Polyvanadate-stimulated NADH oxidation by plasma membranes-The need for a mixture of deca and meta forms of vanadate

Polyvanadate solutions obtained by extracting vanadium pentoxide with dilute alkali over a period of several hours contained increasing amounts of decavanadate as characterized by NMR and ir spectra. Those solutions having a metavanadate:decavanadate ratio in the range of 1-5 showed maximum stimulation of NADH oxidation by rat liver plasma membranes. Reduction of decavanadate, but not metavanadate, was obtained only in the presence of the plasma membrane enzyme system. High simulation of activity of NADH oxidation was obtained with a mixture of the two forms of vanadate and this further increased on lowering the pH. Addition of increasing concentrations of decavanadate to metavanadate and vice versa increased the stimulatory activity, reaching a maximum when the metavanadate:decavanadate ratio was in the range of 1-5. Increased stimulatory activity can also be obtained by reaching these ratios by conversion of decavanadate to metavanadate by alkaline phosphate degradation, and of metavanadate to decavanadate by acidification. These studies show for the first time that both deca and meta forms of vanadate present in polyvanadate solutions are needed for maximum activity of NADH oxidation.

Vitrification, relaxation and free volume in glycerol-water binary liquid mixture:Spin probe ESR studies

Glass transition and relaxation of the glycerol-water (G-W) binary mixture system have been studied over the glycerol concentration range of 5-85 mol% by using the highly sensitive technique of electron spin resonance (ESR). For the water rich mixture the glass transition,sensed by the dissolved spin probe, arises from the vitrified mesoscopic portion of the binary system. The concentration dependence of the glass transition temperature manifests a closely related molecular level cooperativity in the system. A drastic change in the mesoscopic structure of the system at the critical concentration of 40 mol is confirmed by an estimation of the spin probe effective volume in a temperature range where the tracer reorientation is strongly coupled to the system dynamics.

Modeling transport through an environment crowded by a mixture of obstacles of different shapes and sizes

Many biological environments are crowded by macromolecules, organelles and cells which can impede the transport of other cells and molecules. Previous studies have sought to describe these effects using either random walk models or fractional order diffusion equations. Here we examine the transport of both a single agent and a population of agents through an environment containing obstacles of varying size and shape, whose relative densities are drawn from a specified distribution. Our simulation results for a single agent indicate that smaller obstacles are more effective at retarding transport than larger obstacles; these findings are consistent with our simulations of the collective motion of populations of agents. In an attempt to explore whether these kinds of stochastic random walk simulations can be described using a fractional order diffusion equation framework, we calibrate the solution of such a differential equation to our averaged agent density information. Our approach suggests that these kinds of commonly used differential equation models ought to be used with care since we are unable to match the solution of a fractional order diffusion equation to our data in a consistent fashion over a finite time period.

Gaussian mixture model based switched split vector quantization of LSF parameters

We address the issue of rate-distortion (R/D) performance optimality of the recently proposed switched split vector quantization (SSVQ) method. The distribution of the source is modeled using Gaussian mixture density and thus, the non-parametric SSVQ is analyzed in a parametric model based framework for achieving optimum R/D performance. Using high rate quantization theory, we derive the optimum bit allocation formulae for the intra-cluster split vector quantizer (SVQ) and the inter-cluster switching. For the wide-band speech line spectrum frequency (LSF) parameter quantization, it is shown that the Gaussian mixture model (GMM) based parametric SSVQ method provides 1 bit/vector advantage over the non-parametric SSVQ method.

Diffusion of Pure CH4 and Its Binary Mixture with CO2 in Faujasite NaY: A Combination of Neutron Scattering Experiments and Molecular Dynamics Simulations

The self-diffusion properties of pure CH4 and its binary mixture with CO2 within MY zeolite have been investigated by combining an experimental quasi-elastic neutron scattering (QENS) technique and classical Molecular dynamics simulations. The QENS measurements carried out at 200 K led to an unexpected self-diffusivity profile for Pure CH4 with the presence of a maximum for a loading of 32 CH4/unit cell, which was never observed before for the diffusion of apolar species in azeolite system With large windows. Molecular dynamics simulations were performed using two distinct microscopic models for representing the CH4/NaY interactions. Depending on the model, we are able to fairly reproduce either the magnitude or the profile of the self-diffusivity.Further analysis allowed LIS to provide some molecular insight into the diffusion mechanism in play. The QENS measurements report only a slight decrease of the self-diffusivity of CH4 in the presence of CO2 when the CO2 loading increases. Molecular dynamics simulations successfully capture this experimental trend and suggest a plausible microscopic diffusion mechanism in the case of this binary mixture.

