Ictal Behaviors During Nonepileptic Seizures Differ in Patients with Temporal Lobe Interictal Epileptiform EEG Activity and Patients Without Interictal Epileptiform EEG Abnormalities

Purpose: Ictal behaviors during psychogenic non-epileptic seizures (NES) vary considerably among individuals, and can closely resemble common semiologies of epileptic seizures (ES). We tested the hypothesis that behaviors during NES in patients who have temporal spikes would more closely resemble behaviors during ES in patients with temporal lobe epilepsy than would behaviors during NES in patients who do not have EEG spikes. Methods: We identified 20 patients who had interictal temporal EEG spikes and EEG-video recorded NES (Study Group), 133 patients with temporal EEG spikes and recorded ES, without NES (Epileptic Group), and 24 patients with recorded NES and no epileptiform EEG abnormalities, without ES (Nonepileptic Group). Results: The hypothesis was supported with regard to ictal motor behaviors. Motionless staring or complex automatisms occurred mainly during NES in the Study Group and during ES in the Epileptic Group. In contrast, convulsive movements or flaccid falls were most common during NES in the Nonepileptic Group. Duration of unresponsiveness was longer, and there were fewer postictal states in NES both in the Study and Non-epileptic Groups. Unresponsiveness was briefer and postictal states were more consistent in ES in the Epileptic Group, however. Conclusions: Stereotyped motor activities during NES presumably represent learned behaviors. Processes underlying acquisition of ictal behaviors of NES probably differ in patients with interictal epileptiform EEG abnormalities compared to those without. Prior experiences and temporal lobe dysfunctions that are associated with epilepsy, and psychological characteristics that are unrelated to interictal epileptic dysfunctions, may determine ictal behaviors during NES.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65913/1/j.1528-1157.1998.tb01355.x.pd

HIPPIE: Integrating Protein Interaction Networks with Experiment Based Quality Scores

Protein function is often modulated by protein-protein interactions (PPIs) and therefore defining the partners of a protein helps to understand its activity. PPIs can be detected through different experimental approaches and are collected in several expert curated databases. These databases are used by researchers interested in examining detailed information on particular proteins. In many analyses the reliability of the characterization of the interactions becomes important and it might be necessary to select sets of PPIs of different confidence levels. To this goal, we generated HIPPIE (Human Integrated Protein-Protein Interaction rEference), a human PPI dataset with a normalized scoring scheme that integrates multiple experimental PPI datasets. HIPPIE's scoring scheme has been optimized by human experts and a computer algorithm to reflect the amount and quality of evidence for a given PPI and we show that these scores correlate to the quality of the experimental characterization. The HIPPIE web tool (available at http://cbdm.mdc-berlin.de/tools/hippie) allows researchers to do network analyses focused on likely true PPI sets by generating subnetworks around proteins of interest at a specified confidence level

Community landscapes: an integrative approach to determine overlapping network module hierarchy, identify key nodes and predict network dynamics

Background: Network communities help the functional organization and evolution of complex networks. However, the development of a method, which is both fast and accurate, provides modular overlaps and partitions of a heterogeneous network, has proven to be rather difficult. Methodology/Principal Findings: Here we introduce the novel concept of ModuLand, an integrative method family determining overlapping network modules as hills of an influence function-based, centrality-type community landscape, and including several widely used modularization methods as special cases. As various adaptations of the method family, we developed several algorithms, which provide an efficient analysis of weighted and directed networks, and (1) determine pervasively overlapping modules with high resolution; (2) uncover a detailed hierarchical network structure allowing an efficient, zoom-in analysis of large networks; (3) allow the determination of key network nodes and (4) help to predict network dynamics. Conclusions/Significance: The concept opens a wide range of possibilities to develop new approaches and applications including network routing, classification, comparison and prediction.Comment: 25 pages with 6 figures and a Glossary + Supporting Information containing pseudo-codes of all algorithms used, 14 Figures, 5 Tables (with 18 module definitions, 129 different modularization methods, 13 module comparision methods) and 396 references. All algorithms can be downloaded from this web-site: http://www.linkgroup.hu/modules.ph

IDSS: deformation invariant signatures for molecular shape comparison

<p>Abstract</p> <p>Background</p> <p>Many molecules of interest are flexible and undergo significant shape deformation as part of their function, but most existing methods of molecular shape comparison (MSC) treat them as rigid bodies, which may lead to incorrect measure of the shape similarity of flexible molecules.</p> <p>Results</p> <p>To address the issue we introduce a new shape descriptor, called Inner Distance Shape Signature (IDSS), for describing the 3D shapes of flexible molecules. The inner distance is defined as the length of the shortest path between landmark points within the molecular shape, and it reflects well the molecular structure and deformation without explicit decomposition. Our IDSS is stored as a histogram which is a probability distribution of inner distances between all sample point pairs on the molecular surface. We show that IDSS is insensitive to shape deformation of flexible molecules and more effective at capturing molecular structures than traditional shape descriptors. Our approach reduces the 3D shape comparison problem of flexible molecules to the comparison of IDSS histograms.</p> <p>Conclusion</p> <p>The proposed algorithm is robust and does not require any prior knowledge of the flexible regions. We demonstrate the effectiveness of IDSS within a molecular search engine application for a benchmark containing abundant conformational changes of molecules. Such comparisons in several thousands per second can be carried out. The presented IDSS method can be considered as an alternative and complementary tool for the existing methods for rigid MSC. The binary executable program for Windows platform and database are available from <url>https://engineering.purdue.edu/PRECISE/IDSS</url>.</p

