Será que a Definição de Síndroma Metabólica pela International Diabetes Federation Melhora a Capacidade Preditora para Doença Coronária e do Espessamento da Íntima-Média Carotídea?

BACKGROUND: Metabolic syndrome (MS) is associated with increased incidence of diabetes and atherosclerotic complications. The new definition of the International Diabetes Federation (IDF) increases the population with this entity, compared to the NCEP ATP III definition. OBJECTIVES: To study the prevalence of coronary artery disease (CAD) and carotid intima-media thickness (IMT) in patients with and without MS, according to the NCEP ATP III and IDF definitions, and the predictive ability of carotid IMT for CAD. METHODS: We studied 270 consecutive patients admitted for elective coronary angiography due to suspicion of CAD. All patients underwent ultrasound study of the carotid arteries to measure IMT (the highest value between the right and left common carotid arteries was used in the analysis). Coronary stenosis of > or =70% (or 50% for the left main coronary artery) was considered significant. RESULTS: By the ATP III definition, 14% of the patients had MS, and these patients had a higher prevalence of CAD (87% vs. 63%, p = 0.004), but no significant difference was found for carotid IMT (1.03 +/- 0.36 mm vs. 0.95 +/- 0.35 mm, p=NS). With the IDF definition, 61% of the patients had MS; this group was slightly older and included more women. There were no differences in terms of CAD (68% vs. 63%) or carotid IMT (0.97 +/- 0.34 vs. 0.96 +/- 0.39 mm). On multivariate analysis, the ATP III definition of MS predicts CAD (OR 4.76, 95% CI 1.71-13.25, p = 0.003), but the IDF definition does not (OR 1.29, 95% CI 0.74-2.27, p = 0.37). On ROC curve analysis, an IMT of > or = 0.95 mm predicts CAD (AUC 0.66, p < 0.001), with a sensitivity of 52% and specificity of 75%. CONCLUSIONS: The new IDF definition increases the population with MS, decreasing the capacity to predict the presence of CAD. In our population, neither the ATP III nor the IDF definition showed differences in terms of carotid IMT. Carotid IMT can predict CAD, but with only modest sensitivity.

Is It Possible to Simplify Risk Stratification Scores for Patients with ST-Segment Elevation Myocardial Infarction Undergoing Primary Angioplasty?

INTRODUCTION: There are several risk scores for stratification of patients with ST-segment elevation myocardial infarction (STEMI), the most widely used of which are the TIMI and GRACE scores. However, these are complex and require several variables. The aim of this study was to obtain a reduced model with fewer variables and similar predictive and discriminative ability. METHODS: We studied 607 patients (age 62 years, SD=13; 76% male) who were admitted with STEMI and underwent successful primary angioplasty. Our endpoints were all-cause in-hospital and 30-day mortality. Considering all variables from the TIMI and GRACE risk scores, multivariate logistic regression models were fitted to the data to identify the variables that best predicted death. RESULTS: Compared to the TIMI score, the GRACE score had better predictive and discriminative performance for in-hospital mortality, with similar results for 30-day mortality. After data modeling, the variables with highest predictive ability were age, serum creatinine, heart failure and the occurrence of cardiac arrest. The new predictive model was compared with the GRACE risk score, after internal validation using 10-fold cross validation. A similar discriminative performance was obtained and some improvement was achieved in estimates of probabilities of death (increased for patients who died and decreased for those who did not). CONCLUSION: It is possible to simplify risk stratification scores for STEMI and primary angioplasty using only four variables (age, serum creatinine, heart failure and cardiac arrest). This simplified model maintained a good predictive and discriminative performance for short-term mortality.

Does direct cash flow presentation help in predicting future operating cash flow?

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Does direct cash flow presentation help in predicting future operating cash flow?