Carbohydrate binding specificity of the B-cell maturation mitogen from Artocarpus integrifolia seeds

Artocarpin, a mannose-specific lectin, is a homotetrameric protein (M(r) 65,000) devoid of covalently attached carbohydrates and consists of four isolectins with pI in the range 5-6.5. Investigations of its carbohydrate binding specificity reveal that among monosaccharides, mannose is preferred over glucose. Among mannooligosaccharides, mannotriose (Man alpha 1-3[Man alpha 1-6]Man) and mannopentaose are the strongest ligands followed by Man alpha 1-3Man. Extension of these ligands by GlcNAc at the reducing ends of mannooligosaccharides tested remarkably improves their inhibitory potencies, while substitution of both the alpha 1-3 and alpha 1-6 mannosyl residues of mannotriose and the core pentasaccharide of N-linked glycans (Man alpha 1-3[Man alpha 1-6]Man beta 1-4GlcNAc beta 1-4GlcNAc) by GlcNAc or N-acetyllactosamine in beta 1-2 linkage diminishes their inhibitory potencies. Sialylated oligosaccharides are non-inhibitory. Moreover, the substitution of either alpha 1-3 or alpha 1-6 linked mannosyl residues of M5Gn or both by mannose in alpha 1-2 linkage leads to a considerable reduction of their inhibitory power. Addition of a xylose residue in beta 1-2 linkage to the core pentasaccharide improves the inhibitory activity. Considering the fact that artocarpin has the strongest affinity for the xylose containing hepasaccharide from horseradish peroxidase, which differs significantly from all the mannose/glucose-specific lectins, it should prove a useful tool for the isolation and characterization of glycoproteins displaying such structure.

Determination of mixture composition by the float balance

Herein is described a method by which component gases can be weighed as they are added one by one to a gas mixture. The float balance, designed for the purpose, is capable of determining a maximum mass of about 3 kg of a gas mixture contained in a cylinder of mass about 5 kg with a sensitivity of ±0·1 g mm-1 of the stem height.

The Isolation and Characterization of β-N-Oxalyl-L-α,β-Diaminopropionic Acid: A Neurotoxin from the Seeds of Lathyrus sativus

A neurotoxic compound has been isolated from the seeds of Lathyrus sativus in 0.5% yield and characterized as β-N-oxalyl-L-α,β-diaminopropionic acid. The compound is highly acidic in character and forms oxalic acid and diaminopropionic acid on acid hydrolysis. The compound has a specific rotation of -36.9° and has apparent pK values in the order of 1.95, 2.95, and 9.25, corresponding to the two carboxyl and one amino functions, respectively. The compound has been synthesized by reacting an aqueous methanolic solution of the copper complex of L-α,β-diaminopropionic acid prepared at pH 4.5-5.0 with dimethyl oxalate under controlled pH conditions and isolating the compound by chromatography on a Dowex 50-H+ column after precipitating the copper. The compound induced severe neurological symptoms in day-old chicks at the level of 20 mg/chick, but not in rats or mice. It also inhibited the growth of several microorganisms and of the insect larva Corcyra cephalonica Staint. L-Homoarginine had no neural action in chicks. It is suggested that the neurotoxic compound is species specific in its action and may be related to "neurolathyrism" associated with the human consumption of L. sativus seeds.

Estimation of signals in colored non gaussian noise based on Gaussian Mixture models

Non-Gaussianity of signals/noise often results in significant performance degradation for systems, which are designed using the Gaussian assumption. So non-Gaussian signals/noise require a different modelling and processing approach. In this paper, we discuss a new Bayesian estimation technique for non-Gaussian signals corrupted by colored non Gaussian noise. The method is based on using zero mean finite Gaussian Mixture Models (GMMs) for signal and noise. The estimation is done using an adaptive non-causal nonlinear filtering technique. The method involves deriving an estimator in terms of the GMM parameters, which are in turn estimated using the EM algorithm. The proposed filter is of finite length and offers computational feasibility. The simulations show that the proposed method gives a significant improvement compared to the linear filter for a wide variety of noise conditions, including impulsive noise. We also claim that the estimation of signal using the correlation with past and future samples leads to reduced mean squared error as compared to signal estimation based on past samples only.

An Empirical Study of the Mixture of Time and Movements in Prices

This paper investigates the persistent pattern in the Helsinki Exchanges. The persistent pattern is analyzed using a time and a price approach. It is hypothesized that arrival times are related to movements in prices. Thus, the arrival times are defined as durations and formulated as an Autoregressive Conditional Duration (ACD) model as in Engle and Russell (1998). The prices are defined as price changes and formulated as a GARCH process including duration measures. The research question follows from market microstructure predictions about price intensities defined as time between price changes. The microstructure theory states that long transaction durations might be associated with both no news and bad news. Accordingly, short durations would be related to high volatility and long durations to low volatility. As a result, the spread will tend to be larger under intensive moments. The main findings of this study are 1) arrival times are positively autocorrelated and 2) long durations are associated with low volatility in the market.

