23,879 research outputs found

    Role of (p)ppGpp in Viability and Biofilm Formation of Actinobacillus pleuropneumoniae S8.

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    Actinobacillus pleuropneumoniae is a Gram-negative bacterium and the cause of porcine pleuropneumonia. When the bacterium encounters nutritional starvation, the relA-dependent (p)ppGpp-mediated stringent response is activated. The modified nucleotides guanosine 5'-diphosphate 3'-diphosphate (ppGpp) and guanosine 5'-triphosphate 3'-diphosphate (pppGpp) are known to be signaling molecules in other prokaryotes. Here, to investigate the role of (p)ppGpp in A. pleuropneumoniae, we created a mutant A. pleuropneumoniae strain, S8ΔrelA, which lacks the (p)ppGpp-synthesizing enzyme RelA, and investigated its phenotype in vitro. S8ΔrelA did not survive after stationary phase (starvation condition) and grew exclusively as non-extended cells. Compared to the wild-type (WT) strain, the S8ΔrelA mutant had an increased ability to form a biofilm. Transcriptional profiles of early stationary phase cultures revealed that a total of 405 bacterial genes were differentially expressed (including 380 up-regulated and 25 down-regulated genes) in S8ΔrelA as compared with the WT strain. Most of the up-regulated genes are involved in ribosomal structure and biogenesis, amino acid transport and metabolism, translation cell wall/membrane/envelope biogenesis. The data indicate that (p)ppGpp coordinates the growth, viability, morphology, biofilm formation and metabolic ability of A. pleuropneumoniae in starvation conditions. Furthermore, S8ΔrelA could not use certain sugars nor produce urease which has been associated with the virulence of A. pleuropneumoniae, suggesting that (p)ppGpp may directly or indirectly affect the pathogenesis of A. pleuropneumoniae during the infection process. In summary, (p)ppGpp signaling represents an essential component of the regulatory network governing stress adaptation and virulence in A. pleuropneumoniae

    Enhanced Second-Harmonic Generation in Monolayer MoS2 Driven by a BIC-based Nonlinear Metasurface

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    Dielectric metasurfaces have opened novel routes for nonlinear optics in recent years. In this work, we integrate a nonlinear metasurface with monolayer molybdenum disulfide (MoS2) to enhance second-harmonic generation (SHG) from atomically thin MoS2. By utilizing bound states in the continuum, we achieve about 600× of SHG enhancement from monolayer MoS2 on a resonant metasurface relative to suspended monolayer MoS2. Moreover, an eigenmode expansion approach is exploited to express second-harmonic power and the corresponding analytical results agree well with the rigorous calculations

    Semiparametric regression analysis via Infer.NET

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    © 2018, American Statistical Association. All rights reserved. We provide several examples of Bayesian semiparametric regression analysis via the Infer.NET package for approximate deterministic inference in Bayesian models. The examples are chosen to encompass a wide range of semiparametric regression situations. Infer.NET is shown to produce accurate inference in comparison with Markov chain Monte Carlo via the BUGS package, but to be considerably faster. Potentially, this contribution represents the start of a new era for semiparametric regression, where large and complex analyses are performed via fast Bayesian inference methodology and software, mainly being developed within Machine Learning

    Photochemical internalisation of a macromolecular protein toxin using a cell penetrating peptide-photosensitiser conjugate.

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    Photochemical internalisation (PCI) is a site-specific technique for improving cellular delivery of macromolecular drugs. In this study, a cell penetrating peptide, containing the core HIV-1 Tat 48-57 sequence, conjugated with a porphyrin photosensitiser has been shown to be effective for PCI. Herein we report an investigation of the photophysical and photobiological properties of a water soluble bioconjugate of the cationic Tat peptide with a hydrophobic tetraphenylporphyrin derivative. The cellular uptake and localisation of the amphiphilic bioconjugate was examined in the HN5 human head and neck squamous cell carcinoma cell line. Efficient cellular uptake and localisation in endo/lysosomal vesicles was found using fluorescence detection, and light-induced, rupture of the vesicles resulting in a more diffuse intracellular fluorescence distribution was observed. Conjugation of the Tat sequence with a hydrophobic porphyrin thus enables cellular delivery of an amphiphilic photosensitiser which can then localise in endo/lysosomal membranes, as required for effective PCI treatment. PCI efficacy was tested in combination with a protein toxin, saporin, and a significant reduction in cell viability was measured versus saporin or photosensitiser treatment alone. This study demonstrates that the cell penetrating peptide-photosensitiser bioconjugation strategy is a promising and versatile approach for enhancing the therapeutic potential of bioactive agents through photochemical internalisation

    A Wireless Multifunctional SSVEP-Based Brain Computer Interface Assistive System

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    IEEE Several kinds of brain-computer interface (BCI) systems have been proposed to compensate for the lack of medical technology for assisting patients who lose the ability to use motor functions to communicate with the outside world. However, most of the proposed systems are limited by their non-portability, impracticality and inconvenience because of the adoption of wired or invasive electroencephalography (EEG) acquisition devices. Another common limitation is the shortage of functions provided because of the difficulty of integrating multiple functions into one BCI system. In this study, we propose a wireless, non-invasive and multifunctional assistive system which integrates steady state visually evoked potential (SSVEP)-based BCI and a robotic arm to assist patients to feed themselves. Patients are able to control the robotic arm via the BCI to serve themselves food. Three other functions: video entertainment, video calling, and active interaction are also integrated. This is achieved by designing a functional menu and integrating multiple subsystems. A refinement decision-making mechanism is incorporated to ensure the accuracy and applicability of the system. Fifteen participants were recruited to validate the usability and performance of the system. The averaged accuracy and information transfer rate (ITR) achieved is 90.91% and 24.94 bit per min respectively. The feedback from the participants demonstrates that this assistive system is able to significantly improve the quality of daily life

