A Scalable Feature Selection and Opinion Miner Using Whale Optimization Algorithm

Due to the fast-growing volume of text documents and reviews in recent years, current analyzing techniques are not competent enough to meet the users' needs. Using feature selection techniques not only support to understand data better but also lead to higher speed and also accuracy. In this article, the Whale Optimization algorithm is considered and applied to the search for the optimum subset of features. As known, F-measure is a metric based on precision and recall that is very popular in comparing classifiers. For the evaluation and comparison of the experimental results, PART, random tree, random forest, and RBF network classification algorithms have been applied to the different number of features. Experimental results show that the random forest has the best accuracy on 500 features. Keywords: Feature selection, Whale Optimization algorithm, Selecting optimal, Classification algorith

Mitochondrial and Plasma Membrane Pools of Stomatin-Like Protein 2 Coalesce at the Immunological Synapse during T Cell Activation

Stomatin-like protein 2 (SLP-2) is a member of the stomatin – prohibitin – flotillin – HflC/K (SPFH) superfamily. Recent evidence indicates that SLP-2 is involved in the organization of cardiolipin-enriched microdomains in mitochondrial membranes and the regulation of mitochondrial biogenesis and function. In T cells, this role translates into enhanced T cell activation. Although the major pool of SLP-2 is associated with mitochondria, we show here that there is an additional pool of SLP-2 associated with the plasma membrane of T cells. Both plasma membrane-associated and mitochondria-associated pools of SLP-2 coalesce at the immunological synapse (IS) upon T cell activation. SLP-2 is not required for formation of IS nor for the re-localization of mitochondria to the IS because SLP-2-deficient T cells showed normal re-localization of these organelles in response to T cell activation. Interestingly, upon T cell activation, we found the surface pool of SLP-2 mostly excluded from the central supramolecular activation complex, and enriched in the peripheral area of the IS where signalling TCR microclusters are located. Based on these results, we propose that SLP-2 facilitates the compartmentalization not only of mitochondrial membranes but also of the plasma membrane into functional microdomains. In this latter location, SLP-2 may facilitate the optimal assembly of TCR signalosome components. Our data also suggest that there may be a net exchange of membrane material between mitochondria and plasma membrane, explaining the presence of some mitochondrial proteins in the plasma membrane

Formation of beads-on-a-string structures during break-up of viscoelastic filaments

Break-up of viscoelastic filaments is pervasive in both nature and technology. If a filament is formed by placing a drop of saliva between a thumb and forefinger and is stretched, the filament’s morphology close to break-up corresponds to beads of several sizes interconnected by slender threads. Although there is general agreement that formation of such beads-on-a-string (BOAS) structures occurs only for viscoelastic fluids, the underlying physics remains unclear and controversial. The physics leading to the formation of BOAS structures is probed by numerical simulation. Computations reveal that viscoelasticity alone does not give rise to a small, satellite bead between two much larger main beads but that inertia is required for its formation. Viscoelasticity, however, enhances the growth of the bead and delays pinch-off, which leads to a relatively long-lived beaded structure. We also show for the first time theoretically that yet smaller, sub-satellite beads can also form as seen in experiments.National Science Foundation (U.S.). ERC-SOPS (EEC-0540855)Nanoscale Interdisciplinary Research Thrust on 'Directed Self-assembly of Suspended Polymer Fibers' (NSF-DMS0506941

Shared heritability of attention-deficit/hyperactivity disorder and autism spectrum disorder

Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are both highly heritable neurodevelopmental disorders. Evidence indicates both disorders co-occur with a high frequency, in 20–50% of children with ADHD meeting criteria for ASD and in 30-80% of ASD children meeting criteria for ADHD. This review will provide an overview on all available studies [family based, twin, candidate gene, linkage, and genome wide association (GWA) studies] shedding light on the role of shared genetic underpinnings of ADHD and ASD. It is concluded that family and twin studies do provide support for the hypothesis that ADHD and ASD originate from partly similar familial/genetic factors. Only a few candidate gene studies, linkage studies and GWA studies have specifically addressed this co-occurrence, pinpointing to some promising pleiotropic genes, loci and single nucleotide polymorphisms (SNPs), but the research field is in urgent need for better designed and powered studies to tackle this complex issue. We propose that future studies examining shared familial etiological factors for ADHD and ASD use a family-based design in which the same phenotypic (ADHD and ASD), candidate endophenotypic, and environmental measurements are obtained from all family members. Multivariate multi-level models are probably best suited for the statistical analysis

Comparative residue interaction analysis (CoRIA): a 3D-QSAR approach to explore the binding contributions of active site residues with ligands

A novel approach termed comparative residue-interaction analysis (CoRIA), emphasizing the trends and principles of QSAR in a ligand–receptor environment has been developed to analyze and predict the binding affinity of enzyme inhibitors. To test this new approach, a training set of 36 COX-2 inhibitors belonging to nine families was selected. The putative binding (bioactive) conformations of inhibitors in the COX-2 active site were searched using the program DOCK. The docked configurations were further refined by a combination of Monte Carlo and simulated annealing methods with the Affinity program. The non-bonded interaction energies of the inhibitors with the individual amino acid residues in the active site were then computed. These interaction energies, plus specific terms describing the thermodynamics of ligand–enzyme binding, were correlated to the biological activity with G/PLS. The various QSAR models obtained were validated internally by cross validation and boot strapping, and externally using a test set of 13 molecules. The QSAR models developed on the CoRIA formalism were robust with good r 2, q 2 and r pred2 values. The major highlights of the method are: adaptation of the QSAR formalism in a receptor setting to answer both the type (qualitative) and the extent (quantitative) of ligand–receptor binding, and use of descriptors that account for the complete thermodynamics of the ligand–receptor binding. The CoRIA approach can be used to identify crucial interactions of inhibitors with the enzyme at the residue level, which can be gainfully exploited in optimizing the inhibitory activity of ligands. Furthermore, it can be used with advantage to guide point mutation studies. As regards the COX-2 dataset, the CoRIA approach shows that improving Coulombic interaction with Pro528 and reducing van der Waals interaction with Tyr385 will improve the binding affinity of inhibitors