Response-Time Analysis of Conditional DAG Tasks in Multiprocessor Systems

Different task models have been proposed to represent the parallel structure of real-time tasks executing on manycore platforms: fork/join, synchronous parallel, DAG-based, etc. Despite different schedulability tests and resource augmentation bounds are available for these task systems, we experience difficulties in applying such results to real application scenarios, where the execution flow of parallel tasks is characterized by multiple (and nested) conditional structures. When a conditional branch drives the number and size of sub-jobs to spawn, it is hard to decide which execution path to select for modeling the worst-case scenario. To circumvent this problem, we integrate control flow information in the task model, considering conditional parallel tasks (cp-tasks) represented by DAGs composed of both precedence and conditional edges. For this task model, we identify meaningful parameters that characterize the schedulability of the system, and derive efficient algorithms to compute them. A response time analysis based on these parameters is then presented for different scheduling policies. A set of simulations shows that the proposed approach allows efficiently checking the schedulability of the addressed systems, and that it significantly tightens the schedulability analysis of non-conditional (e.g., Classic DAG) tasks over existing approaches

A Bayesian method for evaluating and discovering disease loci associations

Background: A genome-wide association study (GWAS) typically involves examining representative SNPs in individuals from some population. A GWAS data set can concern a million SNPs and may soon concern billions. Researchers investigate the association of each SNP individually with a disease, and it is becoming increasingly commonplace to also analyze multi-SNP associations. Techniques for handling so many hypotheses include the Bonferroni correction and recently developed Bayesian methods. These methods can encounter problems. Most importantly, they are not applicable to a complex multi-locus hypothesis which has several competing hypotheses rather than only a null hypothesis. A method that computes the posterior probability of complex hypotheses is a pressing need. Methodology/Findings: We introduce the Bayesian network posterior probability (BNPP) method which addresses the difficulties. The method represents the relationship between a disease and SNPs using a directed acyclic graph (DAG) model, and computes the likelihood of such models using a Bayesian network scoring criterion. The posterior probability of a hypothesis is computed based on the likelihoods of all competing hypotheses. The BNPP can not only be used to evaluate a hypothesis that has previously been discovered or suspected, but also to discover new disease loci associations. The results of experiments using simulated and real data sets are presented. Our results concerning simulated data sets indicate that the BNPP exhibits both better evaluation and discovery performance than does a p-value based method. For the real data sets, previous findings in the literature are confirmed and additional findings are found. Conclusions/Significance: We conclude that the BNPP resolves a pressing problem by providing a way to compute the posterior probability of complex multi-locus hypotheses. A researcher can use the BNPP to determine the expected utility of investigating a hypothesis further. Furthermore, we conclude that the BNPP is a promising method for discovering disease loci associations. © 2011 Jiang et al

Cloning, expression and nuclear localization of human NPM3, a member of the nucleophosmin/nucleoplasmin family of nuclear chaperones

BACKGROUND: Studies suggest that the related proteins nucleoplasmin and nucleophosmin (also called B23, NO38 or numatrin) are nuclear chaperones that mediate the assembly of nucleosomes and ribosomes, respectively, and that these activities are accomplished through the binding of basic proteins via their acidic domains. Recently discovered and less well characterized members of this family of acidic phosphoproteins include mouse nucleophosmin/nucleoplasmin 3 (Npm3) and Xenopus NO29. Here we report the cloning and initial characterization of the human ortholog of Npm3. RESULTS: Human genomic and cDNA clones of NPM3 were isolated and sequenced. NPM3 lies 5.5 kb upstream of FGF8 and thus maps to chromosome 10q24-26. In addition to amino acid similarities, NPM3 shares many physical characteristics with the nucleophosmin/nucleoplasmin family, including an acidic domain, multiple potential phosphorylation sites and a putative nuclear localization signal. Comparative analyses of 14 members of this family from various metazoans suggest that Xenopus NO29 is a candidate ortholog of human and mouse NPM3, and they further group both proteins closer with the nucleoplasmins than with the nucleophosmins. Northern blot analysis revealed that NPM3 was strongly expressed in all 16 human tissues examined, with especially robust expression in pancreas and testis; lung displayed the lowest level of expression. An analysis of subcellular fractions of NIH3T3 cells expressing epitope-tagged NPM3 revealed that NPM3 protein was localized solely in the nucleus. CONCLUSIONS: Human NPM3 is an abundant and widely expressed protein with primarily nuclear localization. These biological activities, together with its physical relationship to the chaparones nucleoplasmin and nucleophosmin, are consistent with the proposed function of NPM3 as a molecular chaperone functioning in the nucleus

