Robustness analysis of discrete predictor-based controllers for input-delay systems

In this article, robustness to model uncertainties are analysed in the context of discrete predictor-based state-feedback controllers for discrete-time input-delay systems with time-varying delay, in an LMI framework. The goal is comparing robustness of predictor-based strategies with respect to other (sub)optimal state feedback ones. A numerical example illustrates that improvements in tolerance to modelling errors can be achieved by using the predictor framework.The authors are grateful for grant nos. DPI2008-06737-C02-01, DPI2008-06731-C02-01, DPI2011-27845-C02-01 and PROMETEO/2008/088 from the Spanish and Valencian governments.González Sorribes, A.; Sala, A.; García Gil, PJ.; Albertos Pérez, P. (2013). Robustness analysis of discrete predictor-based controllers for input-delay systems. International Journal of Systems Science. 44(2):232-239. https://doi.org/10.1080/00207721.2011.600469S232239442Boukas, E.-K. (2006). 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Novel Plasmids and Resistance Phenotypes in Yersinia pestis: Unique Plasmid Inventory of Strain Java 9 Mediates High Levels of Arsenic Resistance

Growing evidence suggests that the plasmid repertoire of Yersinia pestis is not restricted to the three classical virulence plasmids. The Java 9 strain of Y. pestis is a biovar Orientalis isolate obtained from a rat in Indonesia. Although it lacks the Y. pestis-specific plasmid pMT, which encodes the F1 capsule, it retains virulence in mouse and non-human primate animal models. While comparing diverse Y. pestis strains using subtractive hybridization, we identified sequences in Java 9 that were homologous to a Y. enterocolitica strain carrying the transposon Tn2502, which is known to encode arsenic resistance. Here we demonstrate that Java 9 exhibits high levels of arsenic and arsenite resistance mediated by a novel promiscuous class II transposon, named Tn2503. Arsenic resistance was self-transmissible from Java 9 to other Y. pestis strains via conjugation. Genomic analysis of the atypical plasmid inventory of Java 9 identified pCD and pPCP plasmids of atypical size and two previously uncharacterized cryptic plasmids. Unlike the Tn2502-mediated arsenic resistance encoded on the Y. enterocolitica virulence plasmid; the resistance loci in Java 9 are found on all four indigenous plasmids, including the two novel cryptic plasmids. This unique mobilome introduces more than 105 genes into the species gene pool. The majority of these are encoded by the two entirely novel self-transmissible plasmids, which show partial homology and synteny to other enterics. In contrast to the reductive evolution in Y. pestis, this study underlines the major impact of a dynamic mobilome and lateral acquisition in the genome evolution of the plague bacterium

Seasonal influenza risk in hospital healthcare workers is more strongly associated with household than occupational exposures: results from a prospective cohort study in Berlin, Germany, 2006/07

Background: Influenza immunisation for healthcare workers is encouraged to protect their often vulnerable patients but also due to a perceived higher risk for influenza. We aimed to compare the risk of influenza infection in healthcare workers in acute hospital care with that in non-healthcare workers over the same season. Methods: We conducted a prospective, multicentre cohort study during the 2006/07 influenza season in Berlin, Germany. Recruited participants gave serum samples before and after the season, and completed questionnaires to determine their relevant exposures and possible confounding factors. The main outcome measure was serologically confirmed influenza infection (SCII), defined as a fourfold or greater rise in haemagglutination inhibition antibody titres to a circulating strain of influenza (with post-season titre at least 1:40). Weekly mobile phone text messages were used to prompt participants to report respiratory illnesses during the influenza season. A logistic regression model was used to assess the influence of potential risk factors. Results: We recruited 250 hospital healthcare workers (mean age 35.7 years) and 486 non-healthcare workers (mean age 39.2 years) from administrative centres, blood donors and colleges. Overall SCII attack rate was 10.6%. Being a healthcare worker was not a risk factor for SCII (relative risk 1.1, p=0.70). The final multivariate model had three significant factors: living with children (odds ratio [OR] 3.7, p=0.005), immunization (OR 0.50, p=0.02), and - among persons living in households without children - ownership of a car (OR 3.0, p=0.02). Living with three or more children (OR 13.8,

