Impact of HSD11B1 polymorphisms on BMI and components of the metabolic syndrome in patients receiving psychotropic treatments.

BACKGROUND: Metabolic syndrome (MetS) associated with psychiatric disorders and psychotropic treatments represents a major health issue. 11β-Hydroxysteroid dehydrogenase type 1 (11β-HSD1) is an enzyme that catalyzes tissue regeneration of active cortisol from cortisone. Elevated enzymatic activity of 11β-HSD1 may lead to the development of MetS. METHODS: We investigated the association between seven HSD11B1 gene (encoding 11β-HSD1) polymorphisms and BMI and MetS components in a psychiatric sample treated with potential weight gain-inducing psychotropic drugs (n=478). The polymorphisms that survived Bonferroni correction were analyzed in two independent psychiatric samples (nR1=168, nR2=188) and in several large population-based samples (n1=5338; n2=123 865; n3>100 000). RESULTS: HSD11B1 rs846910-A, rs375319-A, and rs4844488-G allele carriers were found to be associated with lower BMI, waist circumference, and diastolic blood pressure compared with the reference genotype (Pcorrected<0.05). These associations were exclusively detected in women (n=257) with more than 3.1 kg/m, 7.5 cm, and 4.2 mmHg lower BMI, waist circumference, and diastolic blood pressure, respectively, in rs846910-A, rs375319-A, and rs4844488-G allele carriers compared with noncarriers (Pcorrected<0.05). Conversely, carriers of the rs846906-T allele had significantly higher waist circumference and triglycerides and lower high-density lipoprotein-cholesterol exclusively in men (Pcorrected=0.028). The rs846906-T allele was also associated with a higher risk of MetS at 3 months of follow-up (odds ratio: 3.31, 95% confidence interval: 1.53-7.17, Pcorrected=0.014). No association was observed between HSD11B1 polymorphisms and BMI and MetS components in the population-based samples. CONCLUSIONS: Our results indicate that HSD11B1 polymorphisms may contribute toward the development of MetS in psychiatric patients treated with potential weight gain-inducing psychotropic drugs, but do not play a significant role in the general population.

The interaction between Histoplasma capsulatum cell wall carbohydrates and host components: relevance in the immunomodulatory role of histoplasmosis

Histoplasma capsulatum is an intracellular fungal pathogen that causes respiratory and systemic disease by proliferating within phagocytic cells. The binding of H. capsulatum to phagocytes may be mediated by the pathogen's cell wall carbohydrates, glucans, which consist of glucose homo and hetero-polymers and whose glycosydic linkage types differ between the yeast and mycelial phases. The ±-1,3-glucan is considered relevant for H. capsulatum virulence, whereas the ²-1,3-glucan is antigenic and participates in the modulation of the host immune response. H. capsulatum cell wall components with lectin-like activity seem to interact with the host cell surface, while host membrane lectin-like receptors can recognize a particular fungal carbohydrate ligand. This review emphasizes the relevance of the main H. capsulatum and host carbohydrate-driven interactions that allow for binding and internalization of the fungal cell into phagocytes and its subsequent avoidance of intracellular elimination.

Analysis of Pleistocene paleodrainage evolution in the Po Basin (Italy) by multivariate statistical techniques

In order to obtain a high-resolution Pleistocene stratigraphy, eleven continuouslycored boreholes, 100 to 220m deep were drilled in the northern part of the PoPlain by Regione Lombardia in the last five years. Quantitative provenanceanalysis (QPA, Weltje and von Eynatten, 2004) of Pleistocene sands was carriedout by using multivariate statistical analysis (principal component analysis, PCA,and similarity analysis) on an integrated data set, including high-resolution bulkpetrography and heavy-mineral analyses on Pleistocene sands and of 250 majorand minor modern rivers draining the southern flank of the Alps from West toEast (Garzanti et al, 2004; 2006). Prior to the onset of major Alpine glaciations,metamorphic and quartzofeldspathic detritus from the Western and Central Alpswas carried from the axial belt to the Po basin longitudinally parallel to theSouthAlpine belt by a trunk river (Vezzoli and Garzanti, 2008). This scenariorapidly changed during the marine isotope stage 22 (0.87 Ma), with the onset ofthe first major Pleistocene glaciation in the Alps (Muttoni et al, 2003). PCA andsimilarity analysis from core samples show that the longitudinal trunk river at thistime was shifted southward by the rapid southward and westward progradation oftransverse alluvial river systems fed from the Central and Southern Alps.Sediments were transported southward by braided river systems as well as glacialsediments transported by Alpine valley glaciers invaded the alluvial plain.Kew words: Detrital modes; Modern sands; Provenance; Principal ComponentsAnalysis; Similarity, Canberra Distance; palaeodrainage

Coherent forecasting of multiple-decrement life tables: a test using Japanese cause of death data

