Rough set and rule-based multicriteria decision aiding

The aim of multicriteria decision aiding is to give the decision maker a recommendation concerning a set of objects evaluated from multiple points of view called criteria. Since a rational decision maker acts with respect to his/her value system, in order to recommend the most-preferred decision, one must identify decision maker's preferences. In this paper, we focus on preference discovery from data concerning some past decisions of the decision maker. We consider the preference model in the form of a set of "if..., then..." decision rules discovered from the data by inductive learning. To structure the data prior to induction of rules, we use the Dominance-based Rough Set Approach (DRSA). DRSA is a methodology for reasoning about data, which handles ordinal evaluations of objects on considered criteria and monotonic relationships between these evaluations and the decision. We review applications of DRSA to a large variety of multicriteria decision problems

Genome-Wide DNA Methylation Analysis Identifies Novel Hypomethylated Non-Pericentromeric Genes with Potential Clinical Implications in ICF Syndrome

Introduction and Results Immunodeficiency, centromeric instability and facial anomalies syndrome (ICF) is a rare autosomal recessive disease, characterized by severe hypomethylation in pericentromeric regions of chromosomes (1, 16 and 9), marked immunodeficiency and facial anomalies. The majority of ICF patients present mutations in the DNMT3B gene, affecting the DNA methyltransferase activity of the protein. In the present study, we have used the Infinium 450K DNA methylation array to evaluate the methylation level of 450,000 CpGs in lymphoblastoid cell lines and untrasformed fibroblasts derived from ICF patients and healthy donors. Our results demonstrate that ICF-specific DNMT3B variants A603T/STP807ins and V699G/R54X cause global DNA hypomethylation compared to wild-type protein. We identified 181 novel differentially methylated positions (DMPs) including subtelomeric and intrachromosomic regions, outside the classical ICF-related pericentromeric hypomethylated positions. Interestingly, these sites were mainly located in intergenic regions and inside the CpG islands. Among the identified hypomethylated CpG-island associated genes, we confirmed the overexpression of three selected genes, BOLL, SYCP2 and NCRNA00221, in ICF compared to healthy controls, which are supposed to be expressed in germ line and silenced in somatic tissues. Conclusions In conclusion, this study contributes in clarifying the direct relationship between DNA methylation defect and gene expression impairment in ICF syndrome, identifying novel direct target genes of DNMT3B. A high percentage of the DMPs are located in the subtelomeric regions, indicating a specific role of DNMT3B in methylating these chromosomal sites. Therefore, we provide further evidence that hypomethylation in specific non-pericentromeric regions of chromosomes might be involved in the molecular pathogenesis of ICF syndrome. The detection of DNA hypomethylation at BOLL, SYCP2 and NCRNA00221 may pave the way for the development of specific clinical biomarkers with the aim to facilitate the identification of ICF patients

Comprehensive climate system modeling on massively parallel computers

A better understanding of both natural and human induced changes to the Earth`s climate is necessary for policy makers to make informed decisions regarding energy usage and other greenhouse gas producing activities. To achieve this, substantial increases in the sophistication of climate models are required. Coupling between the climate subsystems of the atmosphere, oceans, cryosphere and biosphere is only now beginning to be explored in global models. the enormous computational expenses of such models is one significant factor limiting progress. A comprehensive climate system model targeted to distributed memory massively parallel processing (MPP) computers is under development at Lawrence Livermore National Laboratory. This class of computers promises the computational power to permit the timely execution of climate models of substantially more sophistication than current generation models. Our strategy for achieving high performance on large numbers of processors is to exploit the multiple layers of parallelism naturally contained within highly coupled global climate models. The centerpiece of this strategy is the concurrent execution of multiple independently parallelized components of the climate system model. This methodology allows the assignment of an arbitrary number of processors to each of the major climate subsystems. Hence, a higher total number of processors may be efficiently used. Furthermore, load imbalances arising from the coupling of submodels may be minimized by adjusting the distribution of processors among the submodels

