2,518 research outputs found

    Hydrogenase Gene Distribution and H2 Consumption Ability within the Thiomicrospira Lineage

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    Thiomicrospira were originally characterized as sulfur-oxidizing chemolithoautotrophs. Attempts to grow them on hydrogen failed for many years. Only recently we demonstrated hydrogen consumption among two of three tested Thiomicrospira and posited that hydrogen consumption may be more widespread among Thiomicrospira than previously assumed. Here, we investigate and compare the hydrogen consumption ability and the presence of group 1 [NiFe]-hydrogenase genes (enzyme catalyzes H2↔2H+ + 2e-) for sixteen different Thiomicrospira species. Seven of these Thiomicrospira species encoded group 1 [NiFe]-hydrogenase genes and five of these species could also consume hydrogen. All Thiomicrospira species exhibiting hydrogen consumption were from hydrothermal vents along the Mid-Atlantic ridge or Eastern Pacific ridges. The tested Thiomicrospira from Mediterranean and Western Pacific vents could not consume hydrogen. The [NiFe]-hydrogenase genes were categorized into two clusters: those resembling the hydrogenase from Hydrogenovibrio are in cluster I and are related to those from Alpha- and other Gammaproteobacteria. In cluster II, hydrogenases found exclusively in Thiomicrospira crunogena strains are combined and form a monophyletic group with those from Epsilonproteobacteria suggesting they were acquired through horizontal gene transfer. Hydrogen consumption appears to be common among some Thiomicrospira, given that five of the tested sixteen strains carried this trait. The hydrogen consumption ability expands their competitiveness within an environment

    Cameo: A Python Library for Computer Aided Metabolic Engineering and Optimization of Cell Factories

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    Computational systems biology methods enable rational design of cell factories on a genome-scale and thus accelerate the engineering of cells for the production of valuable chemicals and proteins. Unfortunately, the majority of these methods’ implementations are either not published, rely on proprietary software, or do not provide documented interfaces, which has precluded their mainstream adoption in the field. In this work we present cameo, a platform-independent software that enables <i>in silico</i> design of cell factories and targets both experienced modelers as well as users new to the field. It is written in Python and implements state-of-the-art methods for enumerating and prioritizing knockout, knock-in, overexpression, and down-regulation strategies and combinations thereof. Cameo is an open source software project and is freely available under the Apache License 2.0. A dedicated Web site including documentation, examples, and installation instructions can be found at http://cameo.bio. Users can also give cameo a try at http://try.cameo.bio

    The specifier–head relationship: negation and French subject proforms

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    This article1 and the three others in this thematic collection are about heads and specifiers, the relationship between them, and how this relationship can change over time. A theme which emerges is the notion that the spec(ifier)–head relationship is cyclic, in other words, the synchronic relationship between the head and its specifier within a given phrase in a given language can be characterised as a location at a particular point on a cycle, while the diachronic development of the relationship can be seen as a directional stepwise shift around that cycle. The article is organised as follows. Section 2 introduces the theoretical framework. Section 3.1 sketches a well-known diachronic phenomenon – the history of sentential negation – which readily lends itself to an analysis in terms of a cyclic spec–head relationship, and shows how the stages in the cycle have been characterised theoretically. Section 3.2 considers another set of data − pre- and postverbal subject proforms in French − which is similarly suitable for such an approach. Section 4, finally, introduces the three other contributions to the collection

    Isolating Crucial Steps in Induction of Infective Endocarditis With Preclinical Modeling of Host Pathogen Interaction

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    Animal models of Staphylococcus aureus infective endocarditis (IE), especially in rodents, are commonly used to investigate the underlying pathogenesis, disease progression, potential diagnostic approaches, and therapeutic treatment. All these models are based on surgical interventions, and imply valve trauma by placing a polyurethane catheter at the aortic root. While the influence of endothelial damage and inflammation on the induction of IE has been studied intensively, the role of the catheter, as permanent source of bacteremia, and the interplay with bacterial virulence factors during the formation of IE is poorly understood. In our study, we aimed at identifying which set of preconditions is required for induction and formation of IE: (1) tissue injury, (2) permanent presence of bacteria, and (3) presence of the full bacterial repertoire of adhesion proteins. We investigated the manifestation of the disease in different modifications of the animal model, considering different degrees of endothelial damage and the presence or absence of the catheter. In four infection models the induction of IE was assessed by using two bacterial strains with different expression patterns of virulence factors – S. aureus 6850 and Newman. In vivo magnetic resonance imaging showed conspicuous morphological structures on the aortic valves, when an endothelial damage and a continuous bacterial source were present simultaneously. Cellular and inflammatory pathophysiology were characterized additionally by histology, real-time quantitative polymerase chain reaction analysis, and bacterial counts, revealing strain-specific pathogenesis and manifestation of IE, crucially influenced by bacterial adherence and toxicity. The severity of IE was dependent on the degree of endothelial irritation. However, even severe endothelial damage in the absence of a permanent bacterial source resulted in reduced valve infection. The spread of bacteria to other organs was also dependent on the pathogenic profile of the infectious agent

