959 research outputs found

    Fuzzy Integral with Particle Swarm Optimization for a Motor-Imagery-Based Brain-Computer Interface

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    © 2016 IEEE. A brain-computer interface (BCI) system using electroencephalography signals provides a convenient means of communication between the human brain and a computer. Motor imagery (MI), in which motor actions are mentally rehearsed without engaging in actual physical execution, has been widely used as a major BCI approach. One robust algorithm that can successfully cope with the individual differences in MI-related rhythmic patterns is to create diverse ensemble classifiers using the subband common spatial pattern (SBCSP) method. To aggregate outputs of ensemble members, this study uses fuzzy integral with particle swarm optimization (PSO), which can regulate subject-specific parameters for the assignment of optimal confidence levels for classifiers. The proposed system combining SBCSP, fuzzy integral, and PSO exhibits robust performance for offline single-trial classification of MI and real-time control of a robotic arm using MI. This paper represents the first attempt to utilize fuzzy fusion technique to attack the individual differences problem of MI applications in real-world noisy environments. The results of this study demonstrate the practical feasibility of implementing the proposed method for real-world applications

    Mutagenesis of the fusion peptide-like domain of hepatitis C virus E1 glycoprotein: involvement in cell fusion and virus entry

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    <p>Abstract</p> <p>Background</p> <p>Envelope (E) glycoprotein E2 of the hepatitis C virus (HCV) mediates binding of the virus to target cell receptors. Nevertheless, the precise role of E1 in viral entry remains elusive.</p> <p>Methods</p> <p>To understand the involvement of the fusion peptide-like domain positioned at residues 264 to 290 within envelope glycoprotein E1 in HCV infection, mutants with Ala and Asn substitutions for residues conserved between HCV and E proteins of flaviviruses or the fusion proteins of paramyxoviruses were constructed by site-directed mutagenesis and their effects on membrane fusion and viral infectivity were examined.</p> <p>Results</p> <p>None of these mutations affected the synthesis or cell surface expression of envelope proteins, nor did they alter the formation of a non-covalent E1-E2 heterodimer or E2 binding to the large extracellular loop of CD81. The Cys residues located at positions 272 and 281 were unlikely involved in intra- or intermolecular disulfide bond formation. With the exception of the G267A mutant, which showed increased cell fusion, other mutants displayed reduced or marginally inhibited cell fusion capacities compared to the wild-type (WT) E1E2. The G267A mutant was also an exception in human immunodeficiency virus type 1 (HIV-1)/HCV E1E2 pseudotyping analyses, in that it showed higher one-cycle infectivity; all other mutants exhibited greatly or partially reduced viral entry versus the WT pseudotype. All but the G278A and D279N mutants showed a WT-like profile of E1E2 incorporation into HIV-1 particles. Since C272A, C281A, G282A, and G288A pseudotypes bound to Huh7 cells as effectively as did the WT pseudotype, the reduced infectivity of these pseudotypes was due to their ability to inhibit cell fusion.</p> <p>Conclusion</p> <p>Our results indicate that specific residues, but not the structure, of this fusion peptide-like domain are required for mediating cell fusion and viral entry.</p

    Dynamic model for piezotronic and piezo-phototronic devices under low and high frequency external compressive stresses (Featured)

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    In this work, we aim to establish a theoretical method for modelling the dynamic characteristics of piezotronics and piezo-phototronic devices. By taking the simplest piezotronic device, PN junction as an example, we combine the small signal model and the unified approach to investigate its diffusion capacitance and conductance when it is under both low and high frequency external compressive stresses. This approach is different from the traditional considerations that treat the piezopotential as a static value. Furthermore, we expand the theory into piezo-phototronic devices, e.g., a light emitting diode. The dynamic recombination rate and light emitting intensity are quantitatively calculated under different frequencies of external compressive stresses

    A motor imagery based brain-computer interface system via swarm-optimized fuzzy integral and its application

