Modular analysis of gene expression data with R.

SUMMARY: Large sets of data, such as expression profiles from many samples, require analytic tools to reduce their complexity. The Iterative Signature Algorithm (ISA) is a biclustering algorithm. It was designed to decompose a large set of data into so-called 'modules'. In the context of gene expression data, these modules consist of subsets of genes that exhibit a coherent expression profile only over a subset of microarray experiments. Genes and arrays may be attributed to multiple modules and the level of required coherence can be varied resulting in different 'resolutions' of the modular mapping. In this short note, we introduce two BioConductor software packages written in GNU R: The isa2 package includes an optimized implementation of the ISA and the eisa package provides a convenient interface to run the ISA, visualize its output and put the biclusters into biological context. Potential users of these packages are all R and BioConductor users dealing with tabular (e.g. gene expression) data. AVAILABILITY: http://www.unil.ch/cbg/ISA CONTACT: sven.bergmann@unil.ch

Multi-ethnic fine-mapping of 14 central adiposity loci.

The Genetic Investigation of Anthropometric Traits (GIANT) consortium identified 14 loci in European Ancestry (EA) individuals associated with waist-to-hip ratio (WHR) adjusted for body mass index. These loci are wide and narrowing the signals remains necessary. Twelve of 14 loci identified in GIANT EA samples retained strong associations with WHR in our joint EA/individuals of African Ancestry (AA) analysis (log-Bayes factor >6.1). Trans-ethnic analyses at five loci (TBX15-WARS2, LYPLAL1, ADAMTS9, LY86 and ITPR2-SSPN) substantially narrowed the signals to smaller sets of variants, some of which are in regions that have evidence of regulatory activity. By leveraging varying linkage disequilibrium structures across different populations, single-nucleotide polymorphisms (SNPs) with strong signals and narrower credible sets from trans-ethnic meta-analysis of central obesity provide more precise localizations of potential functional variants and suggest a possible regulatory role. Meta-analysis results for WHR were obtained from 77 167 EA participants from GIANT and 23 564 AA participants from the African Ancestry Anthropometry Genetics Consortium. For fine mapping we interrogated SNPs within ± 250 kb flanking regions of 14 previously reported index SNPs from loci discovered in EA populations by performing trans-ethnic meta-analysis of results from the EA and AA meta-analyses. We applied a Bayesian approach that leverages allelic heterogeneity across populations to combine meta-analysis results and aids in fine-mapping shared variants at these locations. We annotated variants using information from the ENCODE Consortium and Roadmap Epigenomics Project to prioritize variants for possible functionality.

Real-time antifungal susceptibility testing of Mucor spp., Fusarium spp. and Scedosporium spp. by isothermal microcalorimetry

Objective: Aspergillus species are the main pathogens causing invasive fungal infections but the prevalence of other mould species is rising. Resistance to antifungals among these new emerging pathogens presents a challenge for managing of infections. Conventional susceptibility testing of non-Aspergillus species is laborious and often difficult to interpret. We evaluated a new method for real-time susceptibility testing of moulds based on their of growth-related heat production.Methods: Laboratory and clinical strains of Mucor spp. (n = 4), Scedoporium spp. (n = 4) and Fusarium spp. (n = 5) were used. Conventional MIC was determined by microbroth dilution. Isothermal microcalorimetry was performed at 37 C using Sabouraud dextrose broth (SDB) inoculated with 104 spores/ml (determined by microscopical enumeration). SDB without antifungals was used for evaluation of growth characteristics. Detection time was defined as heat flow exceeding 10 lW. For susceptibility testing serial dilutions of amphotericin B, voriconazole, posaconazole and caspofungin were used. The minimal heat inhibitory concentration (MHIC) was defined as the lowest antifungal concentration, inhbiting 50% of the heat produced by the growth control at 48 h or at 24 h for Mucor spp. Susceptibility tests were performed in duplicate.Results: Tested mould genera had distinctive heat flow profiles with a median detection time (range) of 3.4 h (1.9-4.1 h) for Mucor spp, 11.0 h (7.1-13.7 h) for Fusarium spp and 29.3 h (27.4-33.0 h) for Scedosporium spp. Graph shows heat flow (in duplicate) of one representative strain from each genus (dashed line marks detection limit). Species belonging to the same genus showed similar heat production profiles. Table shows MHIC and MIC ranges for tested moulds and antifungals.Conclusions: Microcalorimetry allowed rapid detection of growth of slow-growing species, such as Fusarium spp. and Scedosporium spp. Moreover, microcalorimetry offers a new approach for antifungal susceptibility testing of moulds, correlating with conventional MIC values. Interpretation of calorimetric susceptibility data is easy and real-time data on the effect of different antifungals on the growth of the moulds is additionally obtained. This method may be used for investigation of different mechanisms of action of antifungals, new substances and drug-drug combinations.

Biochemical analysis of female mice urine with reference to endocrine function: a key tool for estrus detection.

Species-specific chemical signals released through urine, sweat, saliva and feces are involved in communication between animals. Urinary biochemical constituents along with pheromones may contribute to variation across reproductive cycles and facilitate to estrus detection. Hence, the present study was designed to analyze such biochemical profiles, such as proteins, carbohydrates, lipids, fatty acids, in response with steroid hormones such as estradiol and progesterone. The experimental groups were normal, prepubertal, ovariectomized, and ovariectomized with estrogentreated female mice. In normal mice, the protein and lipid concentrations in urine were significantly higher in proestrus and estrus phases and the quantity of fatty acids was also comparatively higher in estrus. Furthermore, certain fatty acids, namely tridecanoic, palmitic and oleic acids, were present during proestrus and estrus phases, but were exclusively absent in ovariectomized mice. However, the carbohydrate level was equally maintained throughout the four phases of estrous cycle. For successful communication, higher concentrations of protein and specific fatty acids in estrus are directly involved. The significant increase in estradiol at estrus and progesterone at metestrus seems to be of greater importance in the expression pattern of biochemical constituents and may play a notable role in estrous cycle regulation. Thus, we conclude that the variations observed in the concentration of the biochemical constituents depend on the phase of the reproductive cycle as well as hormonal status of animals. The appearance of protein and specific fatty acids during estrus phase raises the possibility to use these as a urinary indicators for estrus detection.