    An electrochemically functional layer of hydrogenase extract on an electrode of large and tunable specific surface area

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    Electrode supports are generated by electrospinning of polyacrylonitrile fibers and subsequent coating of a thin electrically conductive TiO2 layer by atomic layer deposition. The supports are then functionalized with a [NiFe]-hydrogenase-containing membrane fraction from Escherichia coli and are characterized structurally and electrochemically. The hydrogenase suspension generates a micron-thick organic film around the fiber mat, which exhibits electrocatalytic activity for hydrogen evolution. Furthermore, the electrode geometric surface area is varied systematically via the electrospinning procedure, which reduces the charge transfer resistance and increases the hydrogen evolution current density to >500 μA cm−2 at 0.3 V overpotential

    Activation of brain regions vulnerable to Alzheimer\u27s disease: The effect of mild cognitive impairment

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    This study examined the functionality of the medial temporal lobe (MTL) and posterior cingulate (PC) in mild cognitive impairment amnestic type (MCI), a syndrome that puts patients at greater risk for developing Alzheimer disease (AD). Functional MRI (fMRI) was used to identify regions normally active during encoding of novel items and recognition of previously learned items in a reference group of 77 healthy young and middle-aged adults. The pattern of activation in this group guided further comparisons between 14 MCI subjects and 14 age-matched controls. The MCI patients exhibited less activity in the PC during recognition of previously learned items, and in the right hippocampus during encoding of novel items, despite comparable task performance to the controls. Reduced fMRI signal change in the MTL supports prior studies implicating the hippocampus for encoding new information. Reduced signal change in the PC converges with recent research on its role in recognition in normal adults as well as metabolic decline in people with genetic or cognitive risk for AD. Our results suggest that a change in function in the PC may account, in part, for memory recollection failure in AD. © 2005 Elsevier Inc. All rights reserved

    Microscopic structure and dynamics of glass forming Zr2Co melts and the impact of different late transition metals on the melt properties

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    We studied the short-range order and the atomic dynamics of stable and undercooled binary Zr2Co alloy melts as well as their density and viscosity. The containerless processing technique of electrostatic levitation was used to achieve deep undercooling and to avoid contaminations. Static structure factors are determined by combining this technique with neutron and high energy X-ray diffraction. Co self-diffusion coefficients are measured by quasielastic neutron scattering. Our results reveal that the short-range order of the Zr2Co melts closely resembles that previously observed for Zr64Ni36. We consider this as the origin of the very similar melt dynamics of these two alloys at same temperatures. On the other hand, the difference in the structure and dynamics when compared with those of Zr2Cu and Zr2Pd shows clearly that not only the atomic sizes, but also electronic properties or chemical bonding have an important influence on the melt properties of Zr-based glass forming melts

    Proposed Mobility Assessments with Simultaneous Full-Body Inertial Measurement Units and Optical Motion Capture in Healthy Adults and Neurological Patients for Future Validation Studies: Study Protocol

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    Healthy adults and neurological patients show unique mobility patterns over the course of their lifespan and disease. Quantifying these mobility patterns could support diagnosing, tracking disease progression and measuring response to treatment. This quantification can be done with wearable technology, such as inertial measurement units (IMUs). Before IMUs can be used to quantify mobility, algorithms need to be developed and validated with age and disease-specific datasets. This study proposes a protocol for a dataset that can be used to develop and validate IMU-based mobility algorithms for healthy adults (18–60 years), healthy older adults (>60 years), and patients with Parkinson’s disease, multiple sclerosis, a symptomatic stroke and chronic low back pain. All participants will be measured simultaneously with IMUs and a 3D optical motion capture system while performing standardized mobility tasks and non-standardized activities of daily living. Specific clinical scales and questionnaires will be collected. This study aims at building the largest dataset for the development and validation of IMU-based mobility algorithms for healthy adults and neurological patients. It is anticipated to provide this dataset for further research use and collaboration, with the ultimate goal to bring IMU-based mobility algorithms as quickly as possible into clinical trials and clinical routine
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