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    © 2016 IEEE. A brain-computer interface (BCI) system provides a convenient means of communication between the human brain and a computer, which is applied not only to healthy people but also for people that suffer from motor neuron diseases (MNDs). Motor imagery (MI) is one well-known basis for designing Electroencephalography (EEG)-based real-life BCI systems. However, EEG signals are often contaminated with severe noise and various uncertainties, imprecise and incomplete information streams. Therefore, this study proposes spectrum ensemble based on swam-optimized fuzzy integral for integrating decisions from sub-band classifiers that are established by a sub-band common spatial pattern (SBCSP) method. Firstly, the SBCSP effectively extracts features from EEG signals, and thereby the multiple linear discriminant analysis (MLDA) is employed during a MI classification task. Subsequently, particle swarm optimization (PSO) is used to regulate the subject-specific parameters for assigning optimal confidence levels for classifiers used in the fuzzy integral during the fuzzy fusion stage of the proposed system. Moreover, BCI systems usually tend to have complex architectures, be bulky in size, and require time-consuming processing. To overcome this drawback, a wireless and wearable EEG measurement system is investigated in this study. Finally, in our experimental result, the proposed system is found to produce significant improvement in terms of the receiver operating characteristic (ROC) curve. Furthermore, we demonstrate that a robotic arm can be reliably controlled using the proposed BCI system. This paper presents novel insights regarding the possibility of using the proposed MI-based BCI system in real-life applications

    Mitochondrial and nuclear genes suggest that stony corals are monophyletic but most families of stony corals are not (Order Scleractinia, Class Anthozoa, Phylum Cnidaria)

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    Modern hard corals (Class Hexacorallia; Order Scleractinia) are widely studied because of their fundamental role in reef building and their superb fossil record extending back to the Triassic. Nevertheless, interpretations of their evolutionary relationships have been in flux for over a decade. Recent analyses undermine the legitimacy of traditional suborders, families and genera, and suggest that a non-skeletal sister clade (Order Corallimorpharia) might be imbedded within the stony corals. However, these studies either sampled a relatively limited array of taxa or assembled trees from heterogeneous data sets. Here we provide a more comprehensive analysis of Scleractinia (127 species, 75 genera, 17 families) and various outgroups, based on two mitochondrial genes (cytochrome oxidase I, cytochrome b), with analyses of nuclear genes (ßtubulin, ribosomal DNA) of a subset of taxa to test unexpected relationships. Eleven of 16 families were found to be polyphyletic. Strikingly, over one third of all families as conventionally defined contain representatives from the highly divergent "robust" and "complex" clades. However, the recent suggestion that corallimorpharians are true corals that have lost their skeletons was not upheld. Relationships were supported not only by mitochondrial and nuclear genes, but also often by morphological characters which had been ignored or never noted previously. The concordance of molecular characters and more carefully examined morphological characters suggests a future of greater taxonomic stability, as well as the potential to trace the evolutionary history of this ecologically important group using fossils

    Increased entropy of signal transduction in the cancer metastasis phenotype

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    Studies into the statistical properties of biological networks have led to important biological insights, such as the presence of hubs and hierarchical modularity. There is also a growing interest in studying the statistical properties of networks in the context of cancer genomics. However, relatively little is known as to what network features differ between the cancer and normal cell physiologies, or between different cancer cell phenotypes. Based on the observation that frequent genomic alterations underlie a more aggressive cancer phenotype, we asked if such an effect could be detectable as an increase in the randomness of local gene expression patterns. Using a breast cancer gene expression data set and a model network of protein interactions we derive constrained weighted networks defined by a stochastic information flux matrix reflecting expression correlations between interacting proteins. Based on this stochastic matrix we propose and compute an entropy measure that quantifies the degree of randomness in the local pattern of information flux around single genes. By comparing the local entropies in the non-metastatic versus metastatic breast cancer networks, we here show that breast cancers that metastasize are characterised by a small yet significant increase in the degree of randomness of local expression patterns. We validate this result in three additional breast cancer expression data sets and demonstrate that local entropy better characterises the metastatic phenotype than other non-entropy based measures. We show that increases in entropy can be used to identify genes and signalling pathways implicated in breast cancer metastasis. Further exploration of such integrated cancer expression and protein interaction networks will therefore be a fruitful endeavour.Comment: 5 figures, 2 Supplementary Figures and Table

