Widespread expression of erythropoietin receptor in brain and its induction by injury

Erythropoietin (EPO) exerts potent neuroprotective, neuroregenerative and procognitive functions. However, unequivocal demonstration of erythropoietin receptor (EPOR) expression in brain cells has remained difficult since previously available anti-EPOR antibodies (EPOR-AB) were unspecific. We report here a new, highly specific, polyclonal rabbit EPOR-AB directed against different epitopes in the cytoplasmic tail of human and murine EPOR and its characterization by mass spectrometric analysis of immuno-precipitated endogenous EPOR, Western blotting, immunostaining and flow cytometry. Among others, we applied genetic strategies including overexpression, Lentivirus-mediated conditional knockout of EpoR and tagged proteins, both on cultured cells and tissue sections, as well as intracortical implantation of EPOR-transduced cells to verify specificity. We show examples of EPOR expression in neurons, oligodendroglia, astrocytes and microglia. Employing this new EPOR-AB with double-labeling strategies, we demonstrate membrane expression of EPOR as well as its localization in intracellular compartments such as the Golgi apparatus. Moreover, we show injury-induced expression of EPOR. In mice, a stereotactically applied stab wound to the motor cortex leads to distinct EpoR expression by reactive GFAP-expressing cells in the lesion vicinity. In a patient suffering from epilepsy, neurons and oligodendrocytes of the hippocampus strongly express EPOR. To conclude, this new analytical tool will allow neuroscientists to pinpoint EPOR expression in cells of the nervous system and to better understand its role in healthy conditions, including brain development, as well as under pathological circumstances, such as upregulation upon distress and injury

Physiological and pathophysiological homeostasis of astroglial channel proteins by Nedd4-2

Nedd4-2 is an E3 ubiquitin ligase, missense mutation of which is related to familial epilepsy, indicating its critical role in regulating neuronal network activity. However, Nedd4-2 substrates involved in neuronal network function have yet to be identified. Using mouse lines lacking Nedd4-1 and Nedd4-2, we identified astrocytic channel proteins inwardly rectifying K+ channel 4.1 (Kir4.1) and Connexin43 as Nedd4-2 substrates. We found that the expression of Kir4.1 and Connexin43 is increased upon conditional deletion of Nedd4-2 in astrocytes, leading to an elevation of astrocytic membrane ion permeability and gap junction activity, with a consequent reduction of γ-oscillatory neuronal network activity. Interestingly, our biochemical data demonstrate that missense mutations found in familial epileptic patients produce gain-of-function of Nedd4-2 gene product. Our data reveal a process of coordinated astrocytic ion channel proteostasis that controls astrocyte function and astrocyte-dependent neuronal network activity, and elucidate a potential mechanism by which aberrant Nedd4-2 function leads to epilepsy

Loss of NEDD4 contributes to RTP801 elevation and neuron toxicity: implications for Parkinson's disease

Parkinson's disease (PD) is a disorder characterized by the degeneration of certain neuronal populations in the central and peripheral nervous system. One of the hallmarks of the disease is the toxic accumulation of proteins within susceptible neurons due to major impairment in the degradation/clearance protein systems. RTP801 is a pro-apoptotic protein that is sufficient and necessary to induce neuronal death in cellular and animal models of PD. RTP801 is also upregulated in sporadic and parkin mutant PD brains. Here, we report the role of NEDD4, an E3 ligase involved in α-synuclein degradation and PD pathogenesis, in the regulation of RTP801 protein levels and toxicity. NEDD4 polyubiquitinates RTP801 in a cell-free system and in cellular cultures, and they interact physically. NEDD4 conjugates K63-ubiquitin chains to RTP801 and targets it for degradation. NEDD4 regulates RTP801 protein levels in both cultured cells and in the brain tissue. NEDD4 levels are diminished in nigral neurons from human PD brains. Interestingly, neurotoxin 6-OHDA decreases dramatically NEDD4 protein expression but elevates RTP801 protein levels. Moreover, NEDD4 protects neuronal PC12 cells from both 6-OHDA and RTP801-induced toxicity. In primary cortical neurons, NEDD4 knockdown toxicity is mediated by RTP801 since the double knockdown of RTP801 and NEDD4 abrogates the loss of phospho Ser473-Akt and the appearance of caspase-cleaved spectrin fragments. Thus, NEDD4 ligase regulates RTP801 and is sensitive to PD-associated oxidative stress. This suggests that NEDD4 loss of function in PD could contribute importantly into neuronal death by elevating RTP801

