34,346 research outputs found

    Identification of small RNAs abundant in Burkholderia cenocepacia biofilms reveal putative regulators with a potential role in carbon and iron metabolism

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    Small RNAs play a regulatory role in many central metabolic processes of bacteria, as well as in developmental processes such as biofilm formation. Small RNAs of Burkholderia cenocepacia, an opportunistic pathogenic beta-proteobacterium, are to date not well characterised. To address that, we performed genome-wide transcriptome structure analysis of biofilm grown B. cenocepacia J2315. 41 unannotated short transcripts were identified in intergenic regions of the B. cenocepacia genome. 15 of these short transcripts, highly abundant in biofilms, widely conserved in Burkholderia sp. and without known function, were selected for in-depth analysis. Expression profiling showed that most of these sRNAs are more abundant in biofilms than in planktonic cultures. Many are also highly abundant in cells grown in minimal media, suggesting they are involved in adaptation to nutrient limitation and growth arrest. Their computationally predicted targets include a high proportion of genes involved in carbon metabolism. Expression and target genes of one sRNA suggest a potential role in regulating iron homoeostasis. The strategy used for this study to detect sRNAs expressed in B. cenocepacia biofilms has successfully identified sRNAs with a regulatory function

    Third Earth Resources Technology Satellite Symposium. Volume 3: Discipline summary reports

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    Presentations at the conference covered the following disciplines: (1) agriculture, forestry, and range resources; (2) land use and mapping; (3) mineral resources, geological structure, and landform surveys; (4) water resources; (5) marine resources; (6) environment surveys; and (7) interpretation techniques

    Proceedings of Abstracts Engineering and Computer Science Research Conference 2019

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    © 2019 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Note: Keynote: Fluorescence visualisation to evaluate effectiveness of personal protective equipment for infection control is © 2019 Crown copyright and so is licensed under the Open Government Licence v3.0. Under this licence users are permitted to copy, publish, distribute and transmit the Information; adapt the Information; exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application. Where you do any of the above you must acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This conference is a local event aiming at bringing together the research students, staff and eminent external guests to celebrate Engineering and Computer Science Research at the University of Hertfordshire. The ECS Research Conference aims to showcase the broad landscape of research taking place in the School of Engineering and Computer Science. The 2019 conference was articulated around three topical cross-disciplinary themes: Make and Preserve the Future; Connect the People and Cities; and Protect and Care

    Toward a multilevel representation of protein molecules: comparative approaches to the aggregation/folding propensity problem

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    This paper builds upon the fundamental work of Niwa et al. [34], which provides the unique possibility to analyze the relative aggregation/folding propensity of the elements of the entire Escherichia coli (E. coli) proteome in a cell-free standardized microenvironment. The hardness of the problem comes from the superposition between the driving forces of intra- and inter-molecule interactions and it is mirrored by the evidences of shift from folding to aggregation phenotypes by single-point mutations [10]. Here we apply several state-of-the-art classification methods coming from the field of structural pattern recognition, with the aim to compare different representations of the same proteins gathered from the Niwa et al. data base; such representations include sequences and labeled (contact) graphs enriched with chemico-physical attributes. By this comparison, we are able to identify also some interesting general properties of proteins. Notably, (i) we suggest a threshold around 250 residues discriminating "easily foldable" from "hardly foldable" molecules consistent with other independent experiments, and (ii) we highlight the relevance of contact graph spectra for folding behavior discrimination and characterization of the E. coli solubility data. The soundness of the experimental results presented in this paper is proved by the statistically relevant relationships discovered among the chemico-physical description of proteins and the developed cost matrix of substitution used in the various discrimination systems.Comment: 17 pages, 3 figures, 46 reference

    Applications of active microwave imagery

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    The following topics were discussed in reference to active microwave applications: (1) Use of imaging radar to improve the data collection/analysis process; (2) Data collection tasks for radar that other systems will not perform; (3) Data reduction concepts; and (4) System and vehicle parameters: aircraft and spacecraft

    Third Earth Resources Technology Satellite Symposium. Volume 2: Summary of results

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    Summaries are provided of significant results taken from presentations at the symposium along with some typical examples of the applications of ERTS-1 data for solving resources management problems at the national, state, and local levels
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