    A wireless steady state visually evoked potential-based BCI eating assistive system

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    © 2017 IEEE. Brain-Computer interface (BCI) which aims at enabling users to perform tasks through their brain waves has been a feasible and worth developing solution for growing demand of healthcare. Current proposed BCI systems are often with lower applicability and do not provide much help for reducing burdens of users because of the time-consuming preparation required by adopted wet sensors and the shortage of provided interactive functions. Here, by integrating a state visually evoked potential (SSVEP)-based BCI system and a robotic eating assistive system, we propose a non-invasive wireless steady state visually evoked potential (SSVEP)-based BCI eating assistive system that enables users with physical disabilities to have meals independently. The analysis compared different methods of classification and indicated the best method. The applicability of the integrated eating assistive system was tested by an Amyotrophic Lateral Sclerosis (ALS) patient, and a questionnaire reply and some suggestion are provided. Fifteen healthy subjects engaged the experiment, and an average accuracy of 91.35%, and information transfer rate (ITR) of 20.69 bit per min are achieved. For online performance evaluation, the ALS patient gave basic affirmation and provided suggestions for further improvement. In summary, we proposed a usable SSVEP-based BCI system enabling users to have meals independently. With additional adjustment of movement design of the robotic arm and classification algorithm, the system may offer users with physical disabilities a new way to take care of themselves

    ArrayWiki: an enabling technology for sharing public microarray data repositories and meta-analyses

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    © 2008 Stokes et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.DOI: 10.1186/1471-2105-9-S6-S18Background. A survey of microarray databases reveals that most of the repository contents and data models are heterogeneous (i.e., data obtained from different chip manufacturers), and that the repositories provide only basic biological keywords linking to PubMed. As a result, it is difficult to find datasets using research context or analysis parameters information beyond a few keywords. For example, to reduce the "curse-of-dimension" problem in microarray analysis, the number of samples is often increased by merging array data from different datasets. Knowing chip data parameters such as pre-processing steps (e.g., normalization, artefact removal, etc), and knowing any previous biological validation of the dataset is essential due to the heterogeneity of the data. However, most of the microarray repositories do not have meta-data information in the first place, and do not have a a mechanism to add or insert this information. Thus, there is a critical need to create "intelligent" microarray repositories that (1) enable update of meta-data with the raw array data, and (2) provide standardized archiving protocols to minimize bias from the raw data sources. Results. To address the problems discussed, we have developed a community maintained system called ArrayWiki that unites disparate meta-data of microarray meta-experiments from multiple primary sources with four key features. First, ArrayWiki provides a user-friendly knowledge management interface in addition to a programmable interface using standards developed by Wikipedia. Second, ArrayWiki includes automated quality control processes (caCORRECT) and novel visualization methods (BioPNG, Gel Plots), which provide extra information about data quality unavailable in other microarray repositories. Third, it provides a user-curation capability through the familiar Wiki interface. Fourth, ArrayWiki provides users with simple text-based searches across all experiment meta-data, and exposes data to search engine crawlers (Semantic Agents) such as Google to further enhance data discovery. Conclusions. Microarray data and meta information in ArrayWiki are distributed and visualized using a novel and compact data storage format, BioPNG. Also, they are open to the research community for curation, modification, and contribution. By making a small investment of time to learn the syntax and structure common to all sites running MediaWiki software, domain scientists and practioners can all contribute to make better use of microarray technologies in research and medical practices. ArrayWiki is available at http://www.bio-miblab.org/arraywiki

    Influence of EEG tonic changes on Motor Imagery performance

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    © 2017 IEEE. In Motor Imagery literature, performance predictors are commonly divided in four categories: personal, psychological, anatomical and neurophysiological. However these predictors are limited to inter-subjects changes. To overcome this limitation and evaluate intra-subjects performance, we tried to combine two groups of these measures: psychological and neurophysiological. As neurophysiological variables tonic changes in resting EEG theta and alpha sub-bands were considered. As psychological parameter we analyzed internalized attention and its correlates in lower alpha. We found that when internalized attention doesn't decrease, Motor Imagery performance outcome can be correctly predicted by resting EEG tonic variations

    Browse-to-search

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    This demonstration presents a novel interactive online shopping application based on visual search technologies. When users want to buy something on a shopping site, they usually have the requirement of looking for related information from other web sites. Therefore users need to switch between the web page being browsed and other websites that provide search results. The proposed application enables users to naturally search products of interest when they browse a web page, and make their even causal purchase intent easily satisfied. The interactive shopping experience is characterized by: 1) in session - it allows users to specify the purchase intent in the browsing session, instead of leaving the current page and navigating to other websites; 2) in context - -the browsed web page provides implicit context information which helps infer user purchase preferences; 3) in focus - users easily specify their search interest using gesture on touch devices and do not need to formulate queries in search box; 4) natural-gesture inputs and visual-based search provides users a natural shopping experience. The system is evaluated against a data set consisting of several millions commercial product images. © 2012 Authors
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