Factors influencing peak expiratory flow in teenage boys

Background. Peak expiratory flow (PEF) is a useful measure of pulmonary health status and is frequently utilised in asthm, management. Reduction in PEF is usually indicative of OIlS( of asthma symptoms. However, use can be made of PEF values only if normal values are known. The definition of normal range is always difficult and may vary between regions and be affected by a variety of factors.Objective. To establish PEF values for teenage boys in a Cape Town suburb and examine factors that possibly influence this measurement.Setting. A high school for boys in the southern suburbs of Cape Town.Methods. Measurements of PEF were taken for 124 boys. Subjects were approximately 16 years old and apparently healthy at the time of survey. Further details were provid by means of a questionnaire.Results. PEF ranged from 350 to 760 1/min, with a mean (± standard deviation (SD» of 539 ± 681/min. Factors expected to influence PEF included height and mass, where is unexpected factors included sport intensity and academic grade. A trend to reduced peak flow was already evident in boys who smoked and boys from homes where a parent smoked. Regression analysis suggested peak flow differenct.s in our population compared with the standard reference.Conclusion. Interpretation of results obtained from peak-flow instruments should take into account additional knowledge concerning the individual. Further surveys of the South African population and of different groups should be done to establish local standards and factors influencing PE

Application of regulatory sequence analysis and metabolic network analysis to the interpretation of gene expression data

We present two complementary approaches for the interpretation of clusters of co-regulated genes, such as those obtained from DNA chips and related methods. Starting from a cluster of genes with similar expression profiles, two basic questions can be asked: 1. Which mechanism is responsible for the coordinated transcriptional response of the genes? This question is approached by extracting motifs that are shared between the upstream sequences of these genes. The motifs extracted are putative cis-acting regulatory elements. 2. What is the physiological meaning for the cell to express together these genes? One way to answer the question is to search for potential metabolic pathways that could be catalyzed by the products of the genes. This can be done by selecting the genes from the cluster that code for enzymes, and trying to assemble the catalyzed reactions to form metabolic pathways. We present tools to answer these two questions, and we illustrate their use with selected examples in the yeast Saccharomyces cerevisiae. The tools are available on the web (http://ucmb.ulb.ac.be/bioinformatics/rsa-tools/; http://www.ebi.ac.uk/research/pfbp/; http://www.soi.city.ac.uk/~msch/)

RSAT 2011: regulatory sequence analysis tools

RSAT (Regulatory Sequence Analysis Tools) comprises a wide collection of modular tools for the detection of cis-regulatory elements in genome sequences. Thirteen new programs have been added to the 30 described in the 2008 NAR Web Software Issue, including an automated sequence retrieval from EnsEMBL (retrieve-ensembl-seq), two novel motif discovery algorithms (oligo-diff and info-gibbs), a 100-times faster version of matrix-scan enabling the scanning of genome-scale sequence sets, and a series of facilities for random model generation and statistical evaluation (random-genome-fragments, random-motifs, random-sites, implant-sites, sequence-probability, permute-matrix). Our most recent work also focused on motif comparison (compare-matrices) and evaluation of motif quality (matrix-quality) by combining theoretical and empirical measures to assess the predictive capability of position-specific scoring matrices. To process large collections of peak sequences obtained from ChIP-seq or related technologies, RSAT provides a new program (peak-motifs) that combines several efficient motif discovery algorithms to predict transcription factor binding motifs, match them against motif databases and predict their binding sites. Availability (web site, stand-alone programs and SOAP/WSDL (Simple Object Access Protocol/Web Services Description Language) web services): http://rsat.ulb.ac.be/rsat/

Glutamine synthetase sequence evolution in the mycobacteria and their use as molecular markers for Actinobacteria speciation

<p>Abstract</p> <p>Background</p> <p>Although the gene encoding for glutamine synthetase (<it>gln</it>A) is essential in several organisms, multiple glnA copies have been identified in bacterial genomes such as those of the phylum <it>Actinobacteria</it>, notably the mycobacterial species. Intriguingly, previous reports have shown that only one copy (<it>gln</it>A1) is essential for growth in <it>M. tuberculosis</it>, while the other copies (<it>gln</it>A2, <it>gln</it>A3 and <it>gln</it>A4) are not.</p> <p>Results</p> <p>In this report it is shown that the <it>gln</it>A1 and <it>gln</it>A2 encoded glutamine synthetase sequences were inherited from an <it>Actinobacteria </it>ancestor, while the <it>gln</it>A4 and <it>gln</it>A3 encoded GS sequences were sequentially acquired during <it>Actinobacteria </it>speciation. The glutamine synthetase sequences encoded by <it>gln</it>A4 and <it>gln</it>A3 are undergoing reductive evolution in the mycobacteria, whilst those encoded by <it>gln</it>A1 and <it>gln</it>A2 are more conserved.</p> <p>Conclusion</p> <p>Different selective pressures by the ecological niche that the organisms occupy may influence the sequence evolution of <it>gln</it>A1 and <it>gln</it>A2 and thereby affecting phylogenies based on the protein sequences they encode. The findings in this report may impact the use of similar sequences as molecular markers, as well as shed some light on the evolution of glutamine synthetase in the mycobacteria.</p

Incidence of heat-labile enterotoxin-producing Escherichia coli detected by means of polymerase chain reaction amplification

CITATION: Winterbach, R. et al. 1994. Incidence of heat-labile enterotoxin-producing Escherichia coli detected by means of polymerase chain reaction amplification. South African Medical Journal, 84:85-87.The original publication is available at http://www.samj.org.zaDiarrhoea can be caused by many different organisms, some of which are notoriously difficult to identify. One of these is enterotoxin-producing Escherichia coli. Recently a new diagnostic technique that uses polymerase chain reaction DNA amplification was developed for detection of the 'A' subunit of the labile enterotoxin-producing E. coli gene. This technique was used to evaluate the incidence of heat-labile (LT+) enterotoxin-producing E. coli in the causation of diarrhoea. The results from this study showed that LT+ E. coli is a cause of diarrhoea in the western Cape and that 5,3% of non-diagnosed diarrhoea patients in Tygerberg Hospital were infected with this pathogen. This represented less than 1% of the total number of cases of diarrhoea investigated in this hospital. The peak coincides with the wetter months in this locality and the infection rate is lower than that reported in most other countries. Given the low incidence of occurrence of this organism we do not recommend routine implementation of the diagnostic procedure. However, this test may be useful at times, e.g. to ascertain the source of a diarrhoea epidemic.Publisher’s versio

Evidence of the dominant production mechanism of ammonia in a hydrogen plasma with parts per million of nitrogen

Absolute ground state atomic hydrogen densities were measured, by the utilization of two-photon absorption laser induced fluorescence, in a low-pressure electron cyclotron resonance plasma as a function of nitrogen admixtures - 0 to 5000 ppm. At nitrogen admixtures of 1500 ppm and higher, the spectral distribution of the fluorescence changes from a single Gaussian to a double Gaussian distribution; this is due to a separate, nascent contribution arising from the photolysis of an ammonia molecule. At nitrogen admixtures of 5000 ppm, the nascent contribution becomes the dominant contribution at all investigated pressures. Thermal loading experiments were conducted by heating the chamber walls to different temperatures; this showed a decrease in the nascent contributions with increasing temperature. This is explained by considering how the temperature influences recombination coefficients, and from which, it can be stated that the Langmuir-Hinshelwood recombination mechanism is dominant over the Eley-Rideal mechanism