A High Accuracy Defect-Correction Multigrid Method for the Steady Incompressible Navier-Stokes Equations

The solution of large sets of equations is required when discrete methods are used to solve fluid flow and heat transfer problems. Although the cost of the solution is often a drawback when the number of equations in the set becomes large, higher order numerical methods can be employed in the discretization of differential equations to decrease the number of equations without losing accuracy. For example, using a fourth-order difference scheme instead of a second-order one would reduce the number of equations by approximately half while preserving the same accuracy. In a recent paper, Gupta has developed a fourth-order compact method for the numerical solution of Navier-Stokes equations. In this paper we propose a defect-correction form of the high order approximations using multigrid techniques. We also derive a fourth-order approximation to the boundary conditions to be consistent with the fourth-order discretization of the underlying differential equations. The convergence analysis will be discussed for the parameterized form of a general second-order correction difference scheme which includes a fourth-order scheme as a special case

FPA Tuned Fuzzy Logic Controlled Synchronous Buck Converter for a Wave/SC Energy System

This paper presents a flower pollination algorithm (FPA) tuned fuzzy logic controlled (FLC) synchronous buck converter (SBC) for an integrated wave/ supercapacitor (SC) hybrid energy system. In order to compensate the irregular wave effects on electrical side of the wave energy converter (WEC), a SC unit charged by solar panels is connected in parallel to the WEC system and a SBC is controlled to provide more reliable and stable voltage to the DC load. In order to test the performance of the designed FLC, a classical proportional-integral-derivative (PID) controller is also employed. Both of the controllers are optimized by FPA which is a pretty new optimization algorithm and a well-known optimization algorithm of which particle swarm optimization (PSO) to minimize the integral of time weighted absolute error (ITAE) performance index. Also, the other error-based objective functions are considered. The entire energy system and controllers are developed in Matlab/Simulink and realized experimentally. Real time applications are done through DS1104 Controller Board. The simulation and experimental results show that FPA tuned fuzzy logic controller provides lower value performance indices than conventional PID controller by reducing output voltage sags and swells of the wave/SC energy system

Symbolic polynomial interpolation using Mathematica

This paper discusses teaching polynomial interpolation with the help of Mathematica. The symbolic power of Mathematica is utilized to prove a theorem for the error term in Lagrange interpolating formula. Derivation of the Lagrange formula is provided symbolically and numerically. Runge phenomenon is also illustrated. A simple and efficient symbolic derivation of cubic splines is also provided

2d polynomial interpolation: A symbolic approach with mathematica

This paper extends a previous work done by the same authors on teaching 1d polynomial interpolation using Mathematica [1] to higher dimensions. In this work, it is intended to simplify the the theoretical discussions in presenting multidimensional interpolation in a classroom environment by employing Mathematica's symbolic properties. In addition to symbolic derivations, some numerical tests are provided to show the interesting properties of the higher dimensional interpolation problem. Runge's phenomenon was displayed for 2d polynomial interpolation

Finite Element Thin Plate Splines for Surface Fitting

Surface fitting and smoothing splines techniques are widely used in practice to fit data arising from many different application areas such as meteorology, insurance and stock exchange. A common problem is the approximation of functions of many variables for given values of the function at various points. What makes the problem even more complicated is that the given or observed values may contain noise. We are particularly interested in data mining applications which deal with very large databases. These problems arise in many different areas. One basic aim in data mining is to model functional relationships of high dimensional data sets which introduce the “curse of dimensionality". In order to overcome this curse, additive and interaction splines have been used. Generalised additive models, if interaction terms are limited to order two interactions, lead to the determination of coupled surfaces and curves. Thus, an important part of any data analysis algorithm for these problems is the determination of an approximating surface for extremely large data sets. A variational characterisation of the thin plate smoothing splines was proposed by Duchon. He also proposed to use a radial basis function approach to solve this problem. However, this leads to symmetric indefinite dense linear system of equations. It was seen that this system can be reduced to a positive definite system of equations which can be solved by a conjugate gradient method. Further improvements using ideas from multipole expansions and Lagrange functions [1, 2, 3] lead to methods which are of O(n) or O(n log(n)) in complexity where n is the number of observations. In this work, a new smoothing method is proposed which can be viewed as a discrete thin plate spline. This new approach combines the favourable properties of finite element surface fitting with the ones of thin plate splines. In Section 2, the method is introduced which is based on first order techniques similar to mixed finite element techniques for the biharmonic equation. The numerical solution of the linear system of equations is discussed in Section 3. In Section 4, the technique is illustrated with an example. Conclusions are given in Section 5