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BackgroundmiRNAs circulating in the blood in a cell-free form have been acknowledged for their potential as readily accessible disease markers. Presently, histological examination is the golden standard for diagnosing and grading liver disease, therefore non-invasive options are desirable. Here, we investigated if miRNA expression profile in exosome rich fractionated serum could be useful for determining the disease parameters in patients with chronic hepatitis C (CHC).MethodologyExosome rich fractionated RNA was extracted from the serum of 64 CHC and 24 controls with normal liver (NL). Extracted RNA was subjected to miRNA profiling by microarray and real-time qPCR analysis. The miRNA expression profiles from 4 chronic hepatitis B (CHB) and 12 non alcoholic steatohepatitis (NASH) patients were also established. The resulting miRNA expression was compared to the stage or grade of CHC determined by blood examination and histological inspection.Principal FindingsmiRNAs implicated in chronic liver disease and inflammation showed expression profiles that differed from those in NL and varied among the types and grades of liver diseases. Using the expression patterns of nine miRNAs, we classified CHC and NL with 96.59% accuracy. Additionally, we could link miRNA expression pattern with liver fibrosis stage and grade of liver inflammation in CHC. In particular, the miRNA expression pattern for early fibrotic stage differed greatly from that observed in high inflammation grades.ConclusionsWe demonstrated that miRNA expression pattern in exosome rich fractionated serum shows a high potential as a biomarker for diagnosing the grade and stage of liver diseases.

The Pearson correlation coefficient with its sign flipped is used to measure the dissimilarity of the gene activities in transcriptional response of cell-cycle-synchronized human fibroblasts to serum. These dissimilarity data have been analyzed with our nMDS algorithm to produce an almost circular relational pattern of the genes. The obtained pattern expresses a temporal order in the data in this example; the temporal expression pattern of the genes rotates along this circular arrangement and is related to the cell cycle. For the data we analyze in this paper we observe the following. If an appropriate preparation procedure is applied to the original data set, linear methods such as the principal component analysis (PCA) could achieve reasonable results, but without data preprocessing linear methods such as PCA cannot achieve a useful picture. Furthermore, even with an appropriate data preprocessing, the outcomes of linear procedures are not as clear-cut as those by nMDS without preprocessing.

Convection and fluidization in a vibrated bed of powder are reproduced in a numerical simulation. In the simulation, each particle of the powder, during a collision, has a viscoelastic interaction with the other colliding particle. Because of the discreteness of the particles, this elasticity causes convection. The critical values of fluidization and convection agree with experiments. PACS numbers: 46.10,+z, 02.60.+y, 47.25.Qv Recently, many physicists [1,2] have studied the dynamics of granular materials, because these materials behave differently from continuous media like rigid, elastic, or viscous bodies. This difference is because granular materials behave in two distinct ways: as a set of particles and as continuous media. For example, granular materials under gravity can have a slope with nonzero angle (angle of repose) in the quasistationary state. Avalanches are also characteristic features in the dynamics of granular materials.One of the stranger phenomena is convection in a fluidized bed under vertical vibration [3][4][5][6][7]. A schematic figure of a typical experimental setup is shown in Fig. 1. When a vessel containing a large number of small particles is shaken strongly, heaping of the surface starts spontaneously. At the same time, convection of particles starts. Experimentalists claim that these phenomena are dynamical phase transitions.Moreover, convection is localized near the surface (surface fluidization). The depth of the convection region increases as the strength of the vibration increases. The purpose of this paper is to propose a numerical modeling to reproduce the convective motion and surface fluidization effect.Our model is a very simple one [1,8]. However, no one has pointed out that this model can reveal an instability in the fluidized bed [9]. In this model, each particle is regarded as a sphere with definite diameter d. When particles collide with one another, they penetrate into each other. During the collision, there is a viscoelastic interac-J tion between them. The equation the particles obey isx/ -xy -d X/~Xy |x/-Xy| + »/(v/-Vy) -g> where 0(x) is a step function, TV is the total number of spheres, x, is the position vector of the ith sphere, and k and 77 are the elastic constant and the viscosity coefficient, respectively, g is the acceleration of gravity and v is velocity. The step function restricts the interaction between particles to periods when the distance between two particles is less than d.In order to understand the physical meanings of the two interaction parameters k and 77, we consider the case n glass spheres • 0cm / diameter im$^6&?S&9999S8pS& 5mm io~i CPH b c 0 s CL> 0 t FIG. 1. A schematic of a typical experiment.where two spheres collide head-on with each other. In this case, they have an effective coefficient of restitution e =exp( --qn/(o). The time interval during a collision is also a function of k and 77. We call this interval the collision time, t CQ \=7t/(o [a> = (2& -77 2 ) 1/2 ]. Therefore, fixing k and 77 determines the effective coefficient of...

BackgroundPredicting the three-dimensional structure of a protein from its amino acid sequence is a long-standing goal in computational/molecular biology. The discrimination of different structural classes and folding types are intermediate steps in protein structure prediction.ResultsIn this work, we have proposed a method based on linear discriminant analysis (LDA) for discriminating 30 different folding types of globular proteins using amino acid occurrence. Our method was tested with a non-redundant set of 1612 proteins and it discriminated them with the accuracy of 38%, which is comparable to or better than other methods in the literature. A web server has been developed for discriminating the folding type of a query protein from its amino acid sequence and it is available at http://granular.com/PROLDA/.ConclusionAmino acid occurrence has been successfully used to discriminate different folding types of globular proteins. The discrimination accuracy obtained with amino acid occurrence is better than that obtained with amino acid composition and/or amino acid properties. In addition, the method is very fast to obtain the results.