Computing symmetry groups of polyhedra

Knowing the symmetries of a polyhedron can be very useful for the analysis of its structure as well as for practical polyhedral computations. In this note, we study symmetry groups preserving the linear, projective and combinatorial structure of a polyhedron. In each case we give algorithmic methods to compute the corresponding group and discuss some practical experiences. For practical purposes the linear symmetry group is the most important, as its computation can be directly translated into a graph automorphism problem. We indicate how to compute integral subgroups of the linear symmetry group that are used for instance in integer linear programming.Comment: 20 pages, 1 figure; containing a corrected and improved revisio

Covalent PARylation of DNA base excision repair proteins regulates DNA demethylation.

The intracellular ATP-ribosyltransferases PARP1 and PARP2, contribute to DNA base excision repair (BER) and DNA demethylation and have been implicated in epigenetic programming in early mammalian development. Recently, proteomic analyses identified BER proteins to be covalently poly-ADP-ribosylated by PARPs. The role of this posttranslational modification in the BER process is unknown. Here, we show that PARP1 senses AP-sites and SSBs generated during TET-TDG mediated active DNA demethylation and covalently attaches PAR to each BER protein engaged. Covalent PARylation dissociates BER proteins from DNA, which accelerates the completion of the repair process. Consistently, inhibition of PARylation in mESC resulted both in reduced locus-specific TET-TDG-targeted DNA demethylation, and in reduced general repair of random DNA damage. Our findings establish a critical function of covalent protein PARylation in coordinating molecular processes associated with dynamic DNA methylation

Structural Information in Two-Dimensional Patterns: Entropy Convergence and Excess Entropy

We develop information-theoretic measures of spatial structure and pattern in more than one dimension. As is well known, the entropy density of a two-dimensional configuration can be efficiently and accurately estimated via a converging sequence of conditional entropies. We show that the manner in which these conditional entropies converge to their asymptotic value serves as a measure of global correlation and structure for spatial systems in any dimension. We compare and contrast entropy-convergence with mutual-information and structure-factor techniques for quantifying and detecting spatial structure.Comment: 11 pages, 5 figures, http://www.santafe.edu/projects/CompMech/papers/2dnnn.htm

Differences in autophagy marker levels at birth in preterm vs. term infants.

BACKGROUND Preterm infants are susceptible to oxidative stress and prone to respiratory diseases. Autophagy is an important defense mechanism against oxidative-stress-induced cell damage and involved in lung development and respiratory morbidity. We hypothesized that autophagy marker levels differ between preterm and term infants. METHODS In the prospective Basel-Bern Infant Lung Development (BILD) birth cohort we compared cord blood levels of macroautophagy (Beclin-1, LC3B), selective autophagy (p62) and regulation of autophagy (SIRT1) in 64 preterm and 453 term infants. RESULTS Beclin-1 and LC3B did not differ between preterm and term infants. However, p62 was higher (0.37, 95% confidence interval (CI) 0.05;0.69 in log2-transformed level, p = 0.025, padj = 0.050) and SIRT1 lower in preterm infants (-0.55, 95% CI -0.78;-0.31 in log2-transformed level, padj < 0.001). Furthermore, p62 decreased (padj-value for smoothing function was 0.018) and SIRT1 increased (0.10, 95% CI 0.07;0.13 in log2-transformed level, padj < 0.001) with increasing gestational age. CONCLUSION Our findings suggest differential levels of key autophagy markers between preterm and term infants. This adds to the knowledge of the sparsely studied field of autophagy mechanisms in preterm infants and might be linked to impaired oxidative stress response, preterm birth, impaired lung development and higher susceptibility to respiratory morbidity in preterm infants. IMPACT To the best of our knowledge, this is the first study to investigate autophagy marker levels between human preterm and term infants in a large population-based sample in cord blood plasma This study demonstrates differential levels of key autophagy markers in preterm compared to term infants and an association with gestational age This may be linked to impaired oxidative stress response or developmental aspects and provide bases for future studies investigating the association with respiratory morbidity

Intelligent data analysis to interpret major risk factors for diabetic patients with and without ischemic stroke in a small population

This study proposes an intelligent data analysis approach to investigate and interpret the distinctive factors of diabetes mellitus patients with and without ischemic (non-embolic type) stroke in a small population. The database consists of a total of 16 features collected from 44 diabetic patients. Features include age, gender, duration of diabetes, cholesterol, high density lipoprotein, triglyceride levels, neuropathy, nephropathy, retinopathy, peripheral vascular disease, myocardial infarction rate, glucose level, medication and blood pressure. Metric and non-metric features are distinguished. First, the mean and covariance of the data are estimated and the correlated components are observed. Second, major components are extracted by principal component analysis. Finally, as common examples of local and global classification approach, a k-nearest neighbor and a high-degree polynomial classifier such as multilayer perceptron are employed for classification with all the components and major components case. Macrovascular changes emerged as the principal distinctive factors of ischemic-stroke in diabetes mellitus. Microvascular changes were generally ineffective discriminators. Recommendations were made according to the rules of evidence-based medicine. Briefly, this case study, based on a small population, supports theories of stroke in diabetes mellitus patients and also concludes that the use of intelligent data analysis improves personalized preventive intervention