Research literature and regulators are unconditional in pointing the disclosure of operating cash flow through direct method a section of unique information. Besides the intuitive facet, it is also consistent in forecasting future operating cash flows and a cohesive piece to financial statement puzzle. Bearing this in mind, I produce an analysis on the usefulness and predictive ability on the disclosure of gross cash receipts and payments over the disclosure of reconciliation between net income and accruals for two markets with special features, Portugal and Spain. Results validate the usefulness of direct method format in predicting future operating cash flow. Key

Consumption, wealth, stock and housing returns: evidence from emerging markets

We test the predictive ability of the transitory deviations of consumption from its common trend with aggregate wealth and labour income, cay, for both future equity and housing risk premia in emerging market economies. Using quarterly data for 31 markets, our country-level evidence shows that forecasting power of cay vis-à-vis stock returns is high for Brazil, China, Colombia, Israel, Korea, Latvia and Malaysia. As for housing returns, the empirical evidence suggests that financial and housing assets are perceived as complements in the case of Chile, Russia, South Africa and Thailand, and as substitutes in Argentina, Brazil, Hong Kong, Indonesia, Korea, Malaysia, Mexico and Taiwan. Using a panel econometric framework, we find that the cross-country heterogeneity observed in asset return predictability does not accrue to regional location, but can be attributed to differences in the degree of equity market development and in the level of income.

Sucesso escolar e percursos vocacionais na adolescência: variáveis pessoais e contextuais

Tese de Doutoramento Ciências da Educação (Especialidade em Psicologia da Educação)

Aplicação da metodologia ROC na avaliação de desempenho de índices de gravidade clínica em unidades de neonatologia de Portugal

Tese de Doutoramento em Engenharia Industrial e de Sistemas

Predicting spatial patterns of plant biodiversity : from species to communities

Understanding the distribution and composition of species assemblages and being able to predict them in space and time are highly important tasks io investigate the fate of biodiversity in the current global changes context. Species distribution models are tools that have proven useful to predict the potential distribution of species by relating their occurrences to environmental variables. Species assemblages can then be predicted by combining the prediction of individual species models. In the first part of my thesis, I tested the importance of new environmental predictors to improve species distribution prediction. I showed that edaphic variables, above all soil pH and nitrogen content could be important in species distribution models. In a second chapter, I tested the influence of different resolution of predictors on the predictive ability of species distribution models. I showed that fine resolution predictors could ameliorate the models for some species by giving a better estimation of the micro-topographic condition that species tolerate, but that fine resolution predictors for climatic factors still need to be ameliorated. The second goal of my thesis was to test the ability of empirical models to predict species assemblages' characteristics such as species richness or functional attributes. I showed that species richness could be modelled efficiently and that the resulting prediction gave a more realistic estimate of the number of species than when obtaining it by stacking outputs of single species distribution models. Regarding the prediction of functional characteristics (plant height, leaf surface, seed mass) of plant assemblages, mean and extreme values of functional traits were better predictable than indices reflecting the diversity of traits in the community. This approach proved interesting to understand which environmental conditions influence particular aspects of the vegetation functioning. It could also be useful to predict climate change impacts on the vegetation. In the last part of my thesis, I studied the capacity of stacked species distribution models to predict the plant assemblages. I showed that this method tended to over-predict the number of species and that the composition of the community was not predicted exactly either. Finally, I combined the results of macro- ecological models obtained in the preceding chapters with stacked species distribution models and showed that this approach reduced significantly the number of species predicted and that the prediction of the composition is also ameliorated in some cases. These results showed that this method is promising. It needs now to be tested on further data sets. - Comprendre la manière dont les plantes se répartissent dans l'environnement et s'organisent en communauté est une question primordiale dans le contexte actuel de changements globaux. Cette connaissance peut nous aider à sauvegarder la diversité des espèces et les écosystèmes. Des méthodes statistiques nous permettent de prédire la distribution des espèces de plantes dans l'espace géographique et dans le temps. Ces modèles de distribution d'espèces, relient les occurrences d'une espèce avec des variables environnementales pour décrire sa distribution potentielle. Cette méthode a fait ses preuves pour ce qui est de la prédiction d'espèces individuelles. Plus récemment plusieurs tentatives de cumul de modèles d'espèces individuelles ont été réalisées afin de prédire la composition des communautés végétales. Le premier objectif de mon travail est d'améliorer les modèles de distribution en testant l'importance de nouvelles variables prédictives. Parmi différentes variables édaphiques, le pH et la teneur en azote du sol se sont avérés des facteurs non négligeables pour prédire la distribution des plantes. Je démontre aussi dans un second chapitre que les prédicteurs environnementaux à fine résolution permettent de refléter les conditions micro-topographiques subies par les plantes mais qu'ils doivent encore être améliorés avant de pouvoir être employés de manière efficace dans les modèles. Le deuxième objectif de ce travail consistait à étudier le développement de modèles prédictifs pour des attributs des communautés végétales tels que, par exemple, la richesse en espèces rencontrée à chaque point. Je démontre qu'il est possible de prédire par ce biais des valeurs de richesse spécifiques plus réalistes qu'en sommant les prédictions obtenues précédemment pour des espèces individuelles. J'ai également prédit dans l'espace et dans le temps des caractéristiques de la végétation telles que sa hauteur moyenne, minimale et maximale. Cette approche peut être utile pour comprendre quels facteurs environnementaux promeuvent différents types de végétation ainsi que pour évaluer les changements à attendre au niveau de la végétation dans le futur sous différents régimes de changements climatiques. Dans une troisième partie de ma thèse, j'ai exploré la possibilité de prédire les assemblages de plantes premièrement en cumulant les prédictions obtenues à partir de modèles individuels pour chaque espèce. Cette méthode a le défaut de prédire trop d'espèces par rapport à ce qui est observé en réalité. J'ai finalement employé le modèle de richesse en espèce développé précédemment pour contraindre les résultats du modèle d'assemblage de plantes. Cela a permis l'amélioration des modèles en réduisant la sur-prédiction et en améliorant la prédiction de la composition en espèces. Cette méthode semble prometteuse mais de nouveaux tests sont nécessaires pour bien évaluer ses capacités.

