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      The effects of graded levels of calorie restriction: IX. Global metabolomic screen reveals modulation of carnitines, sphingolipids and bile acids in the liver of C57BL/6 mice

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          Summary

          Calorie restriction ( CR) remains the most robust intervention to extend lifespan and improve health span. Using a global mass spectrometry‐based metabolomic approach, we identified 193 metabolites that were significantly differentially expressed ( SDE) in the livers of C57 BL/6 mice, fed graded levels of CR (10, 20, 30 and 40% CR) compared to mice fed ad libitum for 12 h a day. The differential expression of metabolites also varied with the different feeding groups. Pathway analysis revealed that graded CR had an impact on carnitine synthesis and the carnitine shuttle pathway, sphingosine‐1‐phosphate (S1P) signalling and methionine metabolism. S1P, sphingomyelin and L‐carnitine were negatively correlated with body mass, leptin, insulin‐like growth factor‐ 1 ( IGF‐1) and major urinary proteins ( MUPs). In addition, metabolites which showed a graded effect, such as ceramide, S1P, taurocholic acid and L‐carnitine, responded in the opposite direction to previously observed age‐related changes. We suggest that the modulation of this set of metabolites may improve liver processes involved in energy release from fatty acids. S1P also negatively correlated with catalase activity and body temperature, and positively correlated with food anticipatory activity. Injecting mice with S1P or an S1P receptor 1 agonist did not precipitate changes in body temperature, physical activity or food intake suggesting that these correlations were not causal relationships.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            MissForest--non-parametric missing value imputation for mixed-type data.

            Modern data acquisition based on high-throughput technology is often facing the problem of missing data. Algorithms commonly used in the analysis of such large-scale data often depend on a complete set. Missing value imputation offers a solution to this problem. However, the majority of available imputation methods are restricted to one type of variable only: continuous or categorical. For mixed-type data, the different types are usually handled separately. Therefore, these methods ignore possible relations between variable types. We propose a non-parametric method which can cope with different types of variables simultaneously. We compare several state of the art methods for the imputation of missing values. We propose and evaluate an iterative imputation method (missForest) based on a random forest. By averaging over many unpruned classification or regression trees, random forest intrinsically constitutes a multiple imputation scheme. Using the built-in out-of-bag error estimates of random forest, we are able to estimate the imputation error without the need of a test set. Evaluation is performed on multiple datasets coming from a diverse selection of biological fields with artificially introduced missing values ranging from 10% to 30%. We show that missForest can successfully handle missing values, particularly in datasets including different types of variables. In our comparative study, missForest outperforms other methods of imputation especially in data settings where complex interactions and non-linear relations are suspected. The out-of-bag imputation error estimates of missForest prove to be adequate in all settings. Additionally, missForest exhibits attractive computational efficiency and can cope with high-dimensional data. The package missForest is freely available from http://stat.ethz.ch/CRAN/. stekhoven@stat.math.ethz.ch; buhlmann@stat.math.ethz.ch
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              Superoxide dismutases: role in redox signaling, vascular function, and diseases.

              Excessive reactive oxygen species Revised abstract, especially superoxide anion (O₂•-), play important roles in the pathogenesis of many cardiovascular diseases, including hypertension and atherosclerosis. Superoxide dismutases (SODs) are the major antioxidant defense systems against (O₂•-), which consist of three isoforms of SOD in mammals: the cytoplasmic Cu/ZnSOD (SOD1), the mitochondrial MnSOD (SOD2), and the extracellular Cu/ZnSOD (SOD3), all of which require catalytic metal (Cu or Mn) for their activation. Recent evidence suggests that in each subcellular location, SODs catalyze the conversion of (O₂•-), H2O2, which may participate in cell signaling. In addition, SODs play a critical role in inhibiting oxidative inactivation of nitric oxide, thereby preventing peroxynitrite formation and endothelial and mitochondrial dysfunction. The importance of each SOD isoform is further illustrated by studies from the use of genetically altered mice and viral-mediated gene transfer. Given the essential role of SODs in cardiovascular disease, the concept of antioxidant therapies, that is, reinforcement of endogenous antioxidant defenses to more effectively protect against oxidative stress, is of substantial interest. However, the clinical evidence remains controversial. In this review, we will update the role of each SOD in vascular biologies, physiologies, and pathophysiologies such as atherosclerosis, hypertension, and angiogenesis. Because of the importance of metal cofactors in the activity of SODs, we will also discuss how each SOD obtains catalytic metal in the active sites. Finally, we will discuss the development of future SOD-dependent therapeutic strategies.
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                Author and article information

                Contributors
                j.speakman@abdn.ac.uk
                Journal
                Aging Cell
                Aging Cell
                10.1111/(ISSN)1474-9726
                ACEL
                Aging Cell
                John Wiley and Sons Inc. (Hoboken )
                1474-9718
                1474-9726
                31 January 2017
                June 2017
                : 16
                : 3 ( doiID: 10.1111/acel.2017.16.issue-3 )
                : 529-540
                Affiliations
                [ 1 ] Institute of Biological and Environmental SciencesUniversity of Aberdeen AberdeenUK
                [ 2 ] State Key Laboratory of Molecular Developmental Biology Institute of Genetics and Developmental BiologyChinese Academy of Sciences Chaoyang BeijingChina
                [ 3 ] Key Laboratory of Systems Biology, Innovation Center for Cell Signaling Network Institute of Biochemistry and Cell Biology Shanghai Institute of Biological SciencesChinese Academy of Sciences ShanghaiChina
                [ 4 ] Key Laboratory of Computational Biology Chinese Academy of Sciences‐Max Planck Partner Institute for Computational Biology Shanghai Institutes for Biological SciencesChinese Academy of Sciences ShanghaiChina
                [ 5 ] Department of Pathology and Department of BiologyUniversity of Washington Seattle WAUSA
                Author notes
                [*] [* ] Correspondence

                John R. Speakman, The Institute of Biological and Environmental Sciences, Zoology Building, Tillydrone Avenue, Aberdeen, AB24 2TZ, UK. Tel.: +44 1224 272879; fax: +44 1224 272396; e‐mail: j.speakman@ 123456abdn.ac.uk

                [†]

                Equal contribution.

                Article
                ACEL12570
                10.1111/acel.12570
                5418186
                28139067
                4c196f5b-d529-44ed-aeb6-f57601890212
                © 2017 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

                This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 23 December 2016
                Page count
                Figures: 4, Tables: 3, Pages: 12, Words: 10757
                Funding
                Funded by: UK Biotechnology and Biological Sciences Research Council BBSRC
                Award ID: BB/G009953/1
                Award ID: BB/J020028/1
                Funded by: NIH
                Award ID: AGO49494
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                acel12570
                June 2017
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.0.9 mode:remove_FC converted:18.05.2017

                Cell biology
                aging,bile acid,calorie restriction,carnitine,metabolomics,sphingolipid
                Cell biology
                aging, bile acid, calorie restriction, carnitine, metabolomics, sphingolipid

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