Slime production and proteinase activity of Candida species isolated from blood samples and the comparison of these activities with minimum inhibitory concentration values of antifungal agents

Slime and proteinase activity of 54 strains consisting of 19 Candida parapsilosis and 35 C. albicans strains isolated from blood samples were investigated in this study. Ketoconazole, amphothericin B, and fluconazole susceptibility of Candida species were compared with slime production and proteinase activity of these species. For both Candida species, no correlation was detected between the slime activity and minimum inhibitory concentration (MIC) values of the three antifungal agents. For both Candida species no correlation was detected between the proteinase activity and the MIC values of amphothericin B, and fluconazole however, statistically significant difference, was determined between the proteinase activity and MIC values of ketoconazole (p = 0.007). Slime production was determined by using modified Christensen macrotube method and proteinase activity was measured by the method of Staib. Antifungal susceptibility was determined through the guidelines of National Committee for Laboratory Standards (NCCLS M27-A).

A Rapid Mapping Study of Smoking Projects and Services Targeted at People Living on Low Income and/or Minority Ethnic Groups

This is a study concerned with community based services aimed at smokers living on a low income and/or black and minority ethnic groups.

Health Profiles for the East of England

A collection of Health Profiles for the East of England

2008 Health Inequalities Profiles: Data sources

Links to data sources and methods as used in the production of erpho's 2008 Health Inequalities Profiles. This year's profiles cover the same indicators as previous profiles. Changes since last year:> A fifth time period: 2005-07> Updated populations > IMD 2007> Standardised against European Standard Population> Added comparator area 'All but most deprived' (80/20)

Health Inequality Profiles 2008 - MSOA level data (v2)

Using mortality and population data from 2001 to 2007 DSRs and life expectancy were calculated for all Middle Layer Super Output Areas in the East of England.

Health Inequality Profiles 2008 - All age, all cause standardised vs. EoE

DSRs (with CIs) for All age, all cause mortality 2001-03 to 2005-07, by gender, for Counties/UAs, County quintiles, County 80/20 standardises - as in previous years - against East of England Census 2001 population.

Mapping health inequalities across London

Analysis of infant mortality and life expectancy across London by various dimensions of inequality- socioeconomic; gender; geographical, and trends

Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale: some case studies

Every year, debris flows cause huge damage in mountainous areas. Due to population pressure in hazardous zones, the socio-economic impact is much higher than in the past. Therefore, the development of indicative susceptibility hazard maps is of primary importance, particularly in developing countries. However, the complexity of the phenomenon and the variability of local controlling factors limit the use of processbased models for a first assessment. A debris flow model has been developed for regional susceptibility assessments using digital elevation model (DEM) with a GIS-based approach.. The automatic identification of source areas and the estimation of debris flow spreading, based on GIS tools, provide a substantial basis for a preliminary susceptibility assessment at a regional scale. One of the main advantages of this model is its workability. In fact, everything is open to the user, from the data choice to the selection of the algorithms and their parameters. The Flow-R model was tested in three different contexts: two in Switzerland and one in Pakistan, for indicative susceptibility hazard mapping. It was shown that the quality of the DEM is the most important parameter to obtain reliable results for propagation, but also to identify the potential debris flows sources.

Low plasma lactate concentration as a biomarker of an incompetent brain-pull: a risk factor for weight gain in type 2 diabetes patients.

OBJECTIVE: Body weight development is closely regulated by central nervous mechanisms. As has been demonstrated recently, the capability of the brain to actively demand energy from the body (brain-pull) is indispensable for the maintenance of systemic homeostasis. A deficit in this brain-pull may result in compensatory ingestive behavior followed by weight gain in the medium or long term. The aim of this study was to establish a biomarker of such an incompetent brain-pull. Since lactate is an alternative cerebral energy substrate to glucose, we investigated whether low fasting plasma lactate concentrations are associated with weight gain and increased feelings of hunger in patients with type 2 diabetes over a 3-year period. METHODS: In a population based cohort study 134 type 2 diabetes patients were examined at baseline and 3-year follow-up. Plasma lactate concentrations and additional hormones associated with food intake such as e.g. insulin, or leptin, as well as psychological variables like hunger feelings before and after a standardized breakfast were measured. The relation between fasting plasma lactate concentrations and postprandial hunger as well as follow-up weight was analyzed. RESULTS: Low fasting plasma lactate concentrations predicted a higher 3-year follow-up weight (B=-1.268, SE=0.625, p=0.04). Moreover, low fasting plasma lactate concentrations were associated with more pronounced feelings of postprandial hunger (B=-0.406, SE=0.137, p<0.01). CONCLUSIONS: We conclude that low plasma lactate concentrations may represent a biomarker of an incompetent brain-pull, which is associated with weight gain and increased postprandial hunger in patients with type 2 diabetes mellitus. These results are in line with the view that plasma lactate can be used by the brain as an alternative energy substrate and thereby to some extent prevent overeating and obesity.