The prognostic value of health-related quality-of-life data in predicting survival in glioblastoma cancer patients: results from an international randomised phase III EORTC Brain Tumour and Radiation Oncology Groups, and NCIC Clinical Trials Group study.

This is one of the few studies that have explored the value of baseline symptoms and health-related quality of life (HRQOL) in predicting survival in brain cancer patients. Baseline HRQOL scores (from the EORTC QLQ-C30 and the Brain Cancer Module (BN 20)) were examined in 490 newly diagnosed glioblastoma cancer patients for the relationship with overall survival by using Cox proportional hazards regression models. Refined techniques as the bootstrap re-sampling procedure and the computation of C-indexes and R(2)-coefficients were used to try and validate the model. Classical analysis controlled for major clinical prognostic factors selected cognitive functioning (P=0.0001), global health status (P=0.0055) and social functioning (P<0.0001) as statistically significant prognostic factors of survival. However, several issues question the validity of these findings. C-indexes and R(2)-coefficients, which are measures of the predictive ability of the models, did not exhibit major improvements when adding selected or all HRQOL scores to clinical factors. While classical techniques lead to positive results, more refined analyses suggest that baseline HRQOL scores add relatively little to clinical factors to predict survival. These results may have implications for future use of HRQOL as a prognostic factor in cancer patients.

Genetic relationships between suicide attempts, suicidal ideation and major psychiatric disorders: A genome-wide association and polygenic scoring study.

Epidemiological studies have recognized a genetic diathesis for suicidal behavior, which is independent of other psychiatric disorders. Genome-wide association studies (GWAS) on suicide attempt (SA) and ideation have failed to identify specific genetic variants. Here, we conduct further GWAS and for the first time, use polygenic score analysis in cohorts of patients with mood disorders, to test for common genetic variants for mood disorders and suicide phenotypes. Genome-wide studies for SA were conducted in the RADIANT and GSK-Munich recurrent depression samples and London Bipolar Affective Disorder Case-Control Study (BACCs) then meta-analysis was performed. A GWAS on suicidal ideation during antidepressant treatment had previously been conducted in the Genome Based Therapeutic Drugs for Depression (GENDEP) study. We derived polygenic scores from each sample and tested their ability to predict SA in the mood disorder cohorts or ideation status in the GENDEP study. Polygenic scores for major depressive disorder, bipolar disorder and schizophrenia from the Psychiatric Genomics Consortium were used to investigate pleiotropy between psychiatric disorders and suicide phenotypes. No significant evidence for association was detected at any SNP in GWAS or meta-analysis. Polygenic scores for major depressive disorder significantly predicted suicidal ideation in the GENDEP pharmacogenetics study and also predicted SA in a combined validation dataset. Polygenic scores for SA showed no predictive ability for suicidal ideation. Polygenic score analysis suggests pleiotropy between psychiatric disorders and suicidal ideation whereas the tendency to act on such thoughts may have a partially independent genetic diathesis. © 2014 Wiley Periodicals, Inc.

