Neuronal oxidative injury in the development of the epileptic disease : a potential target for novel therapeutic approaches

Epileptic diseases affect about 50 million people in the world and approximately 30% of patients diagnosed with epilepsy are unresponsive to current medications. For these reasons, primary prevention of epilepsy represents one of the priorities in epilepsy research. Intracellular oxido-reductive (redox) state is well known to play a crucial role, contributing to the maintenance of the proper function of biomolecules. Therefore, oxidative stress results in functional cellular disruption and cellular damage and may cause subsequent cell death via oxidation of proteins, lipids, and nucleotides. Recently, the role of oxidative stress in the early stage and in the progression of epileptic disorders has begun to be recognized. The early molecular response to oxidative stress represents a short-term reversible phenomenon that precedes higher and irreversible forms of oxidation. This article reviews the current understanding of the epileptogenic phenomena related to seizure-induced oxidative injury as potential “critical period” therapeutic targets for the prevention of chronic epileptic disorder.peer-reviewe

A data driven equivariant approach to constrained Gaussian mixture modeling

Maximum likelihood estimation of Gaussian mixture models with different class-specific covariance matrices is known to be problematic. This is due to the unboundedness of the likelihood, together with the presence of spurious maximizers. Existing methods to bypass this obstacle are based on the fact that unboundedness is avoided if the eigenvalues of the covariance matrices are bounded away from zero. This can be done imposing some constraints on the covariance matrices, i.e. by incorporating a priori information on the covariance structure of the mixture components. The present work introduces a constrained equivariant approach, where the class conditional covariance matrices are shrunk towards a pre-specified matrix Psi. Data-driven choices of the matrix Psi, when a priori information is not available, and the optimal amount of shrinkage are investigated. The effectiveness of the proposal is evaluated on the basis of a simulation study and an empirical example

Fermion Tunneling from Dynamical Horizons

The instability against emission of fermionic particles by the trapping horizon of an evolving black hole is analyzed using the Hamilton-Jacobi tunneling method. This method automatically selects one special expression for the surface gravity of a changing horizon. The results also apply to point masses embedded in an expanding universe. As a bonus of the tunneling method, we gain the insight that the surface gravity still defines a temperature parameter as long as the evolution is sufficiently slow that the black hole pass through a sequence of quasi-equilibrium states, and that black holes should be semi-classically unstable even in a hypothetical world without bosonic fields.Comment: 8 pages, standard Latex document, few references adde

Stochastic Hydrodynamic Synchronization in Rotating Energy Landscapes

Hydrodynamic synchronization provides a general mechanism for the spontaneous emergence of coherent beating states in independently driven mesoscopic oscillators. A complete physical picture of those phenomena is of definite importance to the understanding of biological cooperative motions of cilia and flagella. Moreover, it can potentially suggest novel routes to exploit synchronization in technological applications of soft matter. We demonstrate that driving colloidal particles in rotating energy landscapes results in a strong tendency towards synchronization, favouring states where all beads rotate in phase. The resulting dynamics can be described in terms of activated jumps with transition rates that are strongly affected by hydrodynamics leading to an increased probability and lifetime of the synchronous states. Using holographic optical tweezers we quantitatively verify our predictions in a variety of spatial configurations of rotors.Comment: Copyright (2013) by the American Physical Societ

CONCISE: Compressed 'n' Composable Integer Set

Bit arrays, or bitmaps, are used to significantly speed up set operations in several areas, such as data warehousing, information retrieval, and data mining, to cite a few. However, bitmaps usually use a large storage space, thus requiring compression. Nevertheless, there is a space-time tradeoff among compression schemes. The Word Aligned Hybrid (WAH) bitmap compression trades some space to allow for bitwise operations without first decompressing bitmaps. WAH has been recognized as the most efficient scheme in terms of computation time. In this paper we present CONCISE (Compressed 'n' Composable Integer Set), a new scheme that enjoys significatively better performances than those of WAH. In particular, when compared to WAH, our algorithm is able to reduce the required memory up to 50%, by having similar or better performance in terms of computation time. Further, we show that CONCISE can be efficiently used to manipulate bitmaps representing sets of integral numbers in lieu of well-known data structures such as arrays, lists, hashtables, and self-balancing binary search trees. Extensive experiments over synthetic data show the effectiveness of our approach.Comment: Preprint submitted to Information Processing Letters, 7 page