    Analysis of factors influencing the ultrasonic fetal weight estimation

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    Objective: The aim of our study was the evaluation of sonographic fetal weight estimation taking into consideration 9 of the most important factors of influence on the precision of the estimation. Methods: We analyzed 820 singleton pregnancies from 22 to 42 weeks of gestational age. We evaluated 9 different factors that potentially influence the precision of sonographic weight estimation ( time interval between estimation and delivery, experts vs. less experienced investigator, fetal gender, gestational age, fetal weight, maternal BMI, amniotic fluid index, presentation of the fetus, location of the placenta). Finally, we compared the results of the fetal weight estimation of the fetuses with poor scanning conditions to those presenting good scanning conditions. Results: Of the 9 evaluated factors that may influence accuracy of fetal weight estimation, only a short interval between sonographic weight estimation and delivery (0-7 vs. 8-14 days) had a statistically significant impact. Conclusion: Of all known factors of influence, only a time interval of more than 7 days between estimation and delivery had a negative impact on the estimation

    Production and characterization of murine models of classic and intermediate maple syrup urine disease

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    BACKGROUND: Maple Syrup Urine Disease (MSUD) is an inborn error of metabolism caused by a deficiency of branched-chain keto acid dehydrogenase. MSUD has several clinical phenotypes depending on the degree of enzyme deficiency. Current treatments are not satisfactory and require new approaches to combat this disease. A major hurdle in developing new treatments has been the lack of a suitable animal model. METHODS: To create a murine model of classic MSUD, we used gene targeting and embryonic stem cell technologies to create a mouse line that lacked a functional E2 subunit gene of branched-chain keto acid dehydrogenase. To create a murine model of intermediate MSUD, we used transgenic technology to express a human E2 cDNA on the knockout background. Mice of both models were characterized at the molecular, biochemical, and whole animal levels. RESULTS: By disrupting the E2 subunit gene of branched-chain keto acid dehydrogenase, we created a gene knockout mouse model of classic MSUD. The homozygous knockout mice lacked branched-chain keto acid dehydrogenase activity, E2 immunoreactivity, and had a 3-fold increase in circulating branched-chain amino acids. These metabolic derangements resulted in neonatal lethality. Transgenic expression of a human E2 cDNA in the liver of the E2 knockout animals produced a model of intermediate MSUD. Branched-chain keto acid dehydrogenase activity was 5–6% of normal and was sufficient to allow survival, but was insufficient to normalize circulating branched-chain amino acids levels, which were intermediate between wildtype and the classic MSUD mouse model. CONCLUSION: These mice represent important animal models that closely approximate the phenotype of humans with the classic and intermediate forms of MSUD. These animals provide useful models to further characterize the pathogenesis of MSUD, as well as models to test novel therapeutic strategies, such as gene and cellular therapies, to treat this devastating metabolic disease

    Identification of Giardia lamblia DHHC Proteins and the Role of Protein S-palmitoylation in the Encystation Process

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    Protein S-palmitoylation, a hydrophobic post-translational modification, is performed by protein acyltransferases that have a common DHHC Cys-rich domain (DHHC proteins), and provides a regulatory switch for protein membrane association. In this work, we analyzed the presence of DHHC proteins in the protozoa parasite Giardia lamblia and the function of the reversible S-palmitoylation of proteins during parasite differentiation into cyst. Two specific events were observed: encysting cells displayed a larger amount of palmitoylated proteins, and parasites treated with palmitoylation inhibitors produced a reduced number of mature cysts. With bioinformatics tools, we found nine DHHC proteins, potential protein acyltransferases, in the Giardia proteome. These proteins displayed a conserved structure when compared to different organisms and are distributed in different monophyletic clades. Although all Giardia DHHC proteins were found to be present in trophozoites and encysting cells, these proteins showed a different intracellular localization in trophozoites and seemed to be differently involved in the encystation process when they were overexpressed. dhhc transgenic parasites showed a different pattern of cyst wall protein expression and yielded different amounts of mature cysts when they were induced to encyst. Our findings disclosed some important issues regarding the role of DHHC proteins and palmitoylation during Giardia encystation.Fil: Merino, Maria Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra. Universidad Nacional de Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra; ArgentinaFil: Zamponi, Nahuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra. Universidad Nacional de Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra; ArgentinaFil: Vranych, Cecilia Verónica. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra. Universidad Nacional de Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra; ArgentinaFil: Touz, Maria Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra. Universidad Nacional de Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra; ArgentinaFil: Ropolo, Andrea Silvana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra. Universidad Nacional de Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra; Argentin
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