Association of INAD with NORPA is essential for controlled activation and deactivation of Drosophila phototransduction in vivo

Visual transduction in Drosophila is a G protein-coupled phospholipase C-mediated process that leads to depolarization via activation of the transient receptor potential (TRP) calcium channel. Inactivation-no-afterpotential D (INAD) is an adaptor protein containing PDZ domains known to interact with TRP. Immunoprecipitation studies indicate that INAD also binds to eye-specific protein kinase C and the phospholipase C, no-receptor-potential A (NORPA). By overlay assay and site-directed mutagenesis we have defined the essential elements of the NORPA-INAD association and identified three critical residues in the C-terminal tail of NORPA that are required for the interaction. These residues, Phe-Cys-Ala, constitute a novel binding motif distinct from the sequences recognized by the PDZ domain in INAD. To evaluate the functional significance of the INAD-NORPA association in vivo, we generated transgenic flies expressing a modified NORPA, NORPAC1094S, that lacks the INAD interaction. The transgenic animals display a unique electroretinogram phenotype characterized by slow activation and prolonged deactivation. Double mutant analysis suggests a possible inaccessibility of eye-specific protein kinase C to NORPAC1094S, undermining the observed defective deactivation, and that delayed activation may similarly result from NORPAC1094S being unable to localize in close proximity to the TRP channel. We conclude that INAD acts as a scaffold protein that facilitates NORPA-TRP interactions required for gating of the TRP channel in photoreceptor cells.     

Gastric mucosal biopsy via a nasogastric tube: a nonendoscopic method for diagnosing fundic and antral mucosal gastritis and Helicobacter pylori infection in man

Synthesis of poly(gamma-glutamate) metabolites of natural folates and antifolates is a critical process. Folypolyglutamates are essential for cell proliferation. Polyglutamates of glutamate (Glu)-containing antifolates are often critical for their cytotoxic action and are relevant to antifolate resistance. However, the role of polyglutamate synthesis in selectivity is less clear. We have undertaken a research program to further define the significance of polyglutamate metabolism and to devise ways to exploit this metabolism to achieve greater therapeutic selectivity in cancer chemotherapy. This article briefly reviews several approaches tested thus far. Inhibition of folypolyglutamate synthesis should lead to cell death. Current ornithine (Orn)-containing folate-based inhibitors of the enzyme responsible for their synthesis, folypolyglutamate synthetase (FPGS), are poorly transported, apparently because of interference by the protonated delta-amine. Replacement of Orn with 4, 4-difluoroOrn, the delta-amine of which has a much lower pKa and is thus less protonated at physiological pH, was explored. Since it is unclear how polyglutamylation contributes to selectivity, we explored generic means either to eliminate or to enhance polyglutamylation. The data indicate that substitution for Glu in an antifolate by some Glu analogs in which the gamma-COOH is either altered or replaced (e.g., gamma-tetrazole-Glu) leads to loss of both FPGS substrate activity and binding; antifolate target specificity is unchanged, while uptake is actually enhanced. Substitution of 3,3-difluoroGlu for Glu leads to enhanced polyglutamylation (although probably only to the diglutamate), retention of target specificity, and at least equal uptake. Comparative studies of the same antifolate containing different replacements for Glu, such as gamma-tetrazole-Glu (no polyglutamylation) or 3,3-difluoroGlu (enhanced polyglutamylation), will be useful in exploring the role and significance of polyglutamylation.     

Unified equation of state based on the lattice fluid theory for phase equilibria of complex mixtures part I. Molecular thermodynamic framework

Consistent calculation of fugacities of fluid mixtures remains as one of the most important subjects in contemporary molecular thermodynamics. In practice, equations of state (EOSs) and g^E-models have been used. However, most EOSs are erroneous for condensed phases at high densities and g^E-models are inapplicable for pressuresensitive systems. Recently to remedy the shortcomings in both approaches, there has been a surge of new g^E-EOS mixing rules. By equating any set of EOS and g^E-models, the limitations in both approaches could be resolved significantly. However, the self-consistency in the underlying concept of those mixing rules remains controversial. During the last several years, the present authors proposed a new lattice-fluid EOS and its simplification relevant to phase equilibrium calculations. Without employing any g^E-EOS mixing rule and with only two parameters for a pure component and one adjustable interaction energy parameter for a binary mixture, results obtained to date demonstrated that the EOSs are quantitatively applicable to a great variety of phase equilibrium properties of mixtures, especially, for complex and/or macromolecular systems. In the present article we summarize the EOSs and extended the applications to liquid-liquid Equilibria. In part I, we discussed briefly the molecular thermodynamic aspects of general derivation of the EOS and a brief discussion of applying the EOSs to pure fluids while the illustrative application to various real mixture systems is discussed in part II.     

