copy number of given protein varies greatly among cells even in the case of isogeneic cells. Recently, the characteristics of noise in gene expressions were studied by using simple artificial gene networks. However, the noise characteristics in natural regulatory networks having complex interactions still remain unclear. In this study, we have focused on the noise in natural regulatory networks to understand the relationship between the characteristics of the noise and the structures of regulatory interactions. We targeted the expressions of genes related to amino acid biosynthesis (AAB) because of their well known regulatory structures. By measuring the noise of AAB genes in isogeneic Escherichia coli cells using flow cytometry, we found the noise amplitude in AAB genes to depend on the structure of the regulatory network. We categorised the regulatory networks with feedback regulation into two cases. In one case, the gene expression is negatively regulated by the final products of the AAB pathway known as feedback repression, whereas in another case, the gene expression is negatively regulated as a result of depletion of the substrate that is located upstream of the AAB pathway and activates the expression of the corresponding gene. Our data revealed that the noise amplitude of AAB genes in the former case is significantly smaller than the noise amplitude in the latter case. Furthermore, we found that the response time as a result of environmental changes is generally longer in the former case. This result provides a basis for understanding the role of natural regulatory networks better.     

The molecular weight ratio of monomethoxypolyethylene glycol (mPEG) to protein determines the immunotolerogenicity of mPEG proteins

Immunotolerogenic activity of monomethoxypolyethylene glycol-(mPEG) conjugated proteins is a beneficial property in proteinpharmaceutics. However, procedures for the preparation of tolerogenicmPEG proteins have not yet been defined. We prepared mPEG proteinswith different mPEG contents using three proteins, hen egg lysozyme,ovalbumin and bovine gamma globulin, and their tolerogenicitiesto antigen-specific T and B cell responses were examined. Wefound the most appropriate ratio of tolerance induction to be1.5–2.0, which is the molecular weight ratio of conjugatedtotal mPEGs to protein. This value may assist in the preparationof tolerogenic mPEG proteins.     

An attempt to stabilize nilvadipine solid dispersion by the use of ternary systems

Firstly, we investigated the physical stability of nilvadipine (NIL)/crospovidone (cl-PVP) solid dispersion during storage (40°C, 75% relative humidity) with powder x-ray diffraction, differential scanning calorimetry (DSC) and dissolution test. These studies indicated that recrystallization occurred during storage and that the dissolution of NIL greatly decreased, compared with that of the initial finding. Secondly, to improve the amorphous form physical stability of NIL, methylcellulose (MC) was added to NIL/cl-PVP solid dispersions as a dispersion carrier and NIL/cl-PVP/MC ternary solid dispersion systems were obtained by the solvent method. Powder x-ray diffraction and DSC studies indicated that the amorphous form physical stability of NIL clearly improved in the NIL/cl-PVP/MC solid dispersion systems during storage. Moreover, the dissolution properties of NIL/cl-PVP/MC solid dispersion systems were characterized by cl-PVP markedly enhancing the dissolution of NIL and MC inhibiting the change of the dissolution of NIL during storage. Finally, we obtained an ideal solid dispersion that was accompanied by a consistently higher rate of dissolution.     

A genetic network programming with learning approach for enhanced stock trading model

In this paper, an enhancement of stock trading model using Genetic Network Programming (GNP) with Sarsa Learning is described. There are three important points in this paper: First, we use GNP with Sarsa Learning as the basic algorithm while both Technical Indices and Candlestick Charts are introduced for efficient stock trading decision-making. In order to create more efficient judgment functions to judge the current stock price appropriately, Importance Index (IMX) has been proposed to tell GNP the timing of buying and selling stocks. Second, to improve the performance of the proposed GNP-Sarsa algorithm, we proposed a new method that can learn the appropriate function describing the relation between the value of each technical index and the value of the IMX. This is an important point that devotes to the enhancement of the GNP-Sarsa algorithm. The third point is that in order to create more efficient judgment functions, sub-nodes are introduced in each node to select appropriate stock price information depending on the situations and to determine appropriate actions (buying/selling). To confirm the effectiveness of the proposed method, we carried out the simulation and compared the results of GNP-Sarsa with other methods like GNP with Actor Critic, GNP with Candlestick Chart, GA and Buy&Hold method. The results shows that the stock trading model using GNP-Sarsa outperforms all the other methods.     