Ambiguity-free polarization measurements from mixture initial preparations

Starting from beam and target spin systems which are polarized in the usual way by applying external magnetic fields, measurements of appropriate final state tensor parameters, viz., {t0,1k, k=1,...,2j} of particle d with spin j in a reaction a+b→d+c1+c2+. . .are suggested to determine the reaction amplitudes in spin space free from any associated discrete ambiguity.

Crystallization and preliminary X-ray studies of a galactose-specific lectin from the seeds of bitter gourd (Momordica charantia)

A galactose-specific lectin from the seeds of bitter gourd (Momordica charantia) is a four-chain type II ribosome-inactivating protein (RIP) resulting from covalent association through a disulfide bridge between two identical copies of a two-chain unit. The available structural information on such four-chain RIPs is meagre. The bitter gourd lectin was therefore crystallized for structural investigation and the crystals have been characterized. It is anticipated that the structure of the orthorhombic crystals will be analysed using molecular replacement by taking advantage of its sequence, and presumably structural, homology to normal two-chain type II RIPs.

On the charging state of atmospheric aerosols and ion-induced nucleation

Floating in the air that surrounds us is a number of small particles, invisible to the human eye. The mixture of air and particles, liquid or solid, is called an aerosol. Aerosols have significant effects on air quality, visibility and health, and on the Earth's climate. Their effect on the Earth's climate is the least understood of climatically relevant effects. They can scatter the incoming radiation from the Sun, or they can act as seeds onto which cloud droplets are formed. Aerosol particles are created directly, by human activity or natural reasons such as breaking ocean waves or sandstorms. They can also be created indirectly as vapors or very small particles are emitted into the atmosphere and they combine to form small particles that later grow to reach climatically or health relevant sizes. The mechanisms through which those particles are formed is still under scientific discussion, even though this knowledge is crucial to make air quality or climate predictions, or to understand how aerosols will influence and will be influenced by the climate's feedback loops. One of the proposed mechanisms responsible for new particle formation is ion-induced nucleation. This mechanism is based on the idea that newly formed particles were ultimately formed around an electric charge. The amount of available charges in the atmosphere varies depending on radon concentrations in the soil and in the air, as well as incoming ionizing radiation from outer space. In this thesis, ion-induced nucleation is investigated through long-term measurements in two different environments: in the background site of Hyytiälä and in the urban site that is Helsinki. The main conclusion of this thesis is that ion-induced nucleation generally plays a minor role in new particle formation. The fraction of particles formed varies from day to day and from place to place. The relative importance of ion-induced nucleation, i.e. the fraction of particles formed through ion-induced nucleation, is bigger in cleaner areas where the absolute number of particles formed is smaller. Moreover, ion-induced nucleation contributes to a bigger fraction of particles on warmer days, when the sulfuric acid and water vapor saturation ratios are lower. This analysis will help to understand the feedbacks associated with climate change.

Nonlinear mixture autoregressive model: economic applications

The aim of this dissertation is to model economic variables by a mixture autoregressive (MAR) model. The MAR model is a generalization of linear autoregressive (AR) model. The MAR -model consists of K linear autoregressive components. At any given point of time one of these autoregressive components is randomly selected to generate a new observation for the time series. The mixture probability can be constant over time or a direct function of a some observable variable. Many economic time series contain properties which cannot be described by linear and stationary time series models. A nonlinear autoregressive model such as MAR model can a plausible alternative in the case of these time series. In this dissertation the MAR model is used to model stock market bubbles and a relationship between inflation and the interest rate. In the case of the inflation rate we arrived at the MAR model where inflation process is less mean reverting in the case of high inflation than in the case of normal inflation. The interest rate move one-for-one with expected inflation. We use the data from the Livingston survey as a proxy for inflation expectations. We have found that survey inflation expectations are not perfectly rational. According to our results information stickiness play an important role in the expectation formation. We also found that survey participants have a tendency to underestimate inflation. A MAR model has also used to model stock market bubbles and crashes. This model has two regimes: the bubble regime and the error correction regime. In the error correction regime price depends on a fundamental factor, the price-dividend ratio, and in the bubble regime, price is independent of fundamentals. In this model a stock market crash is usually caused by a regime switch from a bubble regime to an error-correction regime. According to our empirical results bubbles are related to a low inflation. Our model also imply that bubbles have influences investment return distribution in both short and long run.