Genome-Wide Prediction Methods in Highly Diverse and Heterozygous Species: Proof-of-Concept through Simulation in Grapevine.

Nowadays, genome-wide association studies (GWAS) and genomic selection (GS) methods which use genome-wide marker data for phenotype prediction are of much potential interest in plant breeding. However, to our knowledge, no studies have been performed yet on the predictive ability of these methods for structured traits when using training populations with high levels of genetic diversity. Such an example of a highly heterozygous, perennial species is grapevine. The present study compares the accuracy of models based on GWAS or GS alone, or in combination, for predicting simple or complex traits, linked or not with population structure. In order to explore the relevance of these methods in this context, we performed simulations using approx 90,000 SNPs on a population of 3,000 individuals structured into three groups and corresponding to published diversity grapevine data. To estimate the parameters of the prediction models, we defined four training populations of 1,000 individuals, corresponding to these three groups and a core collection. Finally, to estimate the accuracy of the models, we also simulated four breeding populations of 200 individuals. Although prediction accuracy was low when breeding populations were too distant from the training populations, high accuracy levels were obtained using the sole core-collection as training population. The highest prediction accuracy was obtained (up to 0.9) using the combined GWAS-GS model. We thus recommend using the combined prediction model and a core-collection as training population for grapevine breeding or for other important economic crops with the same characteristics.

Ignoring information in binary choice with continuous variables: When is less 'more'?

When can a single variable be more accurate in binary choice than multiple sources of information? We derive analytically the probability that a single variable (SV) will correctly predict one of two choices when both criterion and predictor are continuous variables. We further provide analogous derivations for multiple regression (MR) and equal weighting (EW) and specify the conditions under which the models differ in expected predictive ability. Key factors include variability in cue validities, intercorrelation between predictors, and the ratio of predictors to observations in MR. Theory and simulations are used to illustrate the differential effects of these factors. Results directly address why and when one-reason decision making can be more effective than analyses that use more information. We thus provide analytical backing to intriguing empirical results that, to date, have lacked theoretical justification. There are predictable conditions for which one should expect less to be more.

Biaix d'items i habilitat en fraccions

En este artículo se contemplan algunos conceptos clave en la Teoría de respuestas de Items (TRI): curvas características, significado de habilidad y discriminación en dicha Teoría. Se aplica el estudio de niveles de habilidad cognitiva en el aprendizaje de las fracciones en la Educación Básica en 5º y 8ºde EGB en España siguiendo el planteamiento de Onslow y Kieren. Los diseños gráficos muestran claramente las diferencias entre edades y cursos.

Tumor-host interactions Part 1: Stromal signatures of breast and prostate cancer Part 2: GLG1 and the control of the secretory pathway in tumor cells

