Relation between early life socioeconomic position and all cause mortality in two generations. A longitudinal study of Danish men born in 1953 and their parents

Objective: To examine (1) the relation between parental socioeconomic position and all cause mortality in two generations, (2) the relative importance of mother’s educational status and father’s occupational status on offspring mortality, and (3) the effect of factors in the family environment on these relations. Design: A longitudinal study with record linkage to the Civil Registration System. The data were analysed using Cox regression models. Setting: Copenhagen, Denmark. Subjects: 2890 men born in 1953, whose mothers were interviewed regarding family social background in 1968. The vital status of this population and their parents was ascertained from April 1968 to January 2002. Main outcome measures: All cause mortality in study participants, their mothers, and fathers. Results: A similar pattern of relations was found between parental social position and all cause mortality in adult life in the three triads of father, mother, and offspring constituted of the cohort of men born in 1953, their parents, and grandparents. The educational status of mothers showed no independent effect on total mortality when father’s occupational social class was included in the model in either of the triads. Low material wealth was the indicator that remained significantly associated with adult all cause mortality in a model also including parental social position and the intellectual climate of the family in 1968. In the men born in 1953 the influence of material wealth was strongest for deaths later in adult life. Conclusion: Father’s occupational social class is associated with adult mortality in all members of the mother-father-offspring triad. Material wealth seems to be an explanatory factor for this association

Dimensionpudotusmenetelmiä fMRI-analyysissä ja visualisoinnissa

The need to model and understand high-dimensional, noisy data sets is common in many domains these day, among them neuroimaging and fMRI analysis. Dimensionality reduction and variable selection are two common strategies for dealing with high-dimensional data, either as a pre-processing step prior to further analysis, or as an analysis step itself. This thesis discusses both dimensionality reduction and variable selection, with a focus on fMRI analysis, visualization, and applications of visualization in fMRI analysis. Three new algorithms are introduced. The first algorithm uses a sparse Canonical Correlation Analysis model and a high-dimensional stimulus representation to find relevant voxels (variables) in fMRI experiments with complex natural stimuli. Experiments on a data set involving music show that the algorithm successfully retrieves voxels relevant to the experimental condition. The second algorithm, NeRV, is a dimensionality reduction method for visualization high-dimensional data using scatterplots. A simple abstract model of the way a human studies a scatterplot is formulated, and NeRV is derived as an algorithm for producing optimal visualizations in terms of this model. Experiments show that NeRV is superior to conventional dimensionality reduction methods in terms of this model. NeRV is also used to perform a novel form of exploratory data analysis on the fMRI voxels selected by the first algorithm; the analysis simultaneously demonstrates the usefulness of NeRV in practice and offers further insights into the performance of the voxel selection algorithm. The third algorithm, LDA-NeRV, combines a Bayesian latent-variable model for graphs with NeRV to produce one of the first principled graph drawing methods. Experiments show that LDA-NeRV is capable of visualizing structure that conventional graph drawing methods fail to reveal.Monilla aloilla esiintyy tarve korkeaulotteisen, kohinaisen datan analysoimiseen. Algorithminen dimensionpudotus tai muuttujanvalinta ovat usein sovellettavia lähestymistapoja, joko muuta analyysiä edeltävänä esikäsittelynä tai itsenäisenä analyysinä. Tässä työssä käsitellään sekä dimensionpudotusta että muuttujanvalintaa, keskittyen erityisesti fMRI-dataaan ja visualisointiin. Työssä esitellään kolme uutta algoritmia. Ensimmäinen algoritmi käyttää harvaa kanonista korrelaaioanalyysi-mallia (CCA) ja koeärsykkeen korkeaulotteista piirre-esitystä olennaisten vokseleiden (muuttujien) valitsemiseen fMRI-kokeissa, joissa koehenkilöt altistetaan monimutkaiselle luonnolliselle ärsykkeelle, kuten esimerkiksi musiikille. Kokeet musiikkia ärsykkeenä käyttävän fMRI-kokeen kanssa osoittavat algoritmin löytävän tärkeitä vokseleita. Toinen algoritmi, NeRV, on dimensionpudotusmenetelmä korkeaulotteisen datan visualisoimiseen hajontakuvion avulla. NeRV pohjautuu yksinkertaiseen abstraktiin malliin ihmisen tavalle tulkita hajontakuviota. Kokeet osoittavat NeRVin olevan perinteisiä menetelmiä parempi tämän visualisointimallin mielessä. Lisäksi NeRViä sovelletaan ensimmäisen algoritmin valitsemien fMRI-vokseleiden visuaaliseen analyysiin; analyysi sekä osoittaa NeRVin hyödyllisyyden käytännössä että tarjoaa uusia näkökulmia vokselinvalintatulosten ymmärtämiseen. Kolmas algoritmi, LDA-NeRV, on NeRViä ja bayesiläistä latenttimuuttujamallia soveltava visualisointimenetelmä graafeille. Kokeet osoittavat LDA-NeRVin kykenevän visualisoimaan rakennetta, jota perinteiset visualisointimenetelmät eivät tuo esiin