HDNetDB: A Molecular Interaction Database for Network-Oriented Investigations into Huntington’s Disease

Huntington's disease (HD) is a progressive and fatal neurodegenerative disorder caused by an expanded CAG repeat in the huntingtin gene. Although HD is monogenic, its molecular manifestation appears highly complex and involves multiple cellular processes. The recent application of high throughput platforms such as microarrays and mass-spectrometry has indicated multiple pathogenic routes. The massive data generated by these techniques together with the complexity of the pathogenesis, however, pose considerable challenges to researchers. Network-based methods can provide valuable tools to consolidate newly generated data with existing knowledge, and to decipher the interwoven molecular mechanisms underlying HD. To facilitate research on HD in a network-oriented manner, we have developed HDNetDB, a database that integrates molecular interactions with many HD-relevant datasets. It allows users to obtain, visualize and prioritize molecular interaction networks using HD-relevant gene expression, phenotypic and other types of data obtained from human samples or model organisms. We illustrated several HDNetDB functionalities through a case study and identified proteins that constitute potential cross-talk between HD and the unfolded protein response (UPR). HDNetDB is publicly accessible at http://hdnetdb.sysbiolab.eu.CHDI Foundation [A-2666]; Portuguese Fundacao para a Ciencia e a Tecnologia [SFRH/BPD/70718/2010, SFRH/BPD/96890/2013, IF/00881/2013, UID/BIM/04773/2013 - CBMR, UID/Multi/04326/2013 - CCMAR]info:eu-repo/semantics/publishedVersio

Discovering functional linkages and uncharacterized cellular pathways using phylogenetic profile comparisons: a comprehensive assessment

<p>Abstract</p> <p>Background</p> <p>A widely-used approach for discovering functional and physical interactions among proteins involves phylogenetic profile comparisons (PPCs). Here, proteins with similar profiles are inferred to be functionally related under the assumption that proteins involved in the same metabolic pathway or cellular system are likely to have been co-inherited during evolution.</p> <p>Results</p> <p>Our experimentation with <it>E. coli </it>and yeast proteins with 16 different carefully composed reference sets of genomes revealed that the phyletic patterns of proteins in prokaryotes alone could be adequate enough to make reasonably accurate functional linkage predictions. A slight improvement in performance is observed on adding few eukaryotes into the reference set, but a noticeable drop-off in performance is observed with increased number of eukaryotes. Inclusion of most parasitic, pathogenic or vertebrate genomes and multiple strains of the same species into the reference set do not necessarily contribute to an improved sensitivity or accuracy. Interestingly, we also found that evolutionary histories of individual pathways have a significant affect on the performance of the PPC approach with respect to a particular reference set. For example, to accurately predict functional links in carbohydrate or lipid metabolism, a reference set solely composed of prokaryotic (or bacterial) genomes performed among the best compared to one composed of genomes from all three super-kingdoms; this is in contrast to predicting functional links in translation for which a reference set composed of prokaryotic (or bacterial) genomes performed the worst. We also demonstrate that the widely used random null model to quantify the statistical significance of profile similarity is incomplete, which could result in an increased number of false-positives.</p> <p>Conclusion</p> <p>Contrary to previous proposals, it is not merely the number of genomes but a careful selection of informative genomes in the reference set that influences the prediction accuracy of the PPC approach. We note that the predictive power of the PPC approach, especially in eukaryotes, is heavily influenced by the primary endosymbiosis and subsequent bacterial contributions. The over-representation of parasitic unicellular eukaryotes and vertebrates additionally make eukaryotes less useful in the reference sets. Reference sets composed of highly non-redundant set of genomes from all three super-kingdoms fare better with pathways showing considerable vertical inheritance and strong conservation (e.g. translation apparatus), while reference sets solely composed of prokaryotic genomes fare better for more variable pathways like carbohydrate metabolism. Differential performance of the PPC approach on various pathways, and a weak positive correlation between functional and profile similarities suggest that caution should be exercised while interpreting functional linkages inferred from genome-wide large-scale profile comparisons using a single reference set.</p

LCA Loading-Critical Load Cases For Wing Design

Loading Is An Important Phase Of The Structural Analysis And Design Cycle . In This Phase, Various Loads Acting On The Aircraft During Its Operation Are Simulated On The Structural Model, And The Internal Stresses Evaluated . In This Report, The Procedure For Structural Loading Of Lca Using Elfini Is Described . The Mass Cases, Flight Points And Load Envelopes Used For Loading Are Listed . The Critical Load Cases Selected For Using Structural Optimisation Are Presented Along With Justification 'For The Selection

Free Vibration Analysis of ASLV Aeroelastic Buffet Models

1/20 the scale aeroelastic buffet models, of Augmented Satellite Launch Vehicle (ASLV) have been analysed using the finite element method for their dynamic characteristics The analysis has been carried out using the, software package FEAST on the CYBER system at VSSC The of connecting elements: between booster and core vehicle on the natural frequencies and mode shapes and the effects of model support system model dynamic behaviour are presented