Planners in public and private institutions would like coherent forecasts of the components of age-specic mortality, such as causes of death. This has been di cult toachieve because the relative values of the forecast components often fail to behave ina way that is coherent with historical experience. In addition, when the group forecasts are combined the result is often incompatible with an all-groups forecast. It hasbeen shown that cause-specic mortality forecasts are pessimistic when compared withall-cause forecasts (Wilmoth, 1995). This paper abandons the conventional approachof using log mortality rates and forecasts the density of deaths in the life table. Sincethese values obey a unit sum constraint for both conventional single-decrement life tables (only one absorbing state) and multiple-decrement tables (more than one absorbingstate), they are intrinsically relative rather than absolute values across decrements aswell as ages. Using the methods of Compositional Data Analysis pioneered by Aitchison(1986), death densities are transformed into the real space so that the full range of multivariate statistics can be applied, then back-transformed to positive values so that theunit sum constraint is honoured. The structure of the best-known, single-decrementmortality-rate forecasting model, devised by Lee and Carter (1992), is expressed incompositional form and the results from the two models are compared. The compositional model is extended to a multiple-decrement form and used to forecast mortalityby cause of death for Japan

Mixing compositions and other scales

Theory of compositional data analysis is often focused on the composition only. However in practical applications we often treat a composition together with covariableswith some other scale. This contribution systematically gathers and develop statistical tools for this situation. For instance, for the graphical display of the dependenceof a composition with a categorical variable, a colored set of ternary diagrams mightbe a good idea for a first look at the data, but it will fast hide important aspects ifthe composition has many parts, or it takes extreme values. On the other hand colored scatterplots of ilr components could not be very instructive for the analyst, if theconventional, black-box ilr is used.Thinking on terms of the Euclidean structure of the simplex, we suggest to set upappropriate projections, which on one side show the compositional geometry and on theother side are still comprehensible by a non-expert analyst, readable for all locations andscales of the data. This is e.g. done by defining special balance displays with carefully-selected axes. Following this idea, we need to systematically ask how to display, explore,describe, and test the relation to complementary or explanatory data of categorical, real,ratio or again compositional scales.This contribution shows that it is sufficient to use some basic concepts and very fewadvanced tools from multivariate statistics (principal covariances, multivariate linearmodels, trellis or parallel plots, etc.) to build appropriate procedures for all these combinations of scales. This has some fundamental implications in their software implementation, and how might they be taught to analysts not already experts in multivariateanalysis

Dynamic graphics of parametrically linked multivariate methods used in compositional data analysis

Many multivariate methods that are apparently distinct can be linked by introducing oneor more parameters in their definition. Methods that can be linked in this way arecorrespondence analysis, unweighted or weighted logratio analysis (the latter alsoknown as "spectral mapping"), nonsymmetric correspondence analysis, principalcomponent analysis (with and without logarithmic transformation of the data) andmultidimensional scaling. In this presentation I will show how several of thesemethods, which are frequently used in compositional data analysis, may be linkedthrough parametrizations such as power transformations, linear transformations andconvex linear combinations. Since the methods of interest here all lead to visual mapsof data, a "movie" can be made where where the linking parameter is allowed to vary insmall steps: the results are recalculated "frame by frame" and one can see the smoothchange from one method to another. Several of these "movies" will be shown, giving adeeper insight into the similarities and differences between these methods

An R Library for Compositional Data Analysis in Archaeometry

Compositional data naturally arises from the scientific analysis of the chemicalcomposition of archaeological material such as ceramic and glass artefacts. Data of thistype can be explored using a variety of techniques, from standard multivariate methodssuch as principal components analysis and cluster analysis, to methods based upon theuse of log-ratios. The general aim is to identify groups of chemically similar artefactsthat could potentially be used to answer questions of provenance.This paper will demonstrate work in progress on the development of a documentedlibrary of methods, implemented using the statistical package R, for the analysis ofcompositional data. R is an open source package that makes available very powerfulstatistical facilities at no cost. We aim to show how, with the aid of statistical softwaresuch as R, traditional exploratory multivariate analysis can easily be used alongside, orin combination with, specialist techniques of compositional data analysis.The library has been developed from a core of basic R functionality, together withpurpose-written routines arising from our own research (for example that reported atCoDaWork'03). In addition, we have included other appropriate publicly availabletechniques and libraries that have been implemented in R by other authors. Availablefunctions range from standard multivariate techniques through to various approaches tolog-ratio analysis and zero replacement. We also discuss and demonstrate a smallselection of relatively new techniques that have hitherto been little-used inarchaeometric applications involving compositional data. The application of the libraryto the analysis of data arising in archaeometry will be demonstrated; results fromdifferent analyses will be compared; and the utility of the various methods discussed

A compositional data analysis package for R providing multiple approaches

”compositions” is a new R-package for the analysis of compositional and positive data.It contains four classes corresponding to the four different types of compositional andpositive geometry (including the Aitchison geometry). It provides means for computation,plotting and high-level multivariate statistical analysis in all four geometries.These geometries are treated in an fully analogous way, based on the principle of workingin coordinates, and the object-oriented programming paradigm of R. In this way,called functions automatically select the most appropriate type of analysis as a functionof the geometry. The graphical capabilities include ternary diagrams and tetrahedrons,various compositional plots (boxplots, barplots, piecharts) and extensive graphical toolsfor principal components. Afterwards, ortion and proportion lines, straight lines andellipses in all geometries can be added to plots. The package is accompanied by ahands-on-introduction, documentation for every function, demos of the graphical capabilitiesand plenty of usage examples. It allows direct and parallel computation inall four vector spaces and provides the beginner with a copy-and-paste style of dataanalysis, while letting advanced users keep the functionality and customizability theydemand of R, as well as all necessary tools to add own analysis routines. A completeexample is included in the appendix

