Circulating sex steroids during pregnancy and maternal risk of non-epithelial ovarian cancer.

BACKGROUND: Sex steroid hormones have been proposed to play a role in the development of non-epithelial ovarian cancers (NEOC) but so far no direct epidemiological data are available.METHODS: A case-control study was nested within the Finnish Maternity Cohort, the world's largest bio-repository of serum specimens from pregnant women. Study subjects were selected among women who donated a blood sample during a singleton pregnancy that led to the birth of their last child preceding diagnosis of NEOC. Case subjects were 41 women with sex-cord stromal tumors (SCST) and 21 with germ cell tumors (GCT). Three controls, matching the index case for age, parity at the index pregnancy, and date at blood donation were selected (n=171). Odds ratios (OR) and 95% confidence intervals (CI) associated with concentrations of testosterone, androstenedione, 17-OH-progesterone, progesterone, estradiol and sex hormone binding globulin (SHBG) were estimated through conditional logistic regression.RESULTS: For SCST, doubling of testosterone, androstenedione and 17-OH-progesterone concentrations were associated with about 2-fold higher risk of SCST [ORs and 95% CI of 2.16 (1.25-3.74), 2.16 (1.20-3.87), and 2.62 (1.27-5.38), respectively]. These associations remained largely unchanged after excluding women within 2, 4 or 6 years lag-time between blood donation and cancer diagnosis. Sex steroid hormones concentrations were not related to maternal risk of GCT.CONCLUSIONS: This is the first prospective study providing initial evidence that elevated androgens play a role in the pathogenesis of SCST. Impact: Our study may note a particular need for larger confirmatory investigations on sex steroids and NEOC.

Estudio del Business Intelligence y desarrollo de un Cuadro de Mando para el Análisis de Ventas

El Business Intelligence ha pasado en los últimos 20 años de ser un capricho de unos pocos CIO, que podían permitirse destinar partidas presupuestarias para tal efecto, a convertirse en una realidad ya presente en muchas de las grandes empresas o una necesidad urgente para las que todavía no han implantado un sistema de esas características.La primera parte del presente documento, denominada “Estudio del Business Intelligence”, presenta una introducción a dicho concepto, desde la base. Explicando los conceptos teóricos clave necesarios para entender este tipo de soluciones, más adelante se comentan los componentes tecnológicos que van desde los procesos de extracción e integración de información a cómo debemos estructurar la información para facilitar el análisis. Por último, se repasan los diferentes tipos de aplicaciones que existen en el mercado así como las tendencias más actuales en este campo.La segunda parte del documento centra su foco en la implantación de un Cuadro de Mandos para el análisis de las ventas de una empresa, se identifican las diferentes fases del proyecto así como se entra en detalle de los requerimientos identificados. En último lugar, se presenta el desarrollo realizado del Cuadro de Mandos con tecnología Xcelsius, que permite exportar a flash el resultado y visualizarlo en cualquier navegador web.

QuesTInSitu: mejora del sistema de autoría y móvil para la creación, realización y monitorización de rutas abiertas de preguntas geolocalizadas

Aquest projecte te com a objectiu estendre el treball realitzat amb l‟eina QuesTInSitu, ques‟emmarca dins del món de les Tecnologies de la Informació i Comunicació (TIC) iconcretament en l‟àrea d‟E-Learning. Es presenta una aplicació Web, QuesTInSitu, la qual ésuna eina d‟autoria que permet crear preguntes geolocalitzades a sobre de mapes de GoogleMaps. Aquestes preguntes segueixen l‟especificació IMS Question & Test Interporability (QTI)i són gestionades pel motor de QTI NewApis.L‟usuari pot crear preguntes geolocalitzades i organitzar-les com a rutes (qüestionaris) sobre unmapa de qualsevol punt del món. Per una altre banda, s‟ofereix la possibilitat de respondre a lespreguntes geolocalitzades mitjançant mòbils 3G gràcies a una aplicació especialmentdissenyada per a dispositius mòbils on els usuaris poden respondre les preguntes i veure lapuntuació.Aquest PFC presenta nous aspectes de millora sobre l‟eina ja existent, com per exemple: un nousistema de monitorització, un nou sistema de rutes, noves funcionalitats tant de l‟aplicaciómòbil com de l‟aplicació web entre d‟altres. Aquests nous aspectes s‟han avaluat dins de nousescenaris educatius.

Partial correlation : Network analysis

The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.

A genome-wide association study of anorexia nervosa.

Anorexia nervosa (AN) is a complex and heritable eating disorder characterized by dangerously low body weight. Neither candidate gene studies nor an initial genome-wide association study (GWAS) have yielded significant and replicated results. We performed a GWAS in 2907 cases with AN from 14 countries (15 sites) and 14 860 ancestrally matched controls as part of the Genetic Consortium for AN (GCAN) and the Wellcome Trust Case Control Consortium 3 (WTCCC3). Individual association analyses were conducted in each stratum and meta-analyzed across all 15 discovery data sets. Seventy-six (72 independent) single nucleotide polymorphisms were taken forward for in silico (two data sets) or de novo (13 data sets) replication genotyping in 2677 independent AN cases and 8629 European ancestry controls along with 458 AN cases and 421 controls from Japan. The final global meta-analysis across discovery and replication data sets comprised 5551 AN cases and 21 080 controls. AN subtype analyses (1606 AN restricting; 1445 AN binge-purge) were performed. No findings reached genome-wide significance. Two intronic variants were suggestively associated: rs9839776 (P=3.01 × 10(-7)) in SOX2OT and rs17030795 (P=5.84 × 10(-6)) in PPP3CA. Two additional signals were specific to Europeans: rs1523921 (P=5.76 × 10(-)(6)) between CUL3 and FAM124B and rs1886797 (P=8.05 × 10(-)(6)) near SPATA13. Comparing discovery with replication results, 76% of the effects were in the same direction, an observation highly unlikely to be due to chance (P=4 × 10(-6)), strongly suggesting that true findings exist but our sample, the largest yet reported, was underpowered for their detection. The accrual of large genotyped AN case-control samples should be an immediate priority for the field.

Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index.

Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.