Identification of a genetic marker associated with the resistance to Schistosoma mansoni infection using random amplified polymorphic DNA analysis

In schistosomiasis, the host/parasite interaction remains not completely understood. Many questions related to the susceptibility of snails to infection by respective trematode still remain unanswered. The control of schistosomiasis requires a good understanding of the host/parasite association. In this work, the susceptibility/resistance to Schistosoma mansoni infection within Biomphalaria alexandrina snails were studied starting one month post infection and continuing thereafter weekly up to 10 weeks after miracidia exposure. Genetic variations between susceptible and resistant strains to Schistosoma infection within B. alexandrina snails using random amplified polymorphic DNA analysis technique were also carried out. The results showed that 39.8% of the examined field snails were resistant, while 60.2% of these snails showed high infection rates.In the resistant genotype snails, OPA-02 primer produced a major low molecular weight marker 430 bp. Among the two snail strains there were interpopulational variations, while the individual specimens from the same snail strain, either susceptible or resistant, record semi-identical genetic bands. Also, the resistant character was ascendant in contrast to a decline in the susceptibility of snails from one generation to the next.

A population genetics study of Anopheles darlingi (Diptera: Culicidae) from Colombia based on random amplified polymorphic DNA-polymerase chain reaction and amplified fragment lenght polymorphism markers

The genetic variation and population structure of three populations of Anopheles darlingi from Colombia were studied using random amplified polymorphic markers (RAPDs) and amplified fragment length polymorphism markers (AFLPs). Six RAPD primers produced 46 polymorphic fragments, while two AFLP primer combinations produced 197 polymorphic fragments from 71 DNA samples. Both of the evaluated genetic markers showed the presence of gene flow, suggesting that Colombian An. darlingi populations are in panmixia. Average genetic diversity, estimated from observed heterozygosity, was 0.374 (RAPD) and 0.309 (AFLP). RAPD and AFLP markers showed little evidence of geographic separation between eastern and western populations; however, the F ST values showed high gene flow between the two western populations (RAPD: F ST = 0.029; Nm: 8.5; AFLP: F ST = 0.051; Nm: 4.7). According to molecular variance analysis (AMOVA), the genetic distance between populations was significant (RAPD:phiST = 0.084; AFLP:phiST = 0.229, P < 0.001). The F ST distances and AMOVAs using AFLP loci support the differentiation of the Guyana biogeographic province population from those of the Chocó-Magdalena. In this last region, Chocó and Córdoba populations showed the highest genetic flow.

Genetic diversity of environmental Aspergillus flavus strains in the state of São Paulo, Brazil by random amplified polymorphic DNA

Aspergillus flavus is a very important toxigenic fungus that produces aflatoxins, a group of extremely toxic substances to man and animals. Toxigenic fungi can grow in feed crops, such as maize, peanuts, and soybeans, being thus of high concern for public health. There are toxigenic and non-toxigenic A. flavus variants, but the necessary conditions for expressing the toxigenic potential are not fully understood. Therefore, we have studied total-DNA polymorphism from toxigenic and non toxigenic A. flavus strains isolated from maize crops and soil at two geographic locations, 300 km apart, in the Southeast region of Brazil. Total DNA from each A. flavus isolate was extracted and subjected to polymerase chain reaction amplification with five randomic primers through the RAPD (random amplified polymorphic DNA) technique. Phenetic and cladistic analyses of the data, based on bootstrap analyses, led us to conclude that RAPD was not suitable to discriminate toxigenic from non toxigenic strains. But the present results support the use of RAPD for strain characterization, especially for preliminary evaluation over extensive collections.