Improved performances of a S-SEED using extremely shallowquantum-wells and asymmetric Fabry-Perot cavity structure

The authors report significantly improved performances of a symmetric self-electrooptic-effect device (S-SEED), with high on-off contrast ratio (>30:l) and large optical bistability loop widths (ΔP=44%) at an applied bias of V_a=0 V, i.e., with no power supply. The S-SEED is made of extremely shallow quantum wells (ESQWs) in an asymmetric Fabry-Perot (AFP) cavity structure. At V_a =5 V ΔP increased by up to 95%, preserving the high contrast ratio. The reflectivity changes at V_a=0 and 5 V were about 15% and 30%, respectively. These are believed to be the largest values ever reported for such structures     

Eigenvalues and eigenvectors of covariance matrices for signalsclosely spaced in frequency

The eigenstructures of common covariance matrices are identified for the general case of M closely spaced signals. It is shown that the largest signal-space eigenvalue is relatively insensitive to signal separation. By contrast, the ith largest eigenvalue is proportional to δω^2(i-1) or δω^4(i-1), where δω is a measure of signal separation. Therefore, matrix conditioning degrades rapidly as signal separation is reduced. It is also shown that the limiting eigenvectors have remarkably simple structures. The results are very general, and apply to planar far-field direction-finding problems involving almost arbitrary scenarios, and also to time-series analysis of sinusoids, exponentials, and other signals     

Reliability and performance analysis of time – space – time switching networks with multiple separated space switches

Since electronic switching systems usually require very strict reliability requirements as well as good performance objectives, we need to jointly analyse the performance and reliability of switching systems. In this paper, we compare conventional time–space–time switches with single space switches with those with multiple separated space switches, from the viewpoints of reliability and performance. We consider time–space–time switching networks which consist of N incoming time switches, i.e. one NxN space switch, two (N/2)x(N/2) space switches, and four (N/4)x(N/4) space switches. We introduce a Markov reliability model to study the effect of failures and analyse the reliability and performance of three different types of switching networks in terms of average blocking probability and the mean time to unreliable operation, as we vary the offered traffic. As a result, T–S–T switching networks with multiple separated space switches exhibit better performance and reliability than those with single space switches.     

Modified atmosphere packaging of a mixed prepared vegetable salad dish

The aim of this study was to design a modified atmosphere package for a mixed vegetable salad consisting of 75 g of cut carrot, 55 g of cut cucumber, 20 g of sliced garlic and 50 g of whole green pepper. Respiration data of all the components were combined with film permeability data to predict package atmospheres and design optimal packages for experimental testing for improved shelf-life of the produce. The optimal package avoided minimum O₂ and maximum CO₂ tolerance limits, and chilling injury temperatures for any component. A pouch form package made of 27 mm low density polyethylene developed a modified atmosphere of 2.0–2.1% O₂ and 5.5–5.7% CO₂, which was beneficial for all components and provided better quality retention than other test packages.     

Detecting delaminations in a composite beam using anti-optimization

The present study proposes a detection technique for delaminations in a laminated beam. The proposed technique optimizes the spatial distribution of harmonic excitation so as to magnify the difference in response between the delaminated and intact beam. The technique is evaluated by numerical simulation of two-layered aluminum beams. Effects of measurement and geometric noise are included in the analysis. A finite element model for a delaminated composite, based on a layer-wise laminated plate theory is used in conjunction with a step function to simulate delaminations     

A neural network-based power system stabilizer using power flowcharacteristics

A neural network-based power system stabilizer (neuro-PSS) is designed for a generator connected to a multi-machine power system utilizing the nonlinear power flow dynamics. The use of power flow dynamics provides a PSS for a wide range of operation with reduced size neural networks. The neuro-PSS consists of two neural networks: neuro-identifier and neuro-controller. The low-frequency oscillation is modeled by the neuro-identifier using the power flow dynamics, then a generalized backpropagation-through-time (GBTT) algorithm is developed to train the neuro-controller. The simulation results show that the neuro-PSS designed in this paper performs well with good damping in a wide operation range compared with the conventional PSS