Combined therapy with GABA and proinsulin/alum acts synergistically to restore long-term normoglycemia by modulating T-cell autoimmunity and promoting β-cell replication in newly diabetic NOD mice.

Antigen-based therapies (ABTs) fail to restore normoglycemia in newly diabetic NOD mice, perhaps because too few β-cells remain by the time that ABT-induced regulatory responses arise and spread. We hypothesized that combining a fast-acting anti-inflammatory agent with an ABT could limit pathogenic responses while ABT-induced regulatory responses arose and spread. γ-Aminobutyric acid (GABA) administration can inhibit inflammation, enhance regulatory T-cell (Treg) responses, and promote β-cell replication in mice. We examined the effect of combining a prototypic ABT, proinsulin/alum, with GABA treatment in newly diabetic NOD mice. Proinsulin/alum monotherapy failed to correct hyperglycemia, while GABA monotherapy restored normoglycemia for a short period. Combined treatment restored normoglycemia in the long term with apparent permanent remission in some mice. Proinsulin/alum monotherapy induced interleukin (IL)-4- and IL-10-secreting T-cell responses that spread to other β-cell autoantigens. GABA monotherapy induced moderate IL-10 (but not IL-4) responses to β-cell autoantigens. Combined treatment synergistically reduced spontaneous type 1 T-helper cell responses to autoantigens, ABT-induced IL-4 and humoral responses, and insulitis, but enhanced IL-10 and Treg responses and promoted β-cell replication in the islets. Thus, combining ABT with GABA can inhibit pathogenic T-cell responses, induce Treg responses, promote β-cell replication, and effectively restore normoglycemia in newly diabetic NOD mice. Since these treatments appear safe for humans, they hold promise for type 1 diabetes intervention

Insider trading, gender diversity within the board room, CEO pay gap, and stock price crash risk

This paper investigates the impact of insider trading and managerial attributes on future stock price crashes. We conduct a series of regressions addressing the managerial attributes determinants of future stock price crashes including gender diversity, CEO age, and CEO power (measured by CEO pay disparity, CEO tenure and CEO duality). Our empirical results reveal a positive association between insider purchases and price crash risk. This implies that other than compensation and career concerns, insiders hoard bad news to fulfil their trading incentives. Our positive coefficients of insider sales also suggest that insider sellers can assess inside information promptly and anticipate shortly before the crashes. We further document that the presence of female directors on boards can mitigate stock price crash risk. However, firms with powerful or younger Chief Executive Officers are more likely to experience crashes. Overall, we highlight the importance of corporate managerial attributes in dealing with information asymmetry problems

A hierarchical finite element Monte Carlo method for stochastic two-scale elliptic equations

We consider two-scale elliptic equations whose coefficients are random. In particular, we study two cases: in the first case, the coefficients are obtained from an ergodic dynamical system acting on a probability space, and in the second the case, the coefficients are periodic in the microscale but are random. We suppose that the coefficients also depend on the macroscopic slow variables. While the effective coefficient of the ergodic homogenization problem is deterministic, to approximate it, it is necessary to solve cell equations in a large but finite size “truncated" cube and compute an approximated effective coefficient from the solution of this equation. This approximated effective coefficient is, however, realization dependent; and the deterministic effective coefficient of the homogenization problem can be approximated by taking its expectation. In the periodic random setting, the effective coefficient for each realization are obtained from the solutions of cell equations which are posed in the unit cube, but to compute its average by the Monte Carlo method, we need to consider many uncorrelated realizations to accurately approximate the average. Straightforward employment of finite element approximation and the Monte Carlo method to compute this expectation with the same level of finite element resolution and the same number of Monte Carlo samples at every macroscopic point is prohibitively expensive. We develop a hierarchical finite element Monte Carlo algorithm to approximate the effective coefficients at a dense hierarchical network of macroscopic points. The method requires an optimal level of complexity that is essentially equal to that for computing the effective coefficient at one macroscopic point, and achieves essentially the same accuracy. The levels of accuracy for solving cell problems and for the Monte Carlo sampling are chosen according to the level in the hierarchy that the macroscopic points belong to. Solutions and the effective coefficients at the points where the cell problems are solved with higher accuracy and the effective coefficients are approximated with a larger number of Monte Carlo samples are employed as correctors for the effective coefficient at those points at which the cell problems are solved with lower accuracy and fewer Monte Carlo samples. The method combines the hierarchical finite element method for solving cell problems at a dense network of macroscopic points with the optimal complexity developed in D. L. Brown, Y. Efendiev and V. H. Hoang, Multiscale Model. Simul. 11 (2013), with a hierarchical Monte Carlo sampling algorithm that uses different number of samples at different macroscopic points depending on the level in the hierarchy that the macroscopic points belong to. Proof of concept numerical examples confirm the theoretical results