Extremal properties of certain risk models

Cette thèse s'intéresse à étudier les propriétés extrémales de certains modèles de risque d'intérêt dans diverses applications de l'assurance, de la finance et des statistiques. Cette thèse se développe selon deux axes principaux, à savoir: Dans la première partie, nous nous concentrons sur deux modèles de risques univariés, c'est-à- dire, un modèle de risque de déflation et un modèle de risque de réassurance. Nous étudions le développement des queues de distribution sous certaines conditions des risques commun¬s. Les principaux résultats sont ainsi illustrés par des exemples typiques et des simulations numériques. Enfin, les résultats sont appliqués aux domaines des assurances, par exemple, les approximations de Value-at-Risk, d'espérance conditionnelle unilatérale etc. La deuxième partie de cette thèse est consacrée à trois modèles à deux variables: Le premier modèle concerne la censure à deux variables des événements extrême. Pour ce modèle, nous proposons tout d'abord une classe d'estimateurs pour les coefficients de dépendance et la probabilité des queues de distributions. Ces estimateurs sont flexibles en raison d'un paramètre de réglage. Leurs distributions asymptotiques sont obtenues sous certaines condi¬tions lentes bivariées de second ordre. Ensuite, nous donnons quelques exemples et présentons une petite étude de simulations de Monte Carlo, suivie par une application sur un ensemble de données réelles d'assurance. L'objectif de notre deuxième modèle de risque à deux variables est l'étude de coefficients de dépendance des queues de distributions obliques et asymétriques à deux variables. Ces distri¬butions obliques et asymétriques sont largement utiles dans les applications statistiques. Elles sont générées principalement par le mélange moyenne-variance de lois normales et le mélange de lois normales asymétriques d'échelles, qui distinguent la structure de dépendance de queue comme indiqué par nos principaux résultats. Le troisième modèle de risque à deux variables concerne le rapprochement des maxima de séries triangulaires elliptiques obliques. Les résultats théoriques sont fondés sur certaines hypothèses concernant le périmètre aléatoire sous-jacent des queues de distributions. -- This thesis aims to investigate the extremal properties of certain risk models of interest in vari¬ous applications from insurance, finance and statistics. This thesis develops along two principal lines, namely: In the first part, we focus on two univariate risk models, i.e., deflated risk and reinsurance risk models. Therein we investigate their tail expansions under certain tail conditions of the common risks. Our main results are illustrated by some typical examples and numerical simu¬lations as well. Finally, the findings are formulated into some applications in insurance fields, for instance, the approximations of Value-at-Risk, conditional tail expectations etc. The second part of this thesis is devoted to the following three bivariate models: The first model is concerned with bivariate censoring of extreme events. For this model, we first propose a class of estimators for both tail dependence coefficient and tail probability. These estimators are flexible due to a tuning parameter and their asymptotic distributions are obtained under some second order bivariate slowly varying conditions of the model. Then, we give some examples and present a small Monte Carlo simulation study followed by an application on a real-data set from insurance. The objective of our second bivariate risk model is the investigation of tail dependence coefficient of bivariate skew slash distributions. Such skew slash distributions are extensively useful in statistical applications and they are generated mainly by normal mean-variance mixture and scaled skew-normal mixture, which distinguish the tail dependence structure as shown by our principle results. The third bivariate risk model is concerned with the approximation of the component-wise maxima of skew elliptical triangular arrays. The theoretical results are based on certain tail assumptions on the underlying random radius.

Sex, drugs and chronic illness: health behaviours among chronically ill youth.

BACKGROUND: A growing body of literature indicates that adolescents with chronic conditions are as likely, or more likely, to take risky behaviours than their healthy peers. The objective of this research was to assess whether adolescents with chronic illness in Catalonia differ from their healthy peers in risk-taking behaviour. METHODS: Data were drawn from the Catalonia Adolescent Health database, a survey including a random school-based sample of 6952 young people, aged 14-19 years. The index group (IG) included 665 adolescents (450 females) reporting several chronic conditions. The comparison group (CG) comprised 6287 healthy adolescents (3306 females). Personal, family and school-related variables were analysed to ensure comparability between groups. Sexual behaviour, drug use (tobacco, alcohol, cannabis, cocaine and synthetic drugs) and perception of drug use among peers and in school were compared. Analysis was carried out separately by gender. chi-square, Fisher's and Student's tests were used to compare categorical and continuous variables. RESULTS: The prevalence of chronic conditions was 9.6%, with females showing a higher prevalence than males. The IG showed similar or higher rates of sexual intercourse and risky sexual behaviour. For most studied drugs, IG males reported slightly lower rates of use than CG males, while IG females showed higher rates for every drug studied. No differences were found in the perceptions of drug use among peers or in their school. CONCLUSIONS: Similar to previous research, chronically ill adolescents in our sample are as likely, or more likely, to take risky behaviours than their healthy counterparts and should receive the same anticipatory guidance.

Tècniques de Webmetria : anàlisi de logs i Google Analytics per a la obtenció de variables mètriques del web de la Biblioteca Virtual de la Universitat Oberta de Catalunya (UOC)

This presentation aims to make understandable the use and application context of two Webometrics techniques, the logs analysis and Google Analytics, which currently coexist in the Virtual Library of the UOC. In this sense, first of all it is provided a comprehensive introduction to webometrics and then it is analysed the case of the UOC's Virtual Library focusing on the assimilation of these techniques and the considerations underlying their use, and covering in a holistic way the process of gathering, processing and data exploitation. Finally there are also provided guidelines for the interpretation of the metric variables obtained.

