Comparing Several Parametric and Nonparametric Approaches to Time Series Clustering: A Simulation Study

One key point in cluster analysis is to determine a similarity or dissimilarity measure between data objects. When working with time series, the concept of similarity can be established in different ways. In this paper, several non-parametric statistics originally designed to test the equality of the log-spectra of two stochastic processes are proposed as dissimilarity measures between time series data. Their behavior in time series clustering is analyzed throughout a simulation study, and compared with the performance of several model-free and model-based dissimilarity measures. Up to three different classification settings were considered: (i) to distinguish between stationary and non-stationary time series, (ii) to classify different ARMA processes and (iii) to classify several non-linear time series models. As it was expected, the performance of a particular dissimilarity metric strongly depended on the type of processes subjected to clustering. Among all the measures studied, the nonparametric distances showed the most robust behavior.     

Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways

Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.     

Cystatin C inhibits amyloid-beta deposition in Alzheimer's disease mouse models

Using transgenic mice expressing human cystatin C (encoded by CST3), we show that cystatin C binds soluble amyloid-beta peptide and inhibits cerebral amyloid deposition in amyloid-beta precursor protein (APP) transgenic mice. Cystatin C expression twice that of the endogenous mouse cystatin C was sufficient to substantially diminish amyloid-beta deposition. Thus, cystatin C has a protective role in Alzheimer's disease pathogenesis, and modulation of cystatin C concentrations may have therapeutic implications for the disease.     

EP4 receptor stimulation down-regulates human eosinophil function

Accumulation of eosinophils in tissue is a hallmark of allergic inflammation. Here we observed that a selective agonist of the PGE₂ receptor EP4, ONO AE1-329, potently attenuated the chemotaxis of human peripheral blood eosinophils, upregulation of the adhesion molecule CD11b and the production of reactive oxygen species. These effects were accompanied by the inhibition of cytoskeletal rearrangement and Ca²⁺ mobilization. The involvement of the EP4 receptor was substantiated by a selective EP4 antagonist, which reversed the inhibitory effects of PGE₂ and the EP4 agonist. Selective kinase inhibitors revealed that the inhibitory effect of EP4 stimulation on eosinophil migration depended upon activation of PI 3-kinase and PKC, but not cAMP. Finally, we found that EP4 receptors are expressed by human eosinophils, and are also present on infiltrating leukocytes in inflamed human nasal mucosa. These data indicate that EP4 agonists might be a novel therapeutic option in eosinophilic diseases.     

A Symbolic-Numeric Approach for Parametrizing Ruled Surfaces

This paper presents symbolic algorithms to determine whether a given surface(implicitly or parametrically defined) is a rational ruled surface and find a proper parametrization of the ruled surface. However, in practical applications, one has to deal with numerical objects that are given approximately, probably because they proceed from an exact data that has been perturbed under some previous measuring process or manipulation. For these numerical objects, the authors adapt the symbolic algorithms presented by means of the use of numerical techniques. The authors develop numeric algorithms that allow to determine ruled surfaces close to an input(not necessarily ruled)surface, and the distance between the input and the output surface is computed.     

SV40 transformed fibroblasts recognize the same 140 kD fibronectin chemotactic fragment as non-transformed cells

SV40-virus-transformed human embryonal fibroblasts show an enhanced chemotactic response to the glycoprotein fibronectin. However, they recognize the same chemotactic active region as non-transformed fibroblasts. The result suggests that an enhancement of chemotaxis by fibroblasts which have been transformed with Simian Virus 40 is due not to the utilization of further chemotactic domains in the molecule, but to an increased sensitivity of the cells to the chemoattractant.