An Algorithm for Projecting a Reference Direction onto the Nondominated Set of Given Points

In this paper, we consider the problem of searching nondominated alternatives in a discrete multiple criteria problem. The search procedure is based on the use of a reference direction. A reference direction reflects the desire of the decision maker (DM) to specify a search direction. To find a set of given alternatives related somehow to the reference direction specified by the DM, the reference direction has to be projected onto the set of nondominated alternatives. Our purpose is to develop an efficient algorithm for making this projection. The projection of each given reference direction determines a nondominated ordered subset. The set is provided to a decision maker for evaluation. The decision maker will choose the most preferred alternative from this subset and continues the search from this alternative with a new reference direction. The search will end when no direction of of improvement is found. A critical point in the procedure is the efficiency of the projection operation. This efficiency of our algorithm is considered theoretically and numerically. The projection is made by parametrizing an achievement scalarizing function originally proposed by Wierzbicki (1980) to project any single point onto the nondominated set

A gene signature for post-infectious chronic fatigue syndrome

Background: At present, there are no clinically reliable disease markers for chronic fatigue syndrome. DNA chip microarray technology provides a method for examining the differential expression of mRNA from a large number of genes. Our hypothesis was that a gene expression signature, generated by microarray assays, could help identify genes which are dysregulated in patients with post-infectious CFS and so help identify biomarkers for the condition. Methods: Human genome-wide Affymetrix GeneChip arrays (39,000 transcripts derived from 33,000 gene sequences) were used to compare the levels of gene expression in the peripheral blood mononuclear cells of male patients with post-infectious chronic fatigue (n = 8) and male healthy control subjects (n = 7). Results: Patients and healthy subjects differed significantly in the level of expression of 366 genes. Analysis of the differentially expressed genes indicated functional implications in immune modulation, oxidative stress and apoptosis. Prototype biomarkers were identified on the basis of differential levels of gene expression and possible biological significance Conclusion: Differential expression of key genes identified in this study offer an insight into the possible mechanism of chronic fatigue following infection. The representative biomarkers identified in this research appear promising as potential biomarkers for diagnosis and treatment

The role of UDP-Glc:glycoprotein glucosyltransferase 1 in the maturation of an obligate substrate prosaposin

A natural substrate for UGT1 is confirmed, revealing how the enzyme functions in the calnexin chaperone system as a quality control step in protein folding

Respiratory viruses in children hospitalized for acute lower respiratory tract infection in Ghana

<p>Abstract</p> <p>Background</p> <p>Acute respiratory tract infections are one of the major causes of morbidity and mortality among young children in developing countries. Information on the viral aetiology of acute respiratory infections in developing countries is very limited. The study was done to identify viruses associated with acute lower respiratory tract infection among children less than 5 years.</p> <p>Method</p> <p>Nasopharyngeal samples and blood cultures were collected from children less than 5 years who have been hospitalized for acute lower respiratory tract infection. Viruses and bacteria were identified using Reverse Transcriptase Real-Time Polymerase Chain Reaction and conventional biochemical techniques.</p> <p>Results</p> <p>Out of 128 patients recruited, 33(25.88%%, 95%CI: 18.5% to 34.2%) were positive for one or more viruses. Respiratory Syncytial Virus (RSV) was detected in 18(14.1%, 95%CI: 8.5% to 21.3%) patients followed by Adenoviruses (AdV) in 13(10.2%, 95%CI: 5.5% to 16.7%), Parainfluenza (PIV type: 1, 2, 3) in 4(3.1%, 95%CI: 0.9% to 7.8%) and influenza B viruses in 1(0.8%, 95%CI: 0.0 to 4.3). Concomitant viral and bacterial co-infection occurred in two patients. There were no detectable significant differences in the clinical signs, symptoms and severity for the various pathogens isolated. A total of 61.1% (22/36) of positive viruses were detected during the rainy season and Respiratory Syncytial Virus was the most predominant.</p> <p>Conclusion</p> <p>The study has demonstrated an important burden of respiratory viruses as major causes of childhood acute respiratory infection in a tertiary health institution in Ghana. The data addresses a need for more studies on viral associated respiratory tract infection.</p

Beyond the Virus: Multidisciplinary and International Perspectives on Inequalities raised by COVID-19