Ticks and Lyme Disease

A report prepared by Maine Department of Transportation on ticks and lyme disease.https://digitalcommons.usm.maine.edu/mdot-docs/1002/thumbnail.jp

ISOLATION AND ELUCIDATION OF THE CHRYSOMYCIN BIOSYNTHETIC GENE CLUSTER AND ALTERING THE GLYCOSYLATION PATTERNS OF TETRACENOMYCINS AND MITHRAMYCIN-PATHWAY MOLECULES

Natural products occupy a central role as the majority of currently used antibiotic and anticancer agents. Among these are type-II polyketide synthase (PKS)-derived molecules, or polyketides, which are produced by many representatives of the genus Streptomyces. Some type-II polyketides, such as the tetracyclines and the anthracycline doxorubicin, are currently employed as therapeutics. However, several polyketide molecules exhibit promising biological activity, but due to toxic side effects or solubility concerns, remain undeveloped as drugs. Gilvocarcin V (GV) (topoisomerase II inhibitor) has a novel mechanism of action: [2+2] cycloaddition to thymine residues by the 8-vinyl side chain and cross-linking of histone H. Mithramycin blocks transcription of proto-oncogenes c-myc and c-src by forming an Mg2+-coordinated homodimer in the GC-rich minor groove of DNA. The purpose of this research was to investigate the biosynthesis of several type II polyketide compounds (e.g. chrysomycin, elloramycin, and mithramycin) with the goal of improving the bioactivities of these drugs through combinatorial biosynthesis. Alteration of the glycosylation pattern of these molecules is one promising way to improve or alter the bioactivities of these molecules. To this end, an understanding of the glycosyltransferases and post-polyketide tailoring enzymatic steps involved in these biosynthetic pathways must be established. Four specific aims were established to meet these goals. In specific aim 1, the biosynthetic locus of chrysomycin A was successfully cloned and elucidated, which afforded novel biosynthetic tools. Chrysomycin monooxygenases were found to catalyze identical roles to their gilvocarcin counterparts. Cloning of deoxysugar constructs (plasmids) which could direct biosynthesis of ketosugars, NDP-D-virenose, and NDP-D-fucofuranose in foreign pathways was undertaken in specific aim 2. Finally, these “sugar” plasmids were introduced into producer organisms of elloramycin and mithramycin pathways in specific aims 3 and 4 to interrogate the endogenous glycosyltransferases in order to alter their glycosylation patterns. These experiments resulted in the successful generation of a newly glycosylated tetracenomycin, as well as premithramycin, and mithramycin analogues. In specific aim 4, a new mithramycin analogue with an altered sugar pattern rationally designed and improved structural features was generated and structurally elucidated

Wheatland Conservation Area Inc. – project results from the dry Brown Soil Zone

Non-Peer ReviewedThe Wheatland Conservation Area Inc. manages and operates the brown soil zone Agri-ARM program in southwest Saskatchewan. Our non-profit organization conducts producer driven applied research and extension. The majority of the work done is large plot, replicated studies using field scale equipment. Small plot replicated studies are done to a lesser extent, as well as a few non-replicated demonstrations. Results are extended to producers at tours, workshops, and trade shows, as well as by newsletters, fact sheets, and a weekly radio segment called “Walk the Plots”. Partnerships with government and non-government organizations, as well as industry, and producers are a large part of our overall success. Since we are the only site in the dry Brown Soil Zone we run satellite sites throughout the south west in addition to the main site at Swift Current. This is to insure a wider audience and increased adoption rates by producers in the south west. These sites are located near Assiniboia, Frontier, Aneroid, and Success. Small, single study sites are also located in the area. Approximately forty trials are conducted annually involving pulse crops, forages, oilseeds, cereals, cereal recrops, and many others