The Sulfonylurea Drug, Glimepiride, Stimulates Glucose Transport, Glucose Transporter Translocation, and Dephosphorylation In Insulin-Resistant Rat Adipocytes In Vitro

Sulfonylurea drugs are widely used in the therapy of NIDDM. The improvement of glucose tolerance after long-term treatment of NIDDM patients with the drug can be explained by stimulation of glucose utilization in peripheral tissues that are characterized by insulin resistance in these patients. We studied whether the novel sulfonylurea drug, glimepiride, stimulates glucose transport into isolated insulin-resistant rat adipocytes. After long-term incubation of the cells in primary culture with high concentrations of glucose, glutamine, and insulin, stimulation of glucose transport by insulin was significantly reduced both with respect to maximal responsiveness (65% decrease of Vmax) and sensitivity (2.6-fold increase of ED50) compared with adipocytes cultured in medium containing a low concentration of glucose and no insulin. This reflects insulin resistance of glucose transport. In contrast, both responsiveness and sensitivity of glucose transport toward stimulation by glimepiride were only marginally reduced in insulin-resistant adipocytes (15% decrease of Vmax; 1.2-fold increase of ED50) versus control cells. Glimepiride, in combination with glucose and glutamine during the primary culture, caused desensitization of the glucose transport system toward stimulation by insulin, but to a lesser degree than insulin itself (50% reduction of Vmax; ninefold increase of ED50). Again, the maximal responsiveness and sensitivity of glucose transport toward stimulation by glimepiride were only slightly diminished. The presence of glimepiride during primary culture did not antagonize the induction of insulin resistance of glucose transport. The stimulation of glucose transport in insulin-resistant adipocytes by glimepiride is caused by translocation of glucose transporters from low-density microsomes to plasma membranes as demonstrated by subcellular fractionation and immunoblotting with anti-GLUT1 and anti-GLUT4 antibodies. Immunoprecipitation of GLUT4 from 32Pi- and [35S]methionine-labeled adipocytes revealed that the insulin resistance of GLUT4 translocation is accompanied by increased (three- to fourfold) phosphorylation of GLUT4 in both low-density microsomes and plasma membranes. Short-term treatment of desensitized adipocytes with glimepiride or insulin reduced GLUT4 phosphorylation by ∼70 and 25%, respectively, in both fractions. We conclude that glimepiride activates glucose transport by stimulation of GLUT1 and GLUT4 translocation in rat adipocytes via interference at a site downstream of the putative molecular defect in the signaling cascade between the insulin receptor and the glucose transport system induced by high concentrations of glucose and insulin. The molecular site of glimepiride action is related to GLUT4 phosphorylation/dephosphorylation, which may regulate glucose transporter activity and translocation. These in vitro findings implicate an additional mode of sulfonylurea action in the improvement of glucose tolerance of NIDDM patients.</jats:p

Detecting relevant changes in time series models

Most of the literature on change-point analysis by means of hypothesis testing considers hypotheses of the form H0 : \theta_1 = \theta_2 vs. H1 : \theta_1 != \theta_2, where \theta_1 and \theta_2 denote parameters of the process before and after a change point. This paper takes a different perspective and investigates the null hypotheses of no relevant changes, i.e. H0 : ||\theta_1 - \theta_2|| ? \leq \Delta?, where || \cdot || is an appropriate norm. This formulation of the testing problem is motivated by the fact that in many applications a modification of the statistical analysis might not be necessary, if the difference between the parameters before and after the change-point is small. A general approach to problems of this type is developed which is based on the CUSUM principle. For the asymptotic analysis weak convergence of the sequential empirical process has to be established under the alternative of non-stationarity, and it is shown that the resulting test statistic is asymptotically normal distributed. Several applications of the methodology are given including tests for relevant changes in the mean, variance, parameter in a linear regression model and distribution function among others. The finite sample properties of the new tests are investigated by means of a simulation study and illustrated by analyzing a data example from economics.Comment: Keywords: change-point analysis, CUSUM, relevant changes, precise hypotheses, strong mixing, weak convergence under the alternative AMS Subject Classification: 62M10, 62F05, 62G1

Fringe firms: Are they better off in a heterogeneous market?

This paper analyzes a market with three firms. One of them is the dominant firm and the two others are fringe firms. The formulation of demand allows a comparison between price competition with heterogeneous and homogeneous products. Because a parameterization is required to assure that market size is the same in both scenarios, no general conclusions can be drawn. But it can be shown that in large markets with relatively inelastic demand for the fringe firms’ products and a cost advantage of the dominant firm, the fringe firms are better off if they produce a heterogeneous product.dominant firm, competitive fringe, price competition, heterogeneous products

Misspecification Testing in a Class of Conditional Distributional Models

We propose a specification test for a wide range of parametric models for the conditional distribution function of an outcome variable given a vector of covariates. The test is based on the Cramer-von Mises distance between an unrestricted estimate of the joint distribution function of the data, and a restricted estimate that imposes the structure implied by the model. The procedure is straightforward to implement, is consistent against fixed alternatives, has non-trivial power against local deviations of order n^-1/2 from the null hypothesis, and does not require the choice of smoothing parameters. In an empirical application, we use our test to study the validity of various models for the conditional distribution of wages in the US.Cramer-von Mises distance, quantile regression, distributional regression, location-scale model, bootstrap, wage distribution

Rank Logic is Dead, Long Live Rank Logic!

Motivated by the search for a logic for polynomial time, we study rank logic (FPR) which extends fixed-point logic with counting (FPC) by operators that determine the rank of matrices over finite fields. While FPR can express most of the known queries that separate FPC from PTIME, nearly nothing was known about the limitations of its expressive power. In our first main result we show that the extensions of FPC by rank operators over different prime fields are incomparable. This solves an open question posed by Dawar and Holm and also implies that rank logic, in its original definition with a distinct rank operator for every field, fails to capture polynomial time. In particular we show that the variant of rank logic FPR* with an operator that uniformly expresses the matrix rank over finite fields is more expressive than FPR. One important step in our proof is to consider solvability logic FPS which is the analogous extension of FPC by quantifiers which express the solvability problem for linear equation systems over finite fields. Solvability logic can easily be embedded into rank logic, but it is open whether it is a strict fragment. In our second main result we give a partial answer to this question: in the absence of counting, rank operators are strictly more expressive than solvability quantifiers

CUSUM-Type testing for changing parameters in a spatial autoregressive model of stock returns

The paper suggests a CUSUM-type test for time-varying parameters in a recently proposed spatial autoregressive model for stock returns and derives its asymptotic null distribution as well as local power properties. As can be seen from Euro Stoxx 50 returns, a combination of spatial modelling and change point tests allows for superior risk forecasts in portfolio management

A generalized functional delta method

We develop a generalized functional delta method, where the considered random function is not multiplied by a scalar, but by another function. It bases on a generalized Hadamard differentiability between special function spaces. For a certain class of functions, we calculate the Hadamard differential explicitely. We give an example, where the method allows for calculations that are not possible with previous methods