293 research outputs found

    A Lie algebra that can be written as a sum of two nilpotent subalgebras, is solvable

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    This is an old paper put here for archeological purposes. It is proved that a finite-dimensional Lie algebra over a field of characteristic p>5, that can be written as a vector space (not necessarily direct) sum of two nilpotent subalgebras, is solvable. The same result (but covering also the cases of low characteristics) was established independently by V. Panyukov (Russ. Math. Surv. 45 (1990), N4, 181-182), and the homological methods utilized in the proof were developed later in arXiv:math/0204004. Many inaccuracies in the English translation are corrected, otherwise the text is identical to the published version.Comment: v2: minor change

    Yield-related salinity tolerance traits identified in a nested association mapping (NAM) population of wild barley

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    Producing sufficient food for nine billion people by 2050 will be constrained by soil salinity, especially in irrigated systems. To improve crop yield, greater understanding of the genetic control of traits contributing to salinity tolerance in the field is needed. Here, we exploit natural variation in exotic germplasm by taking a genome-wide association approach to a new nested association mapping population of barley called HEB-25. The large population (1,336 genotypes) allowed cross-validation of loci, which, along with two years of phenotypic data collected from plants irrigated with fresh and saline water, improved statistical power. We dissect the genetic architecture of flowering time under high salinity and we present genes putatively affecting this trait and salinity tolerance. In addition, we identify a locus on chromosome 2H where, under saline conditions, lines homozygous for the wild allele yielded 30% more than did lines homozygous for the Barke allele. Introgressing this wild allele into elite cultivars could markedly improve yield under saline conditions.Stephanie Saade, Andreas Maurer, Mohammed Shahid, Helena Oakey, Sandra M. Schmöckel, Sónia Negrão, Klaus Pillen and Mark Teste

    Neuromuscular imaging in inherited muscle diseases

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    Driven by increasing numbers of newly identified genetic defects and new insights into the field of inherited muscle diseases, neuromuscular imaging in general and magnetic resonance imaging (MRI) in particular are increasingly being used to characterise the severity and pattern of muscle involvement. Although muscle biopsy is still the gold standard for the establishment of the definitive diagnosis, muscular imaging is an important diagnostic tool for the detection and quantification of dystrophic changes during the clinical workup of patients with hereditary muscle diseases. MRI is frequently used to describe muscle involvement patterns, which aids in narrowing of the differential diagnosis and distinguishing between dystrophic and non-dystrophic diseases. Recent work has demonstrated the usefulness of muscle imaging for the detection of specific congenital myopathies, mainly for the identification of the underlying genetic defect in core and centronuclear myopathies. Muscle imaging demonstrates characteristic patterns, which can be helpful for the differentiation of individual limb girdle muscular dystrophies. The aim of this review is to give a comprehensive overview of current methods and applications as well as future perspectives in the field of neuromuscular imaging in inherited muscle diseases. We also provide diagnostic algorithms that might guide us through the differential diagnosis in hereditary myopathies

    Protocol of the SOMNIA project : an observational study to create a neurophysiological database for advanced clinical sleep monitoring

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    Introduction Polysomnography (PSG) is the primary tool for sleep monitoring and the diagnosis of sleep disorders. Recent advances in signal analysis make it possible to reveal more information from this rich data source. Furthermore, many innovative sleep monitoring techniques are being developed that are less obtrusive, easier to use over long time periods and in the home situation. Here, we describe the methods of the Sleep and Obstructive Sleep Apnoea Monitoring with Non-Invasive Applications (SOMNIA) project, yielding a database combining clinical PSG with advanced unobtrusive sleep monitoring modalities in a large cohort of patients with various sleep disorders. The SOMNIA database will facilitate the validation and assessment of the diagnostic value of the new techniques, as well as the development of additional indices and biomarkers derived from new and/or traditional sleep monitoring methods. Methods and analysis We aim to include at least 2100 subjects (both adults and children) with a variety of sleep disorders who undergo a PSG as part of standard clinical care in a dedicated sleep centre. Full-video PSG will be performed according to the standards of the American Academy of Sleep Medicine. Each recording will be supplemented with one or more new monitoring systems, including wrist-worn photoplethysmography and actigraphy, pressure sensing mattresses, multimicrophone recording of respiratory sounds including snoring, suprasternal pressure monitoring and multielectrode electromyography of the diaphragm

    Advanced backcross-QTL analysis in spring barley (H. vulgare ssp. spontaneum) comparing a REML versus a Bayesian model in multi-environmental field trials

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    A common difficulty in mapping quantitative trait loci (QTLs) is that QTL effects may show environment specificity and thus differ across environments. Furthermore, quantitative traits are likely to be influenced by multiple QTLs or genes having different effect sizes. There is currently a need for efficient mapping strategies to account for both multiple QTLs and marker-by-environment interactions. Thus, the objective of our study was to develop a Bayesian multi-locus multi-environmental method of QTL analysis. This strategy is compared to (1) Bayesian multi-locus mapping, where each environment is analysed separately, (2) Restricted Maximum Likelihood (REML) single-locus method using a mixed hierarchical model, and (3) REML forward selection applying a mixed hierarchical model. For this study, we used data on multi-environmental field trials of 301 BC2DH lines derived from a cross between the spring barley elite cultivar Scarlett and the wild donor ISR42-8 from Israel. The lines were genotyped by 98 SSR markers and measured for the agronomic traits “ears per m²,” “days until heading,” “plant height,” “thousand grain weight,” and “grain yield”. Additionally, a simulation study was performed to verify the QTL results obtained in the spring barley population. In general, the results of Bayesian QTL mapping are in accordance with REML methods. In this study, Bayesian multi-locus multi-environmental analysis is a valuable method that is particularly suitable if lines are cultivated in multi-environmental field trials
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