In response to various extracellular signals, the morphology of the human fungal pathogen Candida albicans switches from yeast to hypha form. Here, we report that GPR1 encoding a putative G-protein-coupled receptor and GPA2 encoding a G␣ subunit are required for hypha formation and morphogenesis in C. albicans. Mutants lacking Gpr1 (gpr1/gpr1) or Gpa2 (gpa2/gpa2) are defective in hypha formation and morphogenesis on solid hypha-inducing media. These phenotypic defects in solid cultures are suppressed by exogenously added dibutyryl-cyclic AMP (dibutyryl-cAMP). Biochemical studies also reveal that GPR1 and GPA2 are required for a glucose-dependent increase in cellular cAMP. An epistasis analysis indicates that Gpr1 functions upstream of Gpa2 in the same signaling pathway, and a two-hybrid assay reveals that the carboxyl-terminal tail of Gpr1 interacts with Gpa2. Moreover, expression levels of HWP1 and ECE1, which are cAMP-dependent hyphaspecific genes, are reduced in both mutant strains. These findings support a model that Gpr1, as well as Gpa2, regulates hypha formation and morphogenesis in a cAMP-dependent manner. In contrast, GPR1 and GPA2 are not required for hypha formation in liquid fetal bovine serum (FBS) medium. Furthermore, the gpr1 and the gpa2 mutant strains are fully virulent in a mouse infection. These findings suggest that Gpr1 and Gpa2 are involved in the glucose-sensing machinery that regulates morphogenesis and hypha formation in solid media via a cAMP-dependent mechanism, but they are not required for hypha formation in liquid medium or during invasive candidiasis.

A new identification method was proposed for an eduction of vortex sheet structures in turbulent flows. This method took advantage of a prominent feature of a sheet, i.e., comparable dominance of both strain rate and vorticity and their strong correlation. The effectiveness of the proposed method was presented in the assessment using direct numerical simulation data for homogeneous isotropic turbulence. Both strain rate and vorticity were indeed large and correlated in the region identified using the proposed method. As a result, intense dissipation took place in the educed region. The relationship between the eigenvalue solution used in the present method and the invariants of fourth-order moments of velocity gradients was discussed. It was shown that the proposed method performed better than other invariants and previous identification methods for educing the vortex sheets.

( Zn 1−y Mg y ) 1−x Al x O powders were synthesized by the polymerized complex method and then consolidated by spark plasma sintering apparatus. The microscopic structure and thermoelectric properties were examined comparing with the experimental results of the samples prepared by the conventional solid-state reaction method. A small amount of ZnAl2O4 spinel phase as the second phase was observed in the sintered samples with x⩾0.02 by x-ray diffraction and a scanning electron microscope. The grain size of the samples prepared by the polymerized complex method is much smaller than that of the samples prepared by the conventional solid-state reaction method. The absolute values of the Seebeck coefficient and electrical resistivity decrease with increasing x up to about x=0.01, but above x=0.01 they are almost independent of x. This result indicates that the solubility limit of Al in Zn1−xAlxO is about x=0.01, which is also confirmed by Al27 nuclear magnetic resonance spectroscopy. At a fixed composition of x, the absolute values of the Seebeck coefficient and electrical resistivity for the samples prepared by the polymerized complex method are smaller than those for the samples prepared by the solid-state reaction method, which indicates that the doping of the carrier into the material can be more easily realized in the samples prepared by the polymerized complex method. The thermal conductivity decreases with increasing x, but the further suppression of the thermal conductivity was attained by the additional substitution on the Zn site by Mg. The Seebeck coefficient of (Zn1−yMgy)1−xAlxO is almost independent of Mg content y, but the electrical resistivity increases with increasing y. As a result, (Zn0.90Mg0.10)0.9975Al0.0025O shows a maximum dimensionless figure of merit of 0.10 at 1073 K.

Aromatic amino acid decarboxylases (AADCs) are found in various organisms and play distinct physiological roles. AADCs from higher eukaryotes have been well studied because they are involved in the synthesis of biologically important molecules such as neurotransmitters and alkaloids. In contrast, bacterial AADCs have received less attention because of their simplicity in physiology and in target substrate (tyrosine). In the present study, we found that Pseudomonas putida KT2440 possesses an AADC homologue (PP_2552) that is more closely related to eukaryotic enzymes than to bacterial enzymes, and determined the genetic and enzymic characteristics of the homologue. The purified enzyme converted 3,4-dihydroxyphenyl-L-alanine (DOPA) to dopamine with K m and k cat values of 0.092 mM and 1.8 s "1 , respectively. The enzyme was essentially inactive towards other aromatic amino acids such as 5-hydroxy-L-tryptophan, Lphenylalanine, L-tryptophan and L-tyrosine. The observed strict substrate specificity is distinct from that of any AADC characterized so far. The proposed name of this enzyme is DOPA decarboxylase (DDC). Expression of the gene was induced by DOPA, as revealed by quantitative RT-PCR analysis. DDC is encoded in a cluster together with a LysR-type transcriptional regulator and a major facilitator superfamily transporter. This genetic organization is conserved among all sequenced P. putida strains that inhabit the rhizosphere environment, where DOPA acts as a strong allelochemical. These findings suggest the possible involvement of this enzyme in detoxification of the allelochemical in the rhizosphere, and the potential occurrence of a horizontal gene transfer event between the pseudomonad and its host organism.

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To predict software quality, we must consider various factors because software development consists of various activities, which the software reliability growth model (SRGM) does not consider.In this paper, we propose a model to predict the final quality of a software product by using the Bayesian belief network (BBN) model. By using the BBN, we can construct a prediction model that focuses on the structure of the software development process explicitly representing complex relationships between metrics, and handling uncertain metrics, such as residual faults in the software products. In order to evaluate the constructed model, we perform an empirical experiment based on the metrics data collected from development projects in a certain company. As a result of the empirical evaluation, we confirm that the proposed model can predict the amount of residual faults that the SRGM cannot handle.

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During software development, projects often experience risky situations. If projects fail to detect such risks, they may exhibit confused behavior. In this paper, we propose a new scheme for characterization of the level of confusion exhibited by projects based on an empirical questionnaire. First, we designed a questionnaire from five project viewpoints, requirements, estimates, planning, team organization, and project management activities. Each of these viewpoints was assessed using questions in which experience and knowledge of software risks are determined. Secondly, we classify projects into Bconfused'' and Bnot confused,'' using the resulting metrics data. We thirdly analyzed the relationship between responses to the questionnaire and the degree of confusion of the projects using logistic regression analysis and constructing a model to characterize confused projects. The experimental result used actual project data shows that 28 projects out of 32 were characterized correctly. As a result, we concluded that the characterization of confused projects was successful. Furthermore, we applied the constructed model to data from other projects in order to detect risky projects. The result of the application of this concept showed that 7 out of 8 projects were classified correctly. Therefore, we concluded that the proposed scheme is also applicable to the detection of risky projects.