Event-related Potentials reveal differential Brain Regions implicated in Discounting in Two Tasks

The way people make decisions about future benefits – termed discounting - has important implications for both financial planning and health behaviour. Several theories assume that, when delaying gratification, the lower weight given to future benefits (the discount rate) declines exponentially. However there is considerable evidence that it declines hyperbolically with the rate of discount being proportionate to the delay distance. There is relatively little evidence as to whether neural areas mediating time- dependent discounting processes differ according to the nature of the task. The present study investigates the potential neurological mechanisms underpinning domain-specific discounting processes. We present high-density event-related potentials (ERPs) data from a task in which participants were asked to make decisions about financial rewards or their health over short and long time-horizons. Participants (n=17) made a button-press response to their preference for an immediate or delayed gain (in the case of finance) or loss (in the case of health), with the discrepancy in the size of benefits/losses varying between alternatives. Waveform components elicited during the task were similar for both domains and included posterior N1, frontal P2 and posterior P3 components. We provide source dipole evidence that differential brain activation does occur across domains with results suggesting the possible involvement of the right cingulate gyrus and left claustrum for the health domain and the left medial and right superior frontal gyri for the finance domain. However, little evidence for differential activation across time horizons is found.Decision Making, Domain-Specific Discounting, Event-Related Potentials

Mode couplings in superstructure fiber Bragg gratings

Author name used in this publication: A-Ping ZhangAuthor name used in this publication: Xiao-Ming Tao2001-2002 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Lead halide perovskite nanowires stabilized by block copolymers for Langmuir-Blodgett assembly

The rapid development of solar cells based on lead halide perovskites (LHPs) has prompted very active research activities in other closely-related fields. Colloidal nanostructures of such materials display superior optoelectronic properties. Especially, one-dimensional (1D) LHPs nanowires show anisotropic optical properties when they are highly oriented. However, the ionic nature makes them very sensitive to external environment, limiting their large scale practical applications. Here, we introduce an amphiphilic block copolymer, polystyrene-block-poly(4-vinylpyridine) (PS-P4VP), to chemically modify the surface of colloidal CsPbBr3 nanowires. The resulting core-shell nanowires show enhanced photoluminescent emission and good colloidal stability against water. Taking advantage of the stability enhancement, we further applied a modified Langmuir-Blodgett technique to assemble monolayers of highly aligned nanowires, and studied their anisotropic optical properties. [Figure not available: see fulltext.]

Signal peptide peptidases and gamma-secretase: Cousins of the same protease family?

Signal peptide peptidase (SPIP) is an unusual aspartyl protease, which mediates clearance of signal peptides by proteolysis within the endoplasmic reticulum (ER). Like presenilins, which provide the proteolytically active subunit of the,gamma-secretase complex, SPP contains a conserved GxGD motif in its C-terminal domain which is critical for its activity. While SPIP is known to be an aspartyl protease of the GxGD type, several presenilin homologues/SPP-like proteins (PSHs/ SPPL) of unknown function have been identified by database searches. In contrast to SPP and SPPL3, which are both restricted to the endoplasmic reticulum, SPPL2b is targeted through the secretory pathway to endosomes/lysosomes. As suggested by the differential subcellular localization of SPPL2b and SPPL3 distinct phenotypes were found upon antisense gripNA-mediated knockdown in zebrafish. spp and sppl3 knockdowns in zebrafish result in cell death within the central nervous system, whereas reduction of sppl2b expression causes erythrocyte accumulation in an enlarged caudal vein. Moreover, expression of D/A mutants of the putative C-terminal active sites of spp, sppl2, and spp13 produced phenocopies of the respective knockdown phenotypes. These data suggest that all investigated PSHs/SPPLs are members of the novel family of GxGD aspartyl proteases. More recently, it was shown that SPPL2b utilizes multiple intramembrane cleavages to liberate the TNF(x intracellular domain into the cytosol and to release the C-terminal counterpart into the lumen. These findings suggest common principles of intramembrane proteolysis by GxGD type aspartyl proteases. In this article,we will review the similarities of SPPs and gamma-secretase based on recent findings by us and others

