Computational analysis of the genetic and environmental contributions to disease-related human phenotypes: From predicting adverse lipid response of HIV patients receiving antiretroviral therapy to genome-wide association studies of cardiovascular and lipid related disorders

Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.

Energy deficit and length of hospital stay can be reduced by a two-step quality improvement of nutrition therapy: the intensive care unit dietitian can make the difference.

OBJECTIVE: Critically ill patients are at high risk of malnutrition. Insufficient nutritional support still remains a widespread problem despite guidelines. The aim of this study was to measure the clinical impact of a two-step interdisciplinary quality nutrition program. DESIGN: Prospective interventional study over three periods (A, baseline; B and C, intervention periods). SETTING: Mixed intensive care unit within a university hospital. PATIENTS: Five hundred seventy-two patients (age 59 ± 17 yrs) requiring >72 hrs of intensive care unit treatment. INTERVENTION: Two-step quality program: 1) bottom-up implementation of feeding guideline; and 2) additional presence of an intensive care unit dietitian. The nutrition protocol was based on the European guidelines. MEASUREMENTS AND MAIN RESULTS: Anthropometric data, intensive care unit severity scores, energy delivery, and cumulated energy balance (daily, day 7, and discharge), feeding route (enteral, parenteral, combined, none-oral), length of intensive care unit and hospital stay, and mortality were collected. Altogether 5800 intensive care unit days were analyzed. Patients in period A were healthier with lower Simplified Acute Physiologic Scale and proportion of "rapidly fatal" McCabe scores. Energy delivery and balance increased gradually: impact was particularly marked on cumulated energy deficit on day 7 which improved from -5870 kcal to -3950 kcal (p < .001). Feeding technique changed significantly with progressive increase of days with nutrition therapy (A: 59% days, B: 69%, C: 71%, p < .001), use of enteral nutrition increased from A to B (stable in C), and days on combined and parenteral nutrition increased progressively. Oral energy intakes were low (mean: 385 kcal*day, 6 kcal*kg*day ). Hospital mortality increased with severity of condition in periods B and C. CONCLUSION: A bottom-up protocol improved nutritional support. The presence of the intensive care unit dietitian provided significant additional progression, which were related to early introduction and route of feeding, and which achieved overall better early energy balance.

Synthetic calibrators for the analysis of total metanephrines in urine: revisiting the conditions of hydrolysis.

BACKGROUND: The quantification of total (free+sulfated) metanephrines in urine is recommended to diagnose pheochromocytoma. Urinary metanephrines include metanephrine itself, normetanephrine and methoxytyramine, mainly in the form of sulfate conjugates (60-80%). Their determination requires the hydrolysis of the sulfate ester moiety to allow electrochemical oxidation of the phenolic group. Commercially available urine calibrators and controls contain essentially free, unhydrolysable metanephrines which are not representative of native urines. The lack of appropriate calibrators may lead to uncertainty regarding the completion of the hydrolysis of sulfated metanephrines, resulting in incorrect quantification. METHODS: We used chemically synthesized sulfated metanephrines to establish whether the procedure most frequently recommended for commercial kits (pH 1.0 for 30 min over a boiling water bath) ensures their complete hydrolysis. RESULTS: We found that sulfated metanephrines differ in their optimum pH to obtain complete hydrolysis. Highest yields and minimal variance were established for incubation at pH 0.7-0.9 during 20 min. CONCLUSION: Urinary pH should be carefully controlled to ensure an efficient and reproducible hydrolysis of sulfated metanephrines. Synthetic sulfated metanephrines represent the optimal material for calibrators and proficiency testing to improve inter-laboratory accuracy.

Univariate versus multivariate modeling of panel data

Panel data can be arranged into a matrix in two ways, called 'long' and 'wide' formats (LFand WF). The two formats suggest two alternative model approaches for analyzing paneldata: (i) univariate regression with varying intercept; and (ii) multivariate regression withlatent variables (a particular case of structural equation model, SEM). The present papercompares the two approaches showing in which circumstances they yield equivalent?insome cases, even numerically equal?results. We show that the univariate approach givesresults equivalent to the multivariate approach when restrictions of time invariance (inthe paper, the TI assumption) are imposed on the parameters of the multivariate model.It is shown that the restrictions implicit in the univariate approach can be assessed bychi-square difference testing of two nested multivariate models. In addition, commontests encountered in the econometric analysis of panel data, such as the Hausman test, areshown to have an equivalent representation as chi-square difference tests. Commonalitiesand differences between the univariate and multivariate approaches are illustrated usingan empirical panel data set of firms' profitability as well as a simulated panel data.

Problems of allometric scaling analysis: examples from mammalian reproductive biology.

Biological scaling analyses employing the widely used bivariate allometric model are beset by at least four interacting problems: (1) choice of an appropriate best-fit line with due attention to the influence of outliers; (2) objective recognition of divergent subsets in the data (allometric grades); (3) potential restrictions on statistical independence resulting from phylogenetic inertia; and (4) the need for extreme caution in inferring causation from correlation. A new non-parametric line-fitting technique has been developed that eliminates requirements for normality of distribution, greatly reduces the influence of outliers and permits objective recognition of grade shifts in substantial datasets. This technique is applied in scaling analyses of mammalian gestation periods and of neonatal body mass in primates. These analyses feed into a re-examination, conducted with partial correlation analysis, of the maternal energy hypothesis relating to mammalian brain evolution, which suggests links between body size and brain size in neonates and adults, gestation period and basal metabolic rate. Much has been made of the potential problem of phylogenetic inertia as a confounding factor in scaling analyses. However, this problem may be less severe than suspected earlier because nested analyses of variance conducted on residual variation (rather than on raw values) reveals that there is considerable variance at low taxonomic levels. In fact, limited divergence in body size between closely related species is one of the prime examples of phylogenetic inertia. One common approach to eliminating perceived problems of phylogenetic inertia in allometric analyses has been calculation of 'independent contrast values'. It is demonstrated that the reasoning behind this approach is flawed in several ways. Calculation of contrast values for closely related species of similar body size is, in fact, highly questionable, particularly when there are major deviations from the best-fit line for the scaling relationship under scrutiny.

Could concomitant radio-chemotherapy improve the outcomes of early-stage node negative anal canal cancer patients? A retrospective analysis of 122 patients.

One hundred twenty-two early-stage anal canal cancer patients (median age: 69 years) were treated with curative radiotherapy with (70 patients) or without (52 patients) concomitant chemotherapy. Median follow-up was 65 months (range: 4-238). At multivariate analysis, concomitant chemotherapy significantly improved local control (p = .007). Local control significantly influenced all considered endpoints, except the metastases free survival. The global rates of G3-G4 acute and late toxicity were 13.1% and 8.2%, respectively, and they were not increased by concomitant chemotherapy. Finally, concomitant chemotherapy is efficacious and safe in the treatment of T1-2N0 anal canal cancer patients and should be prospectively studied.

Subtypes of adolescents with substance use disorders and psychiatric comorbidity using cluster and discriminant analysis of MMPI-A profiles

The main aim of this study was to replicate and extend previous results on subtypes of adolescents with substance use disorders (SUD), according to their Minnesota Multiphasic Personality Inventory for adolescents (MMPI-A) profiles. Sixty patients with SUD and psychiatric comorbidity (41.7% male, mean age = 15.9 years old) completed the MMPI-A, the Teen Addiction Severity Index (T-ASI), the Child Behaviour Checklist (CBCL), and were interviewed in order to determine DSMIV diagnoses and level of substance use. Mean MMPI-A personality profile showed moderate peaks in Psychopathic Deviate, Depression and Hysteria scales. Hierarchical cluster analysis revealed four profiles (acting-out, 35% of the sample; disorganized-conflictive, 15%; normative-impulsive, 15%; and deceptive-concealed, 35%). External correlates were found between cluster 1, CBCL externalizing symptoms at a clinical level and conduct disorders, and between cluster 2 and mixed CBCL internalized/externalized symptoms at a clinical level. Discriminant analysis showed that Depression, Psychopathic Deviate and Psychasthenia MMPI-A scales correctly classified 90% of the patients into the clusters obtained.

The use of beta-blockers is associated with the occurrence of acute kidney injury in severe alcoholic hepatitis.