Simple Combined Model for Nonlinear Excitations in DNA

We propose a new simple model for DNA denaturation bases on the pendulum model of Englander\cite{A1} and the microscopic model of Peyrard {\it et al.},\cite{A3} so called "combined model". The main parameters of our model are: the coupling constant $k$ along each strand, the mean stretching $y^\ast$ of the hydrogen bonds, the ratio of the damping constant and driven force $\gamma/F$. We show that both the length $L$ of unpaired bases and the velocity $v$ of kinks depend on not only the coupling constant $k$ but also the temperature $T$. Our results are in good agreement with previous works.Comment: 6 pages, 10 figures, submitted to Phys. Rev.

Local Mass Transfer in Turbulent Flow by Electrochemical Methods

Mass transfer to the surface of rotating electrodes during turbulent flow was studied by electrochemical methods under steady and non-steady state diffusion conditions. The flow was due to a large rotating disk made from insulating material, flush with the surface of which was mounted a ring shaped electrode of platinum or nickel. A local study of the radial component of the convective diffusion in turbulent flow was carried out with very thin ring electrodes (width ΔR ~ 0,05 mm). The diffusion layer thickness was varied relatively to the diffusion sublayer thickness by changing the ring width or the rotation speed so as to determine the eddy diffusivity in the viscous sublayer. The local viscous friction was measured at the wall by a steady state method. As an application, the drag reduction phenomenon was studied in the presence of high polymer additives. Using a non-steady state method which yields the electrochemical impedance, we examined the possibility of adsorption of polymers at the wall- fluid interface

Monte Carlo studies of the ordering of the one-dimensional Heisenberg spin glass with long-range power-law interactions

The nature of the ordering of the one-dimensional Heisenberg spin-glass model with a long-range power-law interaction is studied by extensive Monte Carlo simulations, with particular attention to the issue of the spin-chirality decoupling/coupling. Large system sizes up to $L=4096$ are studied. With varying the exponent $\sigma$ describing the power-law interaction, we observe three distinct types of ordering regimes. For smaller $\sigma$, the spin and the chirality order at a common finite temperature with a common correlation-length exponent, exhibiting the standard spin-chirality coupling behavior. For intermediate $\sigma$, the chirality orders at a temperature higher than the spin, exhibiting the spin-chirality decoupling behavior. For larger $\sigma$, both the spin and the chirality order at zero temperature. We construct a phase diagram in the $\sigma$ versus the temperature plane, and discuss implications of the results. Critical properties associated with both the chiral-glass and the spin-glass transitions are also determined.Comment: 28 pages, 26 figures, to appear in J. Phys. Soc. Jp

Group elements whose character values are roots of unity

We classify all finite groups $G$ which possesses an element $x\in G$ such that every irreducible character of $G$ takes a root of unity value at $x$

Localization in Sensor Networks with Fading Channels based on Nonmetric Distrance Models

Wireless Sensor Network (WSN) applications nowadays are an emerging avenue in which sensor localization is an essential and crucial issue. Many algorithms have been proposed to estimate the coordinate of sensors in WSNs, however, the attained accuracy in real-world applications is still far from the theoretical lower bound, Crame-Rao Lower Bound (CRLB), due to the effects of fading channels. In this paper, we propose a very simple and light weight statistical model for rang-based localization schemes, especially for the most typical localization algorithms based on received signal strength (RSS) and time-of-arrival (TOA). Our proposed method infers only the order or the nomination of given distances from measurement data to avoid significant bias caused by fading channels or shadowing. In such way, it radically reduces the effects of the degradation and performs better than existing algorithms do. With simulation of fading channels and irregular noises for both the RSS-based measurement and the TOA-based measurement, we analyze and testify both the benefits and the drawbacks of the proposed models and the localization scheme