A Study of Archiving Strategies in Multi-Objective PSO for Molecular Docking

Molecular docking is a complex optimization problem aimed at predicting the position of a ligand molecule in the active site of a receptor with the lowest binding energy. This problem can be formulated as a bi-objective optimization problem by minimizing the binding energy and the Root Mean Square Deviation (RMSD) difference in the coordinates of ligands. In this context, the SMPSO multi-objective swarm-intelligence algorithm has shown a remarkable performance. SMPSO is characterized by having an external archive used to store the non-dominated solutions and also as the basis of the leader selection strategy. In this paper, we analyze several SMPSO variants based on different archiving strategies in the scope of a benchmark of molecular docking instances. Our study reveals that the SMPSOhv, which uses an hypervolume contribution based archive, shows the overall best performance.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Machine-learning of atomic-scale properties based on physical principles

We briefly summarize the kernel regression approach, as used recently in materials modelling, to fitting functions, particularly potential energy surfaces, and highlight how the linear algebra framework can be used to both predict and train from linear functionals of the potential energy, such as the total energy and atomic forces. We then give a detailed account of the Smooth Overlap of Atomic Positions (SOAP) representation and kernel, showing how it arises from an abstract representation of smooth atomic densities, and how it is related to several popular density-based representations of atomic structure. We also discuss recent generalisations that allow fine control of correlations between different atomic species, prediction and fitting of tensorial properties, and also how to construct structural kernels---applicable to comparing entire molecules or periodic systems---that go beyond an additive combination of local environments

Modelling the effects of disopyramide on short QT syndrome variant 1 in the human ventricles

The short QT syndrome (SQTS) is a recently identified genetic disorder associated with ventricular and/or atrial arrhythmias and increased risk of sudden cardiac death. The SQTS variant 1 (SQT1) N588K mutation to the hERG gene causes a gain-of-function to IKr which shortens the ventricular effective refractory period (ERP), as well as reducing the potency of several drugs which block the hERG channel. This study used computational modelling to assess the effects of disopyramide (DISO), a class 1a anti-arrhythmic agent, on human ventricular electro-physiology in SQT1. The O'Hara Rudy dynamic (ORd) model of the human ventricle action potential (AP) was modified to incorporate a Markov chain model of IKr/hERG including formulations for wild type (WT) and SQT1 N588K mutant hERG channels. The blocking effects of DISO on IKr, INa, ICaL, and Ito were modelled using IC50 and Hill coefficient values from the literature. The ability of DISO to prolong the QT interval was evaluated using a 1D model of human ventricular cells with transmural heterogeneities and the corresponding pseudo-ECG. At a clinically-relevant concentration of 10 μM DISO, the action potential duration (APD) at the single cell level was increased significantly through inhibition of mutant SQT1-hERG channels. The corrected QT interval in tissue was prolonged. This study provides further evidence that DISO is a suitable treatment for hERG-mediated SQTS

Modelling the effects of disopyramide on short QT syndrome variant 1 in the human ventricles

The short QT syndrome (SQTS) is a recently identified genetic disorder associated with ventricular and/or atrial arrhythmias and increased risk of sudden cardiac death. The SQTS variant 1 (SQT1) N588K mutation to the hERG gene causes a gain-of-function to IKr which shortens the ventricular effective refractory period (ERP), as well as reducing the potency of several drugs which block the hERG channel. This study used computational modelling to assess the effects of disopyramide (DISO), a class 1a anti-arrhythmic agent, on human ventricular electro-physiology in SQT1. The O'Hara Rudy dynamic (ORd) model of the human ventricle action potential (AP) was modified to incorporate a Markov chain model of IKr/hERG including formulations for wild type (WT) and SQT1 N588K mutant hERG channels. The blocking effects of DISO on IKr, INa, ICaL, and Ito were modelled using IC50 and Hill coefficient values from the literature. The ability of DISO to prolong the QT interval was evaluated using a 1D model of human ventricular cells with transmural heterogeneities and the corresponding pseudo-ECG. At a clinically-relevant concentration of 10 μM DISO, the action potential duration (APD) at the single cell level was increased significantly through inhibition of mutant SQT1-hERG channels. The corrected QT interval in tissue was prolonged. This study provides further evidence that DISO is a suitable treatment for hERG-mediated SQTS

Tag-Aware Recommender Systems: A State-of-the-art Survey

In the past decade, Social Tagging Systems have attracted increasing attention from both physical and computer science communities. Besides the underlying structure and dynamics of tagging systems, many efforts have been addressed to unify tagging information to reveal user behaviors and preferences, extract the latent semantic relations among items, make recommendations, and so on. Specifically, this article summarizes recent progress about tag-aware recommender systems, emphasizing on the contributions from three mainstream perspectives and approaches: network-based methods, tensor-based methods, and the topic-based methods. Finally, we outline some other tag-related works and future challenges of tag-aware recommendation algorithms.Comment: 19 pages, 3 figure