Transmission of Aerosolized Seasonal H1N1 Influenza A to Ferrets

Influenza virus is a major cause of morbidity and mortality worldwide, yet little quantitative understanding of transmission is available to guide evidence-based public health practice. Recent studies of influenza non-contact transmission between ferrets and guinea pigs have provided insights into the relative transmission efficiencies of pandemic and seasonal strains, but the infecting dose and subsequent contagion has not been quantified for most strains. In order to measure the aerosol infectious dose for 50% (aID50) of seronegative ferrets, seasonal influenza virus was nebulized into an exposure chamber with controlled airflow limiting inhalation to airborne particles less than 5 µm diameter. Airborne virus was collected by liquid impinger and Teflon filters during nebulization of varying doses of aerosolized virus. Since culturable virus was accurately captured on filters only up to 20 minutes, airborne viral RNA collected during 1-hour exposures was quantified by two assays, a high-throughput RT-PCR/mass spectrometry assay detecting 6 genome segments (Ibis T5000™ Biosensor system) and a standard real time RT-qPCR assay. Using the more sensitive T5000 assay, the aID50 for A/New Caledonia/20/99 (H1N1) was approximately 4 infectious virus particles under the exposure conditions used. Although seroconversion and sustained levels of viral RNA in upper airway secretions suggested established mucosal infection, viral cultures were almost always negative. Thus after inhalation, this seasonal H1N1 virus may replicate less efficiently than H3N2 virus after mucosal deposition and exhibit less contagion after aerosol exposure

Distinguishing four components underlying physical activity: a new approach to using physical activity questionnaire data in old age

<p>Abstract</p> <p>Background</p> <p>It is evident that physical activity has many benefits, but it often remains unclear which types of activity are optimal for health and functioning in old age. The aim of this methodological study was to propose a method for distinguishing four components underlying self reported physical activity of older adults: intensity, muscle strength, turning actions and mechanical strain.</p> <p>Methods</p> <p>Physical activity was assessed by the validated LAPAQ questionnaire among 1699 older adults of the Longitudinal Aging Study Amsterdam. Based on expert consultation and literature review, the four component scores for several individual daily and sports activities were developed. Factor analysis was performed to confirm whether the developed components indeed measured different constructs of physical activity.</p> <p>Results</p> <p>Based on the factor analyses, three components were distinguished: 1. intensity and muscle strength loaded on the same factor, 2. mechanical strain and 3. turning actions. Analyses in gender, age and activity level subgroups consistently distinguished three factors.</p> <p>Conclusion</p> <p>Future research using these components may contribute to our understanding of how specific daily and sports activities may have a different influence on health and physical functioning in old age.</p

GOPred: GO Molecular Function Prediction by Combined Classifiers

Functional protein annotation is an important matter for in vivo and in silico biology. Several computational methods have been proposed that make use of a wide range of features such as motifs, domains, homology, structure and physicochemical properties. There is no single method that performs best in all functional classification problems because information obtained using any of these features depends on the function to be assigned to the protein. In this study, we portray a novel approach that combines different methods to better represent protein function. First, we formulated the function annotation problem as a classification problem defined on 300 different Gene Ontology (GO) terms from molecular function aspect. We presented a method to form positive and negative training examples while taking into account the directed acyclic graph (DAG) structure and evidence codes of GO. We applied three different methods and their combinations. Results show that combining different methods improves prediction accuracy in most cases. The proposed method, GOPred, is available as an online computational annotation tool (http://kinaz.fen.bilkent.edu.tr/gopred)

Identification of Novel Mt-Guab2 Inhibitor Series Active against M. tuberculosis

Tuberculosis (TB) remains a leading cause of mortality worldwide. With the emergence of multidrug resistant TB, extensively drug resistant TB and HIV-associated TB it is imperative that new drug targets be identified. The potential of Mycobacterium tuberculosis inosine monophosphate dehydrogenase (IMPDH) as a novel drug target was explored in the present study. IMPDH exclusively catalyzes the conversion of inosine monophosphate (IMP) to xanthosine monophosphate (XMP) in the presence of the cofactor nicotinamide adenine dinucleotide (NAD+). Although the enzyme is a dehydrogenase, the enzyme does not catalyze the reverse reaction i.e. the conversion of XMP to IMP. Unlike other bacteria, M. tuberculosis harbors three IMPDH-like genes, designated as Mt-guaB1, Mt-guaB2 and Mt-guaB3 respectively. Of the three putative IMPDH's, we previously confirmed that Mt-GuaB2 was the only functional ortholog by characterizing the enzyme kinetically. Using an in silico approach based on designed scaffolds, a series of novel classes of inhibitors was identified. The inhibitors possess good activity against M. tuberculosis with MIC values in the range of 0.4 to 11.4 µg mL−1. Among the identified ligands, two inhibitors have nanomolar Kis against the Mt-GuaB2 enzyme