Tumor-host interaction is a key determinant during cancer progression, from primary tumor growth to metastatic dissemination. At each step, tumor cells have to adapt to and subvert different types of microenvironment, leading to major phenotypic and genotypic alterations that affect both tumor and surrounding stromal compartments. Understanding the molecular mechanisms that govern tumor-host interplay may be essential for better comprehension of tumorigenesis in an effort to improve current anti-cancer therapies. The present work is composed of two projects that address tumor-host interactions from two different perspectives, the first focusing on the characterization of tumor-associated stroma and the second on membrane trafficking in tumor cells. Part 1. To selectively address stromal gene expression changes during cancer progression, oligonucleotide-based Affymetrix microarray technology was used to analyze the transcriptomes of laser-microdissected stromal cells derived from invasive human breast and prostate carcinoma. Comparison showed that invasive breast and prostate cancer elicit distinct, tumor-specific stromal responses, with a limited panel of shared induced and/or repressed genes. Both breast and prostate tumor-specific deregulated stromal gene sets displayed statistically significant survival-predictive ability for their respective tumor type. By contrast, a stromal gene signature common to both tumor types did not display prognostic value, although expression of two individual genes within this common signature was found to be associated with patient survival. Part 2. GLG1 is known as an E-selectin ligand and an intracellular FGF receptor, depending on cell type and context. Immunohistochemical and immunofluorescence analyses showed that GLG1 is primarily localized in the Golgi of human tumor cells, a central location in the biosynthetic/secretory pathways. GLG1 has been shown to interact with and to recruit the ARF GEF BIGI to the Golgi membrane. Depletion of GLG1 or BIGI markedly reduced ARF3 membrane localization and activation, and altered the Golgi structure. Interestingly, these perturbations did not impair constitutive secretion in general, but rather seemed to impair secretion of a specific subset of proteins that includes MMP-9. Thus, GLG1 coordinates ARF3 activation by recruiting BIGI to the Golgi membrane, thereby affecting secretion of specific molecules. - Les interactions tumeur-hôte constituent un élément essentiel à la progression tumorale, de la croissance de la tumeur primaire à la dissémination des métastases. A chaque étape, les cellules tumorales doivent s'adapter à différents types de microenvironnement et les détourner à leur propre avantage, donnant lieu à des altérations phénotypiques et génotypiques majeures qui affectent aussi bien la tumeur elle-même que le compartiment stromal environnant. L'étude des mécanismes moléculaires qui régissent les interactions tumeur-hôte constitue une étape essentielle pour une meilleure compréhension du processus de tumorigenèse dans le but d'améliorer les thérapies anti cancer existantes. Le travail présenté ici est composé de deux projets qui abordent la problématique des interactions tumeur-hôte selon différentes perspectives, le premier se concentrant sur la caractérisation du stroma tumoral et le second sur le trafic intracellulaire des cellules tumorales. Partie 1. Pour examiner les changements d'expression des gènes dans le stroma en réponse à la progression du cancer, des puces à ADN Affymetrix ont été utilisées afin d'analyser les transcriptomes des cellules stromales issues de carcinomes invasifs du sein et de la prostate et collectées par microdissection au laser. L'analyse comparative a montré que les cancers invasifs du sein et de la prostate provoquent des réponses stromales spécifiques à chaque type de tumeur, et présentent peu de gènes induits ou réprimés de façon similaire. L'ensemble des gènes dérégulés dans le stroma associé au cancer du sein, ou à celui de la prostate, présente une valeur pronostique pour les patients atteints d'un cancer du sein, respectivement de la prostate. En revanche, la signature stromale commune aux deux types de cancer n'a aucune valeur prédictive, malgré le fait que l'expression de deux gènes présents dans cette liste soit liée à la survie des patients. Partie 2. GLG1 est connu comme un ligand des sélectines E ainsi que comme récepteur intracellulaire pour des facteurs de croissances FGFs selon le type de cellule dans lequel il est exprimé. Des analyses immunohistochimiques et d'immunofluorescence ont montré que dans les cellules tumorales, GLG1 est principalement localisé au niveau de l'appareil de Golgi, une place centrale dans la voie biosynthétique et sécrétoire. Nous avons montré que GLG1 interagit avec la protéine BIGI et participe à son recrutement à la membrane du Golgi. L'absence de GLG1 ou de BIGI réduit drastiquement le pool d'ARF3 associé aux membranes ainsi que la quantité d'ARF3 activés, et modifie la structure de l'appareil de Golgi. Il est particulièrement intéressant de constater que ces perturbations n'ont pas d'effet sur la sécrétion constitutive en général, mais semblent plutôt affecter la sécrétion spécifique d'un sous-groupe défini de protéines comprenant MMP-9. GLG1 coordonne donc l'activation de ARF3 en recrutant BIGI à la membrane du Golgi, agissant par ce moyen sur la sécrétion de molécules spécifiques.

The changing relationship between commodity prices and equity prices in commodity exporting

We explore the linkage between equity and commodity markets, focusing in particular on its evolution over time. We document that a country's equity market valuehas significant out-of-sample predictive ability for the future global commodity priceindex for several primary commodity-exporting countries. The out-of-sample predictive ability of the equity market appears around 2000s. The results are robust to usingseveral control variables as well as firm-level equity data. Finally, our results indicatethat exchange rates are a better predictor of commodity prices than equity markets,especially at very short horizons.