Computing Constrained Approximate Equilibria in Polymatrix Games

This paper is about computing constrained approximate Nash equilibria in polymatrix games, which are succinctly represented many-player games defined by an interaction graph between the players. In a recent breakthrough, Rubinstein showed that there exists a small constant $\epsilon$, such that it is PPAD-complete to find an (unconstrained) $\epsilon$-Nash equilibrium of a polymatrix game. In the first part of the paper, we show that is NP-hard to decide if a polymatrix game has a constrained approximate equilibrium for 9 natural constraints and any non-trivial approximation guarantee. These results hold even for planar bipartite polymatrix games with degree 3 and at most 7 strategies per player, and all non-trivial approximation guarantees. These results stand in contrast to similar results for bimatrix games, which obviously need a non-constant number of actions, and which rely on stronger complexity-theoretic conjectures such as the exponential time hypothesis. In the second part, we provide a deterministic QPTAS for interaction graphs with bounded treewidth and with logarithmically many actions per player that can compute constrained approximate equilibria for a wide family of constraints that cover many of the constraints dealt with in the first part

A biologically inspired network design model

A network design problem is to select a subset of links in a transport network that satisfy passengers or cargo transportation demands while minimizing the overall costs of the transportation. We propose a mathematical model of the foraging behaviour of slime mould P. polycephalum to solve the network design problem and construct optimal transport networks. In our algorithm, a traffic flow between any two cities is estimated using a gravity model. The flow is imitated by the model of the slime mould. The algorithm model converges to a steady state, which represents a solution of the problem. We validate our approach on examples of major transport networks in Mexico and China. By comparing networks developed in our approach with the man-made highways, networks developed by the slime mould, and a cellular automata model inspired by slime mould, we demonstrate the flexibility and efficiency of our approach

A compound directed against S6K1 hampers fat mass expansion and mitigates diet-induced hepatosteatosis

The ribosomal protein S6 kinase 1 (S6K1) is a relevant effector downstream of the mammalian target of rapamycin complex 1 (mTORC1), best known for its role in the control of lipid homeostasis. Consistent with this, mice lacking the S6k1 gene have a defect in their ability to induce the commitment of fat precursor cells to the adipogenic lineage, which contributes to a significant reduction of fat mass. Here, we assess the therapeutic blockage of S6K1 in diet-induced obese mice challenged with LY2584702 tosylate, a specific oral S6K1 inhibitor initially developed for the treatment of solid tumors. We show that diminished S6K1 activity hampers fat mass expansion and ameliorates dyslipidemia and hepatic steatosis, while modifying transcriptome-wide gene expression programs relevant for adipose and liver function. Accordingly, decreased mTORC1 signaling in fat (but increased in the liver) segregated with defective epithelial-mesenchymal transition and the impaired expression of Cd36 (coding for a fatty acid translocase) and Lgals1 (Galectin 1) in both tissues. All these factors combined align with reduced adipocyte size and improved lipidomic signatures in the liver, while hepatic steatosis and hypertriglyceridemia were improved in treatments lasting either 3 months or 6 weeks

Biological Convergence of Cancer Signatures

Gene expression profiling has identified cancer prognostic and predictive signatures with superior performance to conventional histopathological or clinical parameters. Consequently, signatures are being incorporated into clinical practice and will soon influence everyday decisions in oncology. However, the slight overlap in the gene identity between signatures for the same cancer type or condition raises questions about their biological and clinical implications. To clarify these issues, better understanding of the molecular properties and possible interactions underlying apparently dissimilar signatures is needed. Here, we evaluated whether the signatures of 24 independent studies are related at the genome, transcriptome or proteome levels. Significant associations were consistently observed across these molecular layers, which suggest the existence of a common cancer cell phenotype. Convergence on cell proliferation and death supports the pivotal involvement of these processes in prognosis, metastasis and treatment response. In addition, functional and molecular associations were identified with the immune response in different cancer types and conditions that complement the contribution of cell proliferation and death. Examination of additional, independent, cancer datasets corroborated our observations. This study proposes a comprehensive strategy for interpreting cancer signatures that reveals common design principles and systems-level properties

Assessing associations between the AURKAHMMR-TPX2-TUBG1 functional module and breast cancer risk in BRCA1/2 mutation carriers

While interplay between BRCA1 and AURKA-RHAMM-TPX2-TUBG1 regulates mammary epithelial polarization, common genetic variation in HMMR (gene product RHAMM) may be associated with risk of breast cancer in BRCA1 mutation carriers. Following on these observations, we further assessed the link between the AURKA-HMMR-TPX2-TUBG1 functional module and risk of breast cancer in BRCA1 or BRCA2 mutation carriers. Forty-one single nucleotide polymorphisms (SNPs) were genotyped in 15,252 BRCA1 and 8,211 BRCA2 mutation carriers and subsequently analyzed using a retrospective likelihood appr