Robust Factor Analysis for Compositional Data

Factor analysis as frequent technique for multivariate data inspection is widely used also for compositional data analysis. The usual way is to use a centered logratio (clr)transformation to obtain the random vector y of dimension D. The factor model istheny = Λf + e (1)with the factors f of dimension k & D, the error term e, and the loadings matrix Λ.Using the usual model assumptions (see, e.g., Basilevsky, 1994), the factor analysismodel (1) can be written asCov(y) = ΛΛT + ψ (2)where ψ = Cov(e) has a diagonal form. The diagonal elements of ψ as well as theloadings matrix Λ are estimated from an estimation of Cov(y).Given observed clr transformed data Y as realizations of the random vectory. Outliers or deviations from the idealized model assumptions of factor analysiscan severely effect the parameter estimation. As a way out, robust estimation ofthe covariance matrix of Y will lead to robust estimates of Λ and ψ in (2), seePison et al. (2003). Well known robust covariance estimators with good statisticalproperties, like the MCD or the S-estimators (see, e.g. Maronna et al., 2006), relyon a full-rank data matrix Y which is not the case for clr transformed data (see,e.g., Aitchison, 1986).The isometric logratio (ilr) transformation (Egozcue et al., 2003) solves thissingularity problem. The data matrix Y is transformed to a matrix Z by usingan orthonormal basis of lower dimension. Using the ilr transformed data, a robustcovariance matrix C(Z) can be estimated. The result can be back-transformed tothe clr space byC(Y ) = V C(Z)V Twhere the matrix V with orthonormal columns comes from the relation betweenthe clr and the ilr transformation. Now the parameters in the model (2) can beestimated (Basilevsky, 1994) and the results have a direct interpretation since thelinks to the original variables are still preserved.The above procedure will be applied to data from geochemistry. Our specialinterest is on comparing the results with those of Reimann et al. (2002) for the Kolaproject data

Association of Lutzomyia longipalpis (Diptera: Psychodidae) population density with climate variables in Montes Claros, an area of American visceral leishmaniasis transmission in the state of Minas Gerais, Brazil

In the present paper, we evaluate the relationship between climate variables and population density of Lutzomyia longipalpis in Montes Claros, an area of active transmission of American visceral leishmaniasis (AVL) in Brazil. Entomological captures were performed in 10 selected districts of the city, between September 2002-August 2003. A total of 773 specimens of L. longipalpiswere captured in the period and the population density could be associated with local climate variables (cumulative rainfall, average temperature and relative humidity) through a mathematical linear model with a determination coefficient (Rsqr) of 0.752. Although based on an oversimplified statistical analysis, as far as the vector is concerned, this approach showed to be potentially useful as a starting point to guide control measures for AVL in Montes Claros.

Modelling structural zeros in compositional data

This analysis was stimulated by the real data analysis problem of householdexpenditure data. The full dataset contains expenditure data for a sample of 1224 households. The expenditure is broken down at 2 hierarchical levels: 9 major levels (e.g. housing, food, utilities etc.) and 92 minor levels. There are also 5 factors and 5 covariates at the household level. Not surprisingly, there are a small number of zeros at the major level, but many zeros at the minor level. The question is how best to model the zeros. Clearly, models that tryto add a small amount to the zero terms are not appropriate in general as at least some of the zeros are clearly structural, e.g. alcohol/tobacco for households that are teetotal. The key question then is how to build suitable conditional models. For example, is the sub-composition of spendingexcluding alcohol/tobacco similar for teetotal and non-teetotal households?In other words, we are looking for sub-compositional independence. Also, what determines whether a household is teetotal? Can we assume that it is independent of the composition? In general, whether teetotal will clearly depend on the household level variables, so we need to be able to model this dependence. The other tricky question is that with zeros on more than onecomponent, we need to be able to model dependence and independence of zeros on the different components. Lastly, while some zeros are structural, others may not be, for example, for expenditure on durables, it may be chance as to whether a particular household spends money on durableswithin the sample period. This would clearly be distinguishable if we had longitudinal data, but may still be distinguishable by looking at the distribution, on the assumption that random zeros will usually be for situations where any non-zero expenditure is not small.While this analysis is based on around economic data, the ideas carry over tomany other situations, including geological data, where minerals may be missing for structural reasons (similar to alcohol), or missing because they occur only in random regions which may be missed in a sample (similar to the durables)

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

Medical image registration based on random line sampling

One of the key aspects in 3D-image registration is the computation of the joint intensity histogram. We propose a new approach to compute this histogram using uniformly distributed random lines to sample stochastically the overlapping volume between two 3D-images. The intensity values are captured from the lines at evenly spaced positions, taking an initial random offset different for each line. This method provides us with an accurate, robust and fast mutual information-based registration. The interpolation effects are drastically reduced, due to the stochastic nature of the line generation, and the alignment process is also accelerated. The results obtained show a better performance of the introduced method than the classic computation of the joint histogram