Identification and Functional Analysis of a Novel von Willebrand Factor Mutation in a Family with Type 2A von Willebrand Disease

von Willebrand factor (VWF) is essential for normal hemostasis. VWF gene mutations cause the hemorrhagic von Willebrand disease (VWD). In this study, a 9-year-old boy was diagnosed as type 2A VWD, based on a history of abnormal bleeding, low plasma VWF antigen and activity, low plasma factor VIII activity, and lack of plasma high-molecular-weight (HMW) VWF multimers. Sequencing analysis detected a 6-bp deletion in exon 28 of his VWF gene, which created a mutant lacking D1529V1530 residues in VWF A2 domain. This mutation also existed in his family members with abnormal bleedings but not in >60 normal controls. In transfected HEK293 cells, recombinant VWF ΔD1529V1530 protein had markedly reduced levels in the conditioned medium (42±4% of wild-type (WT) VWF, p<0.01). The mutant VWF in the medium had less HMW multimers. In contrast, the intracellular levels of the mutant VWF in the transfected cells were significantly higher than that of WT (174±29%, p<0.05), indicating intracellular retention of the mutant VWF. In co-transfection experiments, the mutant reduced WT VWF secretion from the cells. By immunofluorescence staining, the retention of the mutant VWF was identified within the endoplasmic reticulum (ER). Together, we identified a unique VWF mutation responsible for the bleeding phenotype in a patient family with type 2A VWD. The mutation impaired VWF trafficking through the ER, thereby preventing VWF secretion from the cells. Our results illustrate the diversity of VWF gene mutations, which contributes to the wide spectrum of VWD

Phytochemicals as antibiotic alternatives to promote growth and enhance host health

There are heightened concerns globally on emerging drug-resistant superbugs and the lack of new antibiotics for treating human and animal diseases. For the agricultural industry, there is an urgent need to develop strategies to replace antibiotics for food-producing animals, especially poultry and livestock. The 2nd International Symposium on Alternatives to Antibiotics was held at the World Organization for Animal Health in Paris, France, December 12-15, 2016 to discuss recent scientific developments on strategic antibiotic-free management plans, to evaluate regional differences in policies regarding the reduction of antibiotics in animal agriculture and to develop antibiotic alternatives to combat the global increase in antibiotic resistance. More than 270 participants from academia, government research institutions, regulatory agencies, and private animal industries from >25 different countries came together to discuss recent research and promising novel technologies that could provide alternatives to antibiotics for use in animal health and production; assess challenges associated with their commercialization; and devise actionable strategies to facilitate the development of alternatives to antibiotic growth promoters (AGPs) without hampering animal production. The 3-day meeting consisted of four scientific sessions including vaccines, microbial products, phytochemicals, immune-related products, and innovative drugs, chemicals and enzymes, followed by the last session on regulation and funding. Each session was followed by an expert panel discussion that included industry representatives and session speakers. The session on phytochemicals included talks describing recent research achievements, with examples of successful agricultural use of various phytochemicals as antibiotic alternatives and their mode of action in major agricultural animals (poultry, swine and ruminants). Scientists from industry and academia and government research institutes shared their experience in developing and applying potential antibiotic-alternative phytochemicals commercially to reduce AGPs and to develop a sustainable animal production system in the absence of antibiotics.Fil: Lillehoj, Hyun. United States Department of Agriculture. Agricultural Research Service; ArgentinaFil: Liu, Yanhong. University of California; Estados UnidosFil: Calsamiglia, Sergio. Universitat Autònoma de Barcelona; EspañaFil: Fernandez Miyakawa, Mariano Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Patobiología; ArgentinaFil: Chi, Fang. Amlan International; Estados UnidosFil: Cravens, Ron L.. Amlan International; Estados UnidosFil: Oh, Sungtaek. United States Department of Agriculture. Agricultural Research Service; ArgentinaFil: Gay, Cyril G.. United States Department of Agriculture. Agricultural Research Service; Argentin

