Generalized Newton's Method based on Graphical Derivatives

This paper concerns developing a numerical method of the Newton type to solve systems of nonlinear equations described by nonsmooth continuous functions. We propose and justify a new generalized Newton algorithm based on graphical derivatives, which have never been used to derive a Newton-type method for solving nonsmooth equations. Based on advanced techniques of variational analysis and generalized differentiation, we establish the well-posedness of the algorithm, its local superlinear convergence, and its global convergence of the Kantorovich type. Our convergence results hold with no semismoothness assumption, which is illustrated by examples. The algorithm and main results obtained in the paper are compared with well-recognized semismooth and $B$-differentiable versions of Newton's method for nonsmooth Lipschitzian equations

Early epigenetic downregulation of microRNA-192 expression promotes pancreatic cancer progression

Pancreatic ductal adenocarcinoma (PDAC) is characterized by very early metastasis, suggesting the hypothesis that metastasis-associated changes may occur prior to actual tumor formation. In this study, we identified miR-192 as an epigenetically regulated suppressor gene with predictive value in this disease. miR-192 was downregulated by promoter methylation in both PDAC and chronic pancreatitis, the latter of which is a major risk factor for the development of PDAC. Functional studies in vitro and in vivo in mouse models of PDAC showed that overexpression of miR-192 was sufficient to reduce cell proliferation and invasion. Mechanistic analyses correlated changes in miR-192 promoter methylation and expression with epithelial–mesenchymal transition. Cell proliferation and invasion were linked to altered expression of the miR-192 target gene SERPINE1 that is encoding the protein plasminogen activator inhibitor-1 (PAI-1), an established regulator of these properties in PDAC cells. Notably, our data suggested that invasive capacity was altered even before neoplastic transformation occurred, as triggered by miR-192 downregulation. Overall, our results highlighted a role for miR-192 in explaining the early metastatic behavior of PDAC and suggested its relevance as a target to develop for early diagnostics and therapy. Cancer Res; 76(14); 4149–59. ©2016 AACR

Chemical contrast in STM imaging of transition metal aluminides

The present manuscript reviews recent scanning tunnelling microscopy (STM) studies of transition metal (TM) aluminide surfaces. It provides a general perspective on the contrast between Al atoms and TM atoms in STM imaging. A general trend is the much stronger bias dependence of TM atoms, or TM-rich regions of the surface. This dependence can be attenuated by the local chemical arrangements and environments. Al atoms can show a stronger bias dependence when their chemical environment, such as their immediate subsurface, is populated with TM. All this is well explained in light of combined results of STM and both theoretical and experimental electronic and crystallographic structure determinations. Since STM probes the Fermi surface, the electronic structure in the vicinity of the Fermi level (EF) is essential forunderstanding contrast and bias dependence. Hence, partial density of states provides information about the TM d band position and width, s–p–d hybridization or interactions, or charge transfer between constituent elements. In addition, recent developments in STM image simulations are very interesting for elucidating chemical contrast at Al–TM alloy surfaces, and allow direct atomic identification, when the surface does not show too much disorder. Overall, we show that chemically-specific imaging is often possible at these surfaces

DNA Methylation of the ABO Promoter Underlies Loss of ABO Allelic Expression in a Significant Proportion of Leukemic Patients

Background: Loss of A, B and H antigens from the red blood cells of patients with myeloid malignancies is a frequent occurrence. Previously, we have reported alterations in ABH antigens on the red blood cells of 55% of patients with myeloid malignancies. Methodology/Principal Findings: To determine the underlying molecular mechanisms of this loss, we assessed ABO allelic expression in 21 patients with ABH antigen loss previously identified by flow cytometric analysis as well as an additional 7 patients detected with ABH antigen changes by serology. When assessing ABO mRNA allelic expression, 6/12 (50%) patients with ABH antigen loss detected by flow cytometry and 5/7 (71%) of the patients with ABH antigen loss detected by serology had a corresponding ABO mRNA allelic loss of expression. We examined the ABO locus for copy number and DNA methylation alterations in 21 patients, 11 with loss of expression of one or both ABO alleles, and 10 patients with no detectable allelic loss of ABO mRNA expression. No loss of heterozygosity (LOH) at the ABO locus was observed in these patients. However in 8/11 (73%) patients with loss of ABO allelic expression, the ABO promoter was methylated compared with 2/10 (20%) of patients with no ABO allelic expression loss (P = 0.03). Conclusions/Significance: We have found that loss of ABH antigens in patients with hematological malignancies is associated with a corresponding loss of ABO allelic expression in a significant proportion of patients. Loss of ABO allelic expression was strongly associated with DNA methylation of the ABO promoter.Tina Bianco-Miotto, Damian J. Hussey, Tanya K. Day, Denise S. O'Keefe and Alexander Dobrovi