BACKGROUND & AIMS: The beneficial effect of nonselective beta-blockers (NSBB) has recently been questioned in patients with end-stage cirrhosis. We analysed the impact of NSBB on outcomes in severe alcoholic hepatitis (AH). METHODS: This study was based on a prospective database of patients with severe, biopsy-proven AH. Patients admitted from July, 2006 to July, 2014 were retrospectively studied. Patients were divided into two groups (with and without NSBB) and assessed for the occurrence of Acute Kidney Injury (AKI) and transplant-free mortality during a 168-day follow-up period. RESULTS: One hundred thirty-nine patients were included, the mean Maddrey score was 71 ± 34 and 86 patients (61.9%) developed AKI. Forty-eight patients (34.5%) received NSBB. The overall 168-day transplant-free mortality was 50.5% (95%CI, 41.3-60.0%). The overall 168-day cumulative incidence of AKI was 61.9% (95%CI, 53.2-69.4%). When compared, patients with NSBB had a lower heart rate (65 ± 13 vs 92 ± 12, P < 0.0001) and a lower mean arterial pressure (MAP, 78 ± 3 vs 87 ± 5, P < 0.0001). Patients with NSBB had comparable MELD scores, Maddrey scores, and medical histories. The 168-day transplant-free mortality was 56.8% (95%CI, 41.3-69.7%) in patients with NSBB and 46.7% (95%CI, 35.0-57.6%) without NSBB (P = 0.25). The 168-day cumulative incidence of AKI was 89.6% (95%CI, 74.9-95.9%) with NSBB compared to 50.4% (95%CI: 39.0-60.7) for no NSBB (P = 0.0001). The independent factors predicting AKI were a higher MELD score and the presence of NSBB. CONCLUSIONS: The use of NSBB in patients with severe AH is independently associated with a higher cumulative incidence of AKI.

Incidence and consequence of major bleeding in primary percutaneous intervention for ST-elevation myocardial infarction in the era of radial access: an analysis of the international randomized Acute myocardial infarction Treated with primary angioplasty and intravenous enoxaparin Or unfractionated heparin to Lower ischemic and bleeding events at short- and Long-term follow-up trial.

AIMS: The aims of the study are to compare the outcome with and without major bleeding and to identify the independent correlates of major bleeding complications and mortality in patients described in the ATOLL study. METHODS: The ATOLL study included 910 patients randomly assigned to either 0.5 mg/kg intravenous enoxaparin or unfractionated heparin before primary percutaneous coronary intervention. Incidence of major bleeding and ischemic end points was assessed at 1 month, and mortality, at 1 and 6 months. Patients with and without major bleeding complication were compared. A multivariate model of bleeding complications at 1 month and mortality at 6 months was realized. Intention-to-treat and per-protocol analyses were performed. RESULTS: The most frequent bleeding site appears to be the gastrointestinal tract. Age >75 years, cardiac arrest, and the use of insulin or >1 heparin emerged as independent correlates of major bleeding at 1 month. Patients presenting with major bleeding had significantly higher rates of adverse ischemic complications. Mortality at 6 months was higher in bleeders. Major bleeding was found to be one of the independent correlates of 6-month mortality. The addition or mixing of several anticoagulant drugs was an independent factor of major bleeding despite the predominant use of radial access. CONCLUSIONS: This study shows that major bleeding is independently associated with poor outcome, increasing ischemic events, and mortality in primary percutaneous coronary intervention performed mostly with radial access.

Gamma Knife Surgery versus Linac for Brain Metastasis: Which Technique for Which Patient? Analysis of an Historical Cohort of 63 Consecutive Patients Harboring 130 Lesions