Translating microarray data for diagnostic testing in childhood leukaemia

BACKGROUND: Recent findings from microarray studies have raised the prospect of a standardized diagnostic gene expression platform to enhance accurate diagnosis and risk stratification in paediatric acute lymphoblastic leukaemia (ALL). However, the robustness as well as the format for such a diagnostic test remains to be determined. As a step towards clinical application of these findings, we have systematically analyzed a published ALL microarray data set using Robust Multi-array Analysis (RMA) and Random Forest (RF). METHODS: We examined published microarray data from 104 ALL patients specimens, that represent six different subgroups defined by cytogenetic features and immunophenotypes. Using the decision-tree based supervised learning algorithm Random Forest (RF), we determined a small set of genes for optimal subgroup distinction and subsequently validated their predictive power in an independent patient cohort. RESULTS: We achieved very high overall ALL subgroup prediction accuracies of about 98%, and were able to verify the robustness of these genes in an independent panel of 68 specimens obtained from a different institution and processed in a different laboratory. Our study established that the selection of discriminating genes is strongly dependent on the analysis method. This may have profound implications for clinical use, particularly when the classifier is reduced to a small set of genes. We have demonstrated that as few as 26 genes yield accurate class prediction and importantly, almost 70% of these genes have not been previously identified as essential for class distinction of the six ALL subgroups. CONCLUSION: Our finding supports the feasibility of qRT-PCR technology for standardized diagnostic testing in paediatric ALL and should, in conjunction with conventional cytogenetics lead to a more accurate classification of the disease. In addition, we have demonstrated that microarray findings from one study can be confirmed in an independent study, using an entirely independent patient cohort and with microarray experiments being performed by a different research team

In vivo biomolecular imaging of zebrafish embryos using confocal Raman spectroscopy

Zebrafish embryos provide a unique opportunity to visualize complex biological processes, yet conventional imaging modalities are unable to access intricate biomolecular information without compromising the integrity of the embryos. Here, we report the use of confocal Raman spectroscopic imaging for the visualization and multivariate analysis of biomolecular information extracted from unlabeled zebrafish embryos. We outline broad applications of this method in: (i) visualizing the biomolecular distribution of whole embryos in three dimensions, (ii) resolving anatomical features at subcellular spatial resolution, (iii) biomolecular profiling and discrimination of wild type and ΔRD1 mutant Mycobacterium marinum strains in a zebrafish embryo model of tuberculosis and (iv) in vivo temporal monitoring of the wound response in living zebrafish embryos. Overall, this study demonstrates the application of confocal Raman spectroscopic imaging for the comparative bimolecular analysis of fully intact and living zebrafish embryos

Protist-Type Lysozymes of the Nematode Caenorhabditis elegans Contribute to Resistance against Pathogenic Bacillus thuringiensis

Pathogens represent a universal threat to other living organisms. Most organisms express antimicrobial proteins and peptides, such as lysozymes, as a protection against these challenges. The nematode Caenorhabditis elegans harbours 15 phylogenetically diverse lysozyme genes, belonging to two distinct types, the protist- or Entamoeba-type (lys genes) and the invertebrate-type (ilys genes) lysozymes. In the present study we characterized the role of several protist-type lysozyme genes in defence against a nematocidal strain of the Gram-positive bacterium Bacillus thuringiensis. Based on microarray and subsequent qRT-PCR gene expression analysis, we identified protist-type lysozyme genes as one of the differentially transcribed gene classes after infection. A functional genetic analysis was performed for three of these genes, each belonging to a distinct evolutionary lineage within the protist-type lysozymes (lys-2, lys-5, and lys-7). Their knock-out led to decreased pathogen resistance in all three cases, while an increase in resistance was observed when two out of three tested genes were overexpressed in transgenic lines (lys-5, lys-7, but not lys-2). We conclude that the lysozyme genes lys-5, lys-7, and possibly lys-2 contribute to resistance against B. thuringiensis, thus highlighting the particular role of lysozymes in the nematode's defence against pathogens

Human Mena Associates with Rac1 Small GTPase in Glioblastoma Cell Lines

Mammarian enabled (Mena), a member of the Enabled (Ena)/Vasodilator-stimulated phosphoprotein (VASP) family of proteins, has been implicated in cell motility through regulation of the actin cytoskeleton assembly, including lamellipodial protrusion. Rac1, a member of the Rho family GTPases, also plays a pivotal role in the formation of lamellipodia. Here we report that human Mena (hMena) colocalizes with Rac1 in lamellipodia, and using an unmixing assisted acceptor depletion fluorescence resonance energy transfer (u-adFRET) analysis that hMena associates with Rac1 in vivo in the glioblastoma cell line U251MG. Depletion of hMena by siRNA causes cells to be highly spread with the formation of lamellipodia. This cellular phenotype is canceled by introduction of a dominant negative form of Rac1. A Rac activity assay and FRET analysis showed that hMena knock-down cells increased the activation of Rac1 at the lamellipodia. These results suggest that hMena possesses properties which help to regulate the formation of lamellipodia through the modulation of the activity of Rac1

Google Goes Cancer: Improving Outcome Prediction for Cancer Patients by Network-Based Ranking of Marker Genes

Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice