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Combined Exposure to Simulated Microgravity and Acute or Chronic Radiation Reduces Neuronal Network Integrity and Survival

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      Abstract

      During orbital or interplanetary space flights, astronauts are exposed to cosmic radiations and microgravity. However, most earth-based studies on the potential health risks of space conditions have investigated the effects of these two conditions separately. This study aimed at assessing the combined effect of radiation exposure and microgravity on neuronal morphology and survival in vitro. In particular, we investigated the effects of simulated microgravity after acute (X-rays) or during chronic (Californium-252) exposure to ionizing radiation using mouse mature neuron cultures. Acute exposure to low (0.1 Gy) doses of X-rays caused a delay in neurite outgrowth and a reduction in soma size, while only the high dose impaired neuronal survival. Of interest, the strongest effect on neuronal morphology and survival was evident in cells exposed to microgravity and in particular in cells exposed to both microgravity and radiation. Removal of neurons from simulated microgravity for a period of 24 h was not sufficient to recover neurite length, whereas the soma size showed a clear re-adaptation to normal ground conditions. Genome-wide gene expression analysis confirmed a modulation of genes involved in neurite extension, cell survival and synaptic communication, suggesting that these changes might be responsible for the observed morphological effects. In general, the observed synergistic changes in neuronal network integrity and cell survival induced by simulated space conditions might help to better evaluate the astronaut's health risks and underline the importance of investigating the central nervous system and long-term cognition during and after a space flight.

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      A new mathematical model for relative quantification in real-time RT-PCR.

       M. Pfaffl (2001)
      Use of the real-time polymerase chain reaction (PCR) to amplify cDNA products reverse transcribed from mRNA is on the way to becoming a routine tool in molecular biology to study low abundance gene expression. Real-time PCR is easy to perform, provides the necessary accuracy and produces reliable as well as rapid quantification results. But accurate quantification of nucleic acids requires a reproducible methodology and an adequate mathematical model for data analysis. This study enters into the particular topics of the relative quantification in real-time RT-PCR of a target gene transcript in comparison to a reference gene transcript. Therefore, a new mathematical model is presented. The relative expression ratio is calculated only from the real-time PCR efficiencies and the crossing point deviation of an unknown sample versus a control. This model needs no calibration curve. Control levels were included in the model to standardise each reaction run with respect to RNA integrity, sample loading and inter-PCR variations. High accuracy and reproducibility (<2.5% variation) were reached in LightCycler PCR using the established mathematical model.
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        REVIGO Summarizes and Visualizes Long Lists of Gene Ontology Terms

        Outcomes of high-throughput biological experiments are typically interpreted by statistical testing for enriched gene functional categories defined by the Gene Ontology (GO). The resulting lists of GO terms may be large and highly redundant, and thus difficult to interpret. REVIGO is a Web server that summarizes long, unintelligible lists of GO terms by finding a representative subset of the terms using a simple clustering algorithm that relies on semantic similarity measures. Furthermore, REVIGO visualizes this non-redundant GO term set in multiple ways to assist in interpretation: multidimensional scaling and graph-based visualizations accurately render the subdivisions and the semantic relationships in the data, while treemaps and tag clouds are also offered as alternative views. REVIGO is freely available at http://revigo.irb.hr/.
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          GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists

          Background Since the inception of the GO annotation project, a variety of tools have been developed that support exploring and searching the GO database. In particular, a variety of tools that perform GO enrichment analysis are currently available. Most of these tools require as input a target set of genes and a background set and seek enrichment in the target set compared to the background set. A few tools also exist that support analyzing ranked lists. The latter typically rely on simulations or on union-bound correction for assigning statistical significance to the results. Results GOrilla is a web-based application that identifies enriched GO terms in ranked lists of genes, without requiring the user to provide explicit target and background sets. This is particularly useful in many typical cases where genomic data may be naturally represented as a ranked list of genes (e.g. by level of expression or of differential expression). GOrilla employs a flexible threshold statistical approach to discover GO terms that are significantly enriched at the top of a ranked gene list. Building on a complete theoretical characterization of the underlying distribution, called mHG, GOrilla computes an exact p-value for the observed enrichment, taking threshold multiple testing into account without the need for simulations. This enables rigorous statistical analysis of thousand of genes and thousands of GO terms in order of seconds. The output of the enrichment analysis is visualized as a hierarchical structure, providing a clear view of the relations between enriched GO terms. Conclusion GOrilla is an efficient GO analysis tool with unique features that make a useful addition to the existing repertoire of GO enrichment tools. GOrilla's unique features and advantages over other threshold free enrichment tools include rigorous statistics, fast running time and an effective graphical representation. GOrilla is publicly available at:
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            Author and article information

            Affiliations
            [1 ]Radiobiology Unit, Laboratory of Molecular and Cellular Biology, Institute for Environment, Health and Safety, Belgian Nuclear Research Centre, SCK•CEN, Mol, Belgium
            [2 ]Cell Systems and Imaging Research Group (CSI), Department of Molecular Biotechnology, Ghent University, Ghent, Belgium
            [3 ]Laboratory of Membrane Biochemistry and Applied Nutrition, Department of Pharmacology and Bio-molecular Sciences (DiSFeB), Università degli Studi di Milano, Milano, Italy
            University of Louisville, UNITED STATES
            Author notes

            Competing Interests: The authors have declared that no competing interests exist.

            Conceived and designed the experiments: GP MV RQ PvO SB MB. Performed the experiments: GP MV RQ NS LD. Analyzed the data: GP MV RQ. Wrote the paper: GP MV RQ.

            Contributors
            Role: Editor
            Journal
            PLoS One
            PLoS ONE
            plos
            plosone
            PLoS ONE
            Public Library of Science (San Francisco, CA USA )
            1932-6203
            20 May 2016
            2016
            : 11
            : 5
            27203085 4874625 10.1371/journal.pone.0155260 PONE-D-16-01283
            © 2016 Pani et al

            This is an open access article 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.

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            Figures: 6, Tables: 0, Pages: 19
            Product
            Funding
            Funded by: Prodex/ESA
            Award ID: C90-303
            Award Recipient :
            Funded by: Prodex/ESA
            Award ID: C90-391
            Award Recipient :
            Funded by: Prodex/ESA
            Award ID: C0-90-11-2801-02
            Award Recipient :
            Funded by: Sardinian government
            Award ID: AF-DR-A2008-67
            Award Recipient :
            Funded by PRODEX/ESA: C90-303, C90-391, C0-90-11-2801-02, Sardinian government: EF-DR-A2008-67. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
            Categories
            Research Article
            Biology and Life Sciences
            Cell Biology
            Cellular Types
            Animal Cells
            Neurons
            Biology and Life Sciences
            Neuroscience
            Cellular Neuroscience
            Neurons
            Biology and Life Sciences
            Cell Biology
            Cell Processes
            Cell Death
            Apoptosis
            Biology and Life Sciences
            Cell Biology
            Cellular Types
            Animal Cells
            Neurons
            Neuronal Dendrites
            Neurites
            Biology and Life Sciences
            Neuroscience
            Cellular Neuroscience
            Neurons
            Neuronal Dendrites
            Neurites
            Biology and Life Sciences
            Neuroscience
            Cellular Neuroscience
            Neuronal Morphology
            Physical Sciences
            Physics
            Gravitation
            Artificial Gravity
            Biology and Life Sciences
            Genetics
            Gene Expression
            Physical Sciences
            Physics
            Nuclear Physics
            Nucleons
            Biology and Life Sciences
            Cell Biology
            Cell Processes
            Cell Death
            Neuronal Death
            Custom metadata
            All relevant data are within the paper.

            Uncategorized

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