Lluís Oliver i els components fonamentals de la matèria

Entrevista en Lluís Oliver, químic gironí

On the use of principal components in contemporany population genetics: a case study

In human Population Genetics, routine applications of principal component techniques are oftenrequired. Population biologists make widespread use of certain discrete classifications of humansamples into haplotypes, the monophyletic units of phylogenetic trees constructed from severalsingle nucleotide bimorphisms hierarchically ordered. Compositional frequencies of the haplotypesare recorded within the different samples. Principal component techniques are then required as adimension-reducing strategy to bring the dimension of the problem to a manageable level, say two,to allow for graphical analysis.Population biologists at large are not aware of the special features of compositional data and normally make use of the crude covariance of compositional relative frequencies to construct principalcomponents. In this short note we present our experience with using traditional linear principalcomponents or compositional principal components based on logratios, with reference to a specificdataset

Interpretation of wind components as compositional variables

The classical statistical study of the wind speed in the atmospheric surface layer is madegenerally from the analysis of the three habitual components that perform the wind data,that is, the component W-E, the component S-N and the vertical component,considering these components independent.When the goal of the study of these data is the Aeolian energy, so is when wind isstudied from an energetic point of view and the squares of wind components can beconsidered as compositional variables. To do so, each component has to be divided bythe module of the corresponding vector.In this work the theoretical analysis of the components of the wind as compositionaldata is presented and also the conclusions that can be obtained from the point of view ofthe practical applications as well as those that can be derived from the application ofthis technique in different conditions of weather

Chemical composition and antiprotozoal activities of Colombian Lippia spp essential oils and their major components

The chemical composition and biological activities of 19 essential oils and seven of their major components were tested against free and intracellular forms of Leishmania chagasi and Trypanosoma cruzi parasites as well as Vero and THP-1 mammalian cell lines. The essential oils were obtained from different species of Lippia, a widely distributed genus of Colombian plants. They were extracted by microwave radiation-assisted hydro-distillation and characterised by GC-FID and GC-MS. The major components were geranial, neral, limonene, nerol, carvacrol, p-cymene, γ-terpinene, carvone and thymol. The essential oil of Lippia alba exhibited the highest activity against T. cruzi epimastigotes and intracellular amastigotes with an IC50 of 5.5 μg/mL and 12.2 μg/mL, respectively. The essential oil of Lippia origanoides had an IC50 of 4.4 μg/mL in L. chagasi promastigotes and exhibited no toxicity in mammalian cells. Thymol (IC50 3.2 ± 0.4 μg/mL) and S-carvone (IC50 6.1 ± 2.2 μg/mL), two of the major components of the active essential oils, were active on intracellular amastigotes of T. cruziinfected Vero cells, with a selective index greater than 10. None of the essential oils or major components tested in this study was active on amastigotes of L. chagasi infected THP-1 cells.

Assessing the Precision of Compositional Data in a Stratified Double Stage Cluster Sample: Application to the Swiss Earnings Structure Survey

Precision of released figures is not only an important quality feature of official statistics,it is also essential for a good understanding of the data. In this paper we show a casestudy of how precision could be conveyed if the multivariate nature of data has to betaken into account. In the official release of the Swiss earnings structure survey, the totalsalary is broken down into several wage components. We follow Aitchison's approachfor the analysis of compositional data, which is based on logratios of components. Wefirst present diferent multivariate analyses of the compositional data whereby the wagecomponents are broken down by economic activity classes. Then we propose a numberof ways to assess precision

Adding new components to the knowledge plane GMPLS over WDM networks

A recent study defines a new network plane: the knowledge plane. The incorporation of the knowledge plane over the network allows having more accurate information of the current and future network states. In this paper, the introduction and management of the network reliability information in the knowledge plane is proposed in order to improve the quality of service with protection routing algorithms in GMPLS over WDM networks. Different experiments prove the efficiency and scalability of the proposed scheme in terms of the percentage of resources used to protect the network

I-SS: integrated supervision systems approach based on interactive components

Process supervision is the activity focused on monitoring the process operation in order to deduce conditions to maintain the normality including when faults are present Depending on the number/distribution/heterogeneity of variables, behaviour situations, sub-processes, etc. from processes, human operators and engineers do not easily manipulate the information. This leads to the necessity of automation of supervision activities. Nevertheless, the difficulty to deal with the information complicates the design and development of software applications. We present an approach called "integrated supervision systems". It proposes multiple supervisors coordination to supervise multiple sub-processes whose interactions permit one to supervise the global process