Numerical analysis of sleeve monopole in parallel‐plate waveguide

A monopole with double sleeves, which consists of a resonant loading and a conventional sleeve monopole, is experimentally investigated. The loaded monopole is put vertically in a parallel‐plate waveguide and driven by a coaxial feeder. The new structure exhibits a remarkably broad impedance bandwidth. In this paper, a modal expansion technique is used to numerically evaluate the impedance characteristics of the monopole by modeling the fields between the plates using cylindrical harmonic functions. A Fourier least‐square integration is applied to finding the expansion coefficients by the boundary and continuity conditions. Prior to modeling the proposed sleeve monopole, the developed analysis scheme is examined for its convergence and accuracy. Calculated results are validated by the measurements. For the optimum design at 5.8 Ghz, we investigate the effects of the structure parameters on the impedance characteristics. © 2001 John Wiley & Sons, Inc. Int J RF and Microwave CAE 11: 86–98, 2001.     

Statistical analysis of kernel-based least-squares density-ratio estimation

The ratio of two probability densities can be used for solving various machine learning tasks such as covariate shift adaptation (importance sampling), outlier detection (likelihood-ratio test), feature selection (mutual information), and conditional probability estimation. Several methods of directly estimating the density ratio have recently been developed, e.g., moment matching estimation, maximum-likelihood density-ratio estimation, and least-squares density-ratio fitting. In this paper, we propose a kernelized variant of the least-squares method for density-ratio estimation, which is called kernel unconstrained least-squares importance fitting (KuLSIF). We investigate its fundamental statistical properties including a non-parametric convergence rate, an analytic-form solution, and a leave-one-out cross-validation score. We further study its relation to other kernel-based density-ratio estimators. In experiments, we numerically compare various kernel-based density-ratio estimation methods, and show that KuLSIF compares favorably with other approaches.     

Fluorescence from poly(N-vinylcarbazole) in uniaxially stretched polymer films

Steady-state and time-resolved fluorescence properties of poly(N-vinylcarbazole) (PVCz) dispersed in a polystyrene (PS) cast film were studied under tensile loadings at room temperature. The excited monomer emission of PVCz located around 350 nm decreased with increasing applied tensile strain from 0 to 0.8%. The strain enhanced the emission which was ascribed to the partial-overlap excimer of PVCz in a 360–430 nm region. The emission due to the full-overlap excimer of PVCz between 430 and 500 nm was unchanged by the action of the tensile loadings. The ratio of fluorescence intensities at 375 nm and 345 nm I₃₇₅/I₃₄₅ was proportional to the applied strain. The time-resolved fluorescence study indicated that the lifetimes of the excited monomer and of the partial-overlap excimer were not affected by the strain. The obtained results mean that the strain applied to the PS matrix increases the partial-overlap conformation of two adjacent carbazolyl chromophores in a PVCz chain and suggest that PVCz is a useful probe for detecting residual strains in polymer matrices. © 1997 John Wiley & Sons, Inc. J Appl Polym Sci 66: 1569–1573, 1997     

A holonic control system based on a universal learning network

A new control method is presented using the holonic concept on a universal learning network (ULN). The holonic concept was proposed by Arthur Koestler in 1905. Its aim is to harmonize entire systems with partial systems that have hierarchal structures. On the other hand, a ULN that models and controls large-scale complicated systems such as industrial plants and, economic, social, and life phenomena is proposed. In this paper, a holonic control system based on the holonic concept and ULN is presented. From simulation results from a nonlinear crane system, it has been proved that holonic control can harmonize the system rather than optimize it, which used to be the conventional method in control engineering.