The Methyl-CpG Binding Proteins Mecp2, Mbd2 and Kaiso Are Dispensable for Mouse Embryogenesis, but Play a Redundant Function in Neural Differentiation

The precise molecular changes that occur when a neural stem (NS) cell switches from a programme of self-renewal to commit towards a specific lineage are not currently well understood. However it is clear that control of gene expression plays an important role in this process. DNA methylation, a mark of transcriptionally silent chromatin, has similarly been shown to play important roles in neural cell fate commitment in vivo. While DNA methylation is known to play important roles in neural specification during embryonic development, no such role has been shown for any of the methyl-CpG binding proteins (Mecps) in mice.. No evidence for functional redundancy between these genes in embryonic development or in the derivation or maintenance of neural stem cells in culture was detectable. However evidence for a defect in neuronal commitment of triple knockout NS cells was found.Although DNA methylation is indispensable for mammalian embryonic development, we show that simultaneous deficiency of three methyl-CpG binding proteins genes is compatible with apparently normal mouse embryogenesis. Nevertheless, we provide genetic evidence for redundancy of function between methyl-CpG binding proteins in postnatal mice

Drosophila as a Model for MECP2 Gain of Function in Neurons

Methyl-CpG-binding protein 2 (MECP2) is a multi-functional regulator of gene expression. In humans loss of MECP2 function causes classic Rett syndrome, but gain of MECP2 function also causes mental retardation. Although mouse models provide valuable insight into Mecp2 gain and loss of function, the identification of MECP2 genetic targets and interactors remains time intensive and complicated. This study takes a step toward utilizing Drosophila as a model to identify genetic targets and cellular consequences of MECP2 gain-of function mutations in neurons, the principle cell type affected in patients with Rett-related mental retardation. We show that heterologous expression of human MECP2 in Drosophila motoneurons causes distinct defects in dendritic structure and motor behavior, as reported with MECP2 gain of function in humans and mice. Multiple lines of evidence suggest that these defects arise from specific MECP2 function. First, neurons with MECP2-induced dendrite loss show normal membrane currents. Second, dendritic phenotypes require an intact methyl-CpG-binding domain. Third, dendritic defects are amended by reducing the dose of the chromatin remodeling protein, osa, indicating that MECP2 may act via chromatin remodeling in Drosophila. MECP2-induced motoneuron dendritic defects cause specific motor behavior defects that are easy to score in genetic screening. In sum, our data show that some aspects of MECP2 function can be studied in the Drosophila model, thus expanding the repertoire of genetic reagents that can be used to unravel specific neural functions of MECP2. However, additional genes and signaling pathways identified through such approaches in Drosophila will require careful validation in the mouse model

Gender differences in hemispheric asymmetry for face processing

BACKGROUND: Current cognitive neuroscience models predict a right-hemispheric dominance for face processing in humans. However, neuroimaging and electromagnetic data in the literature provide conflicting evidence of a right-sided brain asymmetry for decoding the structural properties of faces. The purpose of this study was to investigate whether this inconsistency might be due to gender differences in hemispheric asymmetry. RESULTS: In this study, event-related brain potentials (ERPs) were recorded in 40 healthy, strictly right-handed individuals (20 women and 20 men) while they observed infants' faces expressing a variety of emotions. Early face-sensitive P1 and N1 responses to neutral vs. affective expressions were measured over the occipital/temporal cortices, and the responses were analyzed according to viewer gender. Along with a strong right hemispheric dominance for men, the results showed a lack of asymmetry for face processing in the amplitude of the occipito-temporal N1 response in women to both neutral and affective faces. CONCLUSION: Men showed an asymmetric functioning of visual cortex while decoding faces and expressions, whereas women showed a more bilateral functioning. These results indicate the importance of gender effects in the lateralization of the occipito-temporal response during the processing of face identity, structure, familiarity, or affective content