This report summarises the Work-in-Progress Symposium ‘Beyond the Virus: Multidisciplinary and International Perspectives on Inequalities raised by COVID-19’. The event consisted of four panels over two days. It brought together the contributors for the forthcoming edited collection with Bristol University Press (BUP), due to be published in 2022 under the Bristol Studies in Law and Social Justice series, tentatively entitled “Beyond the Virus: Multidisciplinary and International Perspectives on Inequalities raised by COVID-19” edited by Dr Sabrina Germain and Dr Adrienne Yong at The City Law School. The presentations were based on the chapters to the edited collection by each contributor and were followed by discussions. This collection examines social inequalities brought to stark attention by the COVID-19 pandemic under three thematic strands: power and governance, gender and sexuality, and marginalised communities. This project brings together a range of international scholars from multiple disciplines (law, sociology and politics) to showcase a diversity of perspectives on these themes. The unknowns around this novel virus and the scale of the epidemic make COVID-19 and its inequalities a timely subject. Understanding each of these issues from the perspective of multiple disciplines, with law at its centre, is the first step towards tackling them concretely and achieving social justice. The thematic coherence on social inequalities from international and multidisciplinary lenses is the project’s central feature

Triad pattern algorithm for predicting strong promoter candidates in bacterial genomes

Abstract Background Bacterial promoters, which increase the efficiency of gene expression, differ from other promoters by several characteristics. This difference, not yet widely exploited in bioinformatics, looks promising for the development of relevant computational tools to search for strong promoters in bacterial genomes. Results We describe a new triad pattern algorithm that predicts strong promoter candidates in annotated bacterial genomes by matching specific patterns for the group I σ70 factors of Escherichia coli RNA polymerase. It detects promoter-specific motifs by consecutively matching three patterns, consisting of an UP-element, required for interaction with the α subunit, and then optimally-separated patterns of -35 and -10 boxes, required for interaction with the σ70 subunit of RNA polymerase. Analysis of 43 bacterial genomes revealed that the frequency of candidate sequences depends on the A+T content of the DNA under examination. The accuracy of in silico prediction was experimentally validated for the genome of a hyperthermophilic bacterium, Thermotoga maritima, by applying a cell-free expression assay using the predicted strong promoters. In this organism, the strong promoters govern genes for translation, energy metabolism, transport, cell movement, and other as-yet unidentified functions. Conclusion The triad pattern algorithm developed for predicting strong bacterial promoters is well suited for analyzing bacterial genomes with an A+T content of less than 62%. This computational tool opens new prospects for investigating global gene expression, and individual strong promoters in bacteria of medical and/or economic significance.</p

An Algorithm for Projecting a Reference Direction onto the Nondominated Set of Given Points.

In this paper, we consider the problem of searching nondominated alternatives in a discrete multiple criteria problem. The search procedure is based on the use of a reference direction. A reference direction reflects the desire of the decision maker (DM) to specify a search direction. To find a set of given alternatives related somehow to the reference direction specified by the DM, the reference direction has to be projected onto the set of nondominated alternatives. Our purpose is to develop an efficient algorithm for making this projection. The projection of each given reference direction determines a nondominated ordered subset. The set is provided to a decision maker for evaluation. The decision maker will choose the most preferred alternative from this subset and continues the search from this alternative with a new reference direction. The search will end when no direction of of improvement is found. A critical point in the procedure is the efficiency of the projection operation. This efficiency of our algorithm is considered theoretically and numerically. The projection is made by parametrizing an achievement scalarizing function originally proposed by Wierzbicki (1980) to project any single point onto the nondominated set.

Parallel Monte Carlo algorithms for information retrieval

In any data mining applications, automated text and text and image retrieval of information is needed. This becomes essential with the growth of the Internet and digital libraries. Our approach is based on the latent semantic indexing (LSI) and the corresponding term-by-document matrix suggested by Berry and his co-authors. Instead of using deterministic methods to find the required number of first "k" singular triplets, we propose a stochastic approach. First, we use Monte Carlo method to sample and to build much smaller size term-by-document matrix (e.g. we build k x k matrix) from where we then find the first "k" triplets using standard deterministic methods. Second, we investigate how we can reduce the problem to finding the "k"-largest eigenvalues using parallel Monte Carlo methods. We apply these methods to the initial matrix and also to the reduced one. The algorithms are running on a cluster of workstations under MPI and results of the experiments arising in textual retrieval of Web documents as well as comparison of the stochastic methods proposed are presented. (C) 2003 IMACS. Published by Elsevier Science B.V. All rights reserved