Heat transfer in separated flows on the pressure side of turbine blades

Heat transfer in separated flows on the pressure side of a typical high lift turbine profile is numerically investigated by means of an in-house CFD code. The numerical code was first validated on attached flows in turbine blades. To obtain flow separation cases, the profile is subject to large negative incidences so that a separation bubble is obtained at the pressure side. The numerical results are compared to available experimental data for code validation. It is shown how local minima and maxima values of the heat transfer coefficient are related to the separation and reattachment points, where the velocity component perpendicular to the wall is shown to have a significant effect on the heat transfe

Representative Proteomes: A Stable, Scalable and Unbiased Proteome Set for Sequence Analysis and Functional Annotation

The accelerating growth in the number of protein sequences taxes both the computational and manual resources needed to analyze them. One approach to dealing with this problem is to minimize the number of proteins subjected to such analysis in a way that minimizes loss of information. To this end we have developed a set of Representative Proteomes (RPs), each selected from a Representative Proteome Group (RPG) containing similar proteomes calculated based on co-membership in UniRef50 clusters. A Representative Proteome is the proteome that can best represent all the proteomes in its group in terms of the majority of the sequence space and information. RPs at 75%, 55%, 35% and 15% co-membership threshold (CMT) are provided to allow users to decrease or increase the granularity of the sequence space based on their requirements. We find that a CMT of 55% (RP55) most closely follows standard taxonomic classifications. Further analysis of this set reveals that sequence space is reduced by more than 80% relative to UniProtKB, while retaining both sequence diversity (over 95% of InterPro domains) and annotation information (93% of experimentally characterized proteins). All sets can be browsed and are available for sequence similarity searches and download at http://www.proteininformationresource.org/rps, while the set of 637 RPs determined using a 55% CMT are also available for text searches. Potential applications include sequence similarity searches, protein classification and targeted protein annotation and characterization

Structural Alterations from Multiple Displacement Amplification of a Human Genome Revealed by Mate-Pair Sequencing

Comprehensive identification of the acquired mutations that cause common cancers will require genomic analyses of large sets of tumor samples. Typically, the tissue material available from tumor specimens is limited, which creates a demand for accurate template amplification. We therefore evaluated whether phi29-mediated whole genome amplification introduces false positive structural mutations by massive mate-pair sequencing of a normal human genome before and after such amplification. Multiple displacement amplification led to a decrease in clone coverage and an increase by two orders of magnitude in the prevalence of inversions, but did not increase the prevalence of translocations. While multiple strand displacement amplification may find uses in translocation analyses, it is likely that alternative amplification strategies need to be developed to meet the demands of cancer genomics

Deterministic Classifiers Accuracy Optimization for Cancer Microarray Data

The objective of this study was to improve classification accuracy in cancer microarray gene expression data using a collection of machine learning algorithms available in WEKA. State of the art deterministic classification methods, such as: Kernel Logistic Regression, Support Vector Machine, Stochastic Gradient Descent and Logistic Model Trees were applied on publicly available cancer microarray datasets aiming to discover regularities that provide insights to help characterization and diagnosis correctness on each cancer typology. The implemented models, relying on 10-fold cross-validation, parameterized to enhance accuracy, reached accuracy above 90%. Moreover, although the variety of methodologies, no significant statistic differences were registered between them, at significance level 0.05, confirming that all the selected methods are effective for this type of analysis.info:eu-repo/semantics/publishedVersio

Gene Expression Patterns of Oxidative Phosphorylation Complex I Subunits Are Organized in Clusters

After the radiation of eukaryotes, the NUO operon, controlling the transcription of the NADH dehydrogenase complex of the oxidative phosphorylation system (OXPHOS complex I), was broken down and genes encoding this protein complex were dispersed across the nuclear genome. Seven genes, however, were retained in the genome of the mitochondrion, the ancient symbiote of eukaryotes. This division, in combination with the three-fold increase in subunit number from bacteria (N = ∼14) to man (N = 45), renders the transcription regulation of OXPHOS complex I a challenge. Recently bioinformatics analysis of the promoter regions of all OXPHOS genes in mammals supported patterns of co-regulation, suggesting that natural selection favored a mechanism facilitating the transcriptional regulatory control of genes encoding subunits of these large protein complexes. Here, using real time PCR of mitochondrial (mtDNA)- and nuclear DNA (nDNA)-encoded transcripts in a panel of 13 different human tissues, we show that the expression pattern of OXPHOS complex I genes is regulated in several clusters. Firstly, all mtDNA-encoded complex I subunits (N = 7) share a similar expression pattern, distinct from all tested nDNA-encoded subunits (N = 10). Secondly, two sub-clusters of nDNA-encoded transcripts with significantly different expression patterns were observed. Thirdly, the expression patterns of two nDNA-encoded genes, NDUFA4 and NDUFA5, notably diverged from the rest of the nDNA-encoded subunits, suggesting a certain degree of tissue specificity. Finally, the expression pattern of the mtDNA-encoded ND4L gene diverged from the rest of the tested mtDNA-encoded transcripts that are regulated by the same promoter, consistent with post-transcriptional regulation. These findings suggest, for the first time, that the regulation of complex I subunits expression in humans is complex rather than reflecting global co-regulation