Error and complexity of random walk Monte Carlo radiosity

The author studies the error and complexity of the discrete random walk Monte Carlo technique for radiosity, using both the shooting and gathering methods. The author shows that the shooting method exhibits a lower complexity than the gathering one, and under some constraints, it has a linear complexity. This is an improvement over a previous result that pointed to an O(n log n) complexity. The author gives and compares three unbiased estimators for each method, and obtains closed forms and bounds for their variances. The author also bounds the expected value of the mean square error (MSE). Some of the results obtained are also shown

Análisis de las principales variables determinantes de la evolución de la mortalidad por demencias en Andalucía.

BACKGROUND The dementias are a cause of mortality have increased over the last years. Therefore is important to analyze the variables more related to its development in Andalusia between 1999 and 2010. METHODS With the deaths of 60 and over by dementia from Andalusia Statistical Institute and the populations from corresponding years, are estimated crude mortality rates, standardized and age-specific; by joinpoint regression was calculated percentages annual change; and also, with the population estimates by marital status and deaths was calculated crude rates and standardized for age, sex and marital status. RESULTS The standardized mortality rates increased from 124.8 to 161.0 deaths per 100,000 in women and 110.3 to 147.7 in men, the annual increase was 4.2% and 3.8% in women and men. The women died more than men with a standardized rate ratio between 1.08 and 1.29. Age was the variable that determined mortality. CONCLUSIONS Mortality from dementia in Andalusia has increased over the past 12 years and will continue to increase with the consequent social and health impacts posed by these diseases, configured as a major health problem.

Validation de la version française de l'échelle de contrôle de Levenson (IPC), influence de variables démographiques et de la personnalité

We have examined the internal validity of the Levenson's locus of control scales (IPC, Internal, Powerful others and Chances), translated by Loas et al. (1994). The impact of different demographic variables on the Levenson's locus of control scales was assessed. After, we studied the relation between the IPC scales and the NEO PI R, personality inventory that measures the big five. A large sample (n=200) of subjects of different age, gender and profession and a sample of Swiss students (n=161) responding anonymously were used. The reliability of the IPC scale is acceptable. The analyses of the impact of the demographic variables show that gender and level of education have an influence on the I (intern) scale. Age, gender, level of education and profession have an impact on the P (powerful others) scale. The analyses of the relationship between locus of control and personality showed that there was a negative correlation between I (intern) and Neuroticism and a positive correlation between I and Extraversion and Consciousness. The P (powerful others) scale correlate positively with Neuroticism and negatively with Openness and Agreability. The C scale (chance) correlate positively with Neuroticism. Our study also gives the researchers and the practitioner a reference score table according to the gender, the age, the level of education and the profession.

El espacio como producto social: variables arqueológicas para un análisis de la organización social en prehistoria

El espacio social es un concepto ambiguo cuyo componente material está determinado por el carácter del componente social, puesto que la organización de los objetos en el espacio y el espacio mismo, responden a las normas sociales del comportamiento humano. Partimos de la premisa que los residuos generados durante el proceso de producción y del consumo tienden a tener una distribución relativamente regular en el espacio físico. La ausencia de la aleatoriedad en la dispersión de estos restos solo significa que habían sido acumulados y depositados como restos de acciones previamente planificadas no-aleatoriamente. En este trabajo planteamos estudiar la organización y la producción del espacio social de una sociedad cazadora-recolectora concreta – la sociedad yámana - a través del análisis de las actividades cotidianas que figuran en las fuentes etnográficas y en el registro arqueológico. Con este fin creamos una metodología de trabajo interdisciplinaria, basada en un enfoque etnoarqueológico, y a través del estudio de las fuentes etnográficas, los trabajos etnoarqueológicos previos y el registro arquelógico concreto, descubrimos cuáles son las posibilidades y limitaciones de este tipo de estudios. Pudimos reconocer la regularidad espacial de los procesos de producción y reproducción social y a resolver algunas preguntas acerca del estudio de la organización social en prehistoria trabajando con los datos etnoarqueológicos obtenidos en los yacimientos Lanashuaia y Túnel VII (Tierra del Fuego, Argentina), analizando el registro extraido y trabajado en varias campañas de excavaciones arqueológicas en ultimos 25 años. El presente trabajo al fondo es un experimento etnoarqueológico estándar: partiendo de la observación etnográfica registramos unas recurrencias específicas entre algunas variables (por ejemplo: mujer/lugar/tipo de trabajo), intentamos extraer las variables definitorias de esas recurrencias, y finalmente las buscamos en el espacio definido arqueológicamente.