Objectives: We present the retrospective analysis of a single-institution experience for radiosurgery (RS) in brain metastasis (BM) with Gamma Knife (GK) and Linac. Methods: From July 2010 to July 2012, 28 patients (with 83 lesions) had RS with GK and 35 patients (with 47 lesions) with Linac. The primary outcome was the local progression-free survival (LPFS). The secondary outcome was the overall survival (OS). Apart a standard statistical analysis, we included a Cox regression model with shared frailty, to modulate the within-patient correlation (preliminary evaluation showed a significant frailty effect, meaning that the correlation within patient could be ignored). Results: The mean follow-up period was 11.7 months (median 7.9, 1.7-22.7) for GK and 18.1 (median 17, 7.5-28.7) for Linac. The median number of lesions per patient was 2.5 (1-9) in GK compared with 1 (1-3) in Linac. There were more radioresistant lesions (melanoma) and more lesions located in functional areas for the GK group. The median dose was 24 Gy (GK) compared with 20 Gy (Linac). The LPFS actuarial rate was as follows: for GK at 3, 6, 9, 12, and 17 months: 96.96, 96.96, 96.96, 88.1, and 81.5%, and remained stable till 32 months; for Linac at 3, 6, 12, 17, 24, and 33 months, it was 91.5, 91.5, 91.5, 79.9, 55.5, and 17.1%, respectively (p = 0.03, chi-square test). After the Cox regression analysis with shared frailty, the p-value was not statistically significant between groups. The median overall survival was 9.7 months for GK and 23.6 months for Linac group. Uni- and multivariate analysis showed a lower GPA score and noncontrolled systemic status were associated with lower OS. Cox regression analysis adjusting for these two parameters showed comparable OS rate. Conclusions: In this comparative report between GK and Linac, preliminary analysis showed that more difficult cases are treated by GK, with patients harboring more lesions, radioresistant tumors, and highly functional located. The groups look, in this sense, very heterogeneous at baseline. After a Cox frailty model, the LPFS rates seemed very similar (p < 0.05). The OS was similar, after adjusting for systemic status and GPA score (p < 0.05). The technical reasons for choosing GK instead of Linac were the anatomical location related to highly functional areas, histology, technical limitations of Linac movements, especially lower posterior fossa locations, or closeness of multiple lesions to highly functional areas optimal dosimetry with Linac

Modelling body mass index and endometrial cancer risk in a pooled-analysis of three case-control studies.

OBJECTIVE: To quantify the relation between body mass index (BMI) and endometrial cancer risk, and to describe the shape of such a relation. DESIGN: Pooled analysis of three hospital-based case-control studies. SETTING: Italy and Switzerland. POPULATION: A total of 1449 women with endometrial cancer and 3811 controls. METHODS: Multivariate odds ratios (OR) and 95% confidence intervals (95% CI) were obtained from logistic regression models. The shape of the relation was determined using a class of flexible regression models. MAIN OUTCOME MEASURE: The relation of BMI with endometrial cancer. RESULTS: Compared with women with BMI 18.5 to <25 kg/m(2) , the odds ratio was 5.73 (95% CI 4.28-7.68) for women with a BMI ≥35 kg/m(2) . The odds ratios were 1.10 (95% CI 1.09-1.12) and 1.63 (95% CI 1.52-1.75) respectively for an increment of BMI of 1 and 5 units. The relation was stronger in never-users of oral contraceptives (OR 3.35, 95% CI 2.78-4.03, for BMI ≥30 versus <25 kg/m(2) ) than in users (OR 1.22, 95% CI 0.56-2.67), and in women with diabetes (OR 8.10, 95% CI 4.10-16.01, for BMI ≥30 versus <25 kg/m(2) ) than in those without diabetes (OR 2.95, 95% CI 2.44-3.56). The relation was best fitted by a cubic model, although after the exclusion of the 5% upper and lower tails, it was best fitted by a linear model. CONCLUSIONS: The results of this study confirm a role of elevated BMI in the aetiology of endometrial cancer and suggest that the risk in obese women increases in a cubic nonlinear fashion. The relation was stronger in never-users of oral contraceptives and in women with diabetes. TWEETABLE ABSTRACT: Risk of endometrial cancer increases with elevated body weight in a cubic nonlinear fashion.

Analysis of space-time environmental data in complex regions

This thesis develops a comprehensive and a flexible statistical framework for the analysis and detection of space, time and space-time clusters of environmental point data. The developed clustering methods were applied in both simulated datasets and real-world environmental phenomena; however, only the cases of forest fires in Canton of Ticino (Switzerland) and in Portugal are expounded in this document. Normally, environmental phenomena can be modelled as stochastic point processes where each event, e.g. the forest fire ignition point, is characterised by its spatial location and occurrence in time. Additionally, information such as burned area, ignition causes, landuse, topographic, climatic and meteorological features, etc., can also be used to characterise the studied phenomenon. Thereby, the space-time pattern characterisa- tion represents a powerful tool to understand the distribution and behaviour of the events and their correlation with underlying processes, for instance, socio-economic, environmental and meteorological factors. Consequently, we propose a methodology based on the adaptation and application of statistical and fractal point process measures for both global (e.g. the Morisita Index, the Box-counting fractal method, the multifractal formalism and the Ripley's K-function) and local (e.g. Scan Statistics) analysis. Many measures describing the space-time distribution of environmental phenomena have been proposed in a wide variