Quasi-LDU factorization of nonsingular totally nonpositive matrices

Let A = (a(ij)) is an element of R-nxn be a nonsingular totally nonpositive matrix. In this paper we describe some properties of these matrices when a(11) = 0 and obtain a characterization in terms of the quasi-LDU factorization of A, where L is a block lower triangular matrix, D is a diagonal matrix and U is a unit upper triangular matrix. (c) 2012 Elsevier Inc. All rights reserved.The authors are very grateful to the referees for their helpful suggestions. This research was supported by the Spanish DGI Grant MTM2010-18228 and the Programa de Apoyo a la Investigacion y Desarrollo (PAID-06-10) of the Universitat Politecnica de Valencia.Cantó Colomina, R.; Ricarte Benedito, B.; Urbano Salvador, AM. (2013). Quasi-LDU factorization of nonsingular totally nonpositive matrices. Linear Algebra and its Applications. 439(4):836-851. https://doi.org/10.1016/j.laa.2012.06.010S836851439

FABIOLA: Defining the Components for Constraint Optimization Problems in Big Data Environment

The optimization problems can be found in several examples within companies, such as the minimization of the production costs, the faults produced, or the maximization of customer loyalty. The resolution of them is a challenge that entails an extra effort. In addition, many of today’s enterprises are encountering the Big Data problems added to these optimization problems. Unfortunately, to tackle this challenge by medium and small companies is extremely difficult or even impossible. In this paper, we propose a framework that isolates companies from how the optimization problems are solved. More specifically, we solve optimization problems where the data is heterogeneous, distributed and of a huge volume. FABIOLA (FAst BIg cOstraint LAb) framework enables to describe the distributed and structured data used in optimization problems that can be parallelized (the variables are not shared between the various optimization problems), and obtains a solution using Constraint Programming Techniques

Obatoclax and Paclitaxel Synergistically Induce Apoptosis and Overcome Paclitaxel Resistance in Urothelial Cancer Cells

Paclitaxel is a treatment option for advanced or metastatic bladder cancer after the failure of first-line cisplatin and gemcitabine, although resistance limits its clinical benefits. Mcl-1 is an anti-apoptotic protein that promotes resistance to paclitaxel in different tumors. Obatoclax, a BH3 mimetic of the Bcl-2 family of proteins, antagonizes Mcl-1 and hence may reverse paclitaxel resistance in Mcl-1-overexpressing tumors. In this study, paclitaxel-sensitive 5637 and -resistant HT1197 bladder cancer cells were treated with paclitaxel, obatoclax, or combinations of both. Apoptosis, cell cycle, and autophagy were measured by Western blot, flow cytometry, and fluorescence microscopy. Moreover, Mcl-1 expression was analyzed by immunohistochemistry in bladder carcinoma tissues. Our results confirmed that paclitaxel alone induced Mcl-1 downregulation and apoptosis in 5637, but not in HT1197 cells; however, combinations of obatoclax and paclitaxel sensitized HT1197 cells to the treatment. In obatoclax-treated 5637 and obatoclax + paclitaxel-treated HT1197 cells, the blockade of the autophagic flux correlated with apoptosis and was associated with caspase-dependent cleavage of beclin-1. Obatoclax alone delayed the cell cycle in 5637, but not in HT1197 cells, whereas combinations of both retarded the cell cycle and reduced mitotic slippage. In conclusion, obatoclax sensitizes HT1197 cells to paclitaxel-induced apoptosis through the blockade of the autophagic flux and effects on the cell cycle. Furthermore, Mcl-1 is overexpressed in many invasive bladder carcinomas, and it is related to tumor progression, so Mcl-1 expression may be of predictive value in bladder cancer.España, Sistema Público Andaluz Biobanco y ISCIII-Red de Biobancos PT17/0015/004

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.</p

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

Securing Mobile Agent Based Tele-Assistance Systems

Nowadays the scientific community is trying to design new techniques in the search for solving security problems in mobile agent technology. There are now some industry initiatives for using agents in real environments which need a solution for some of their security problems. Companies offering assistive service are getting cost reduction due to teleassistive technologies. In this paper we present a proposal based on secure tunnels to add confidentiality and integrity to any agent platform, present or future, without making any changes to its source-code. Our system is currently implemented and working as part of a complete mobile multi-agent system used for tele-assistance. During our research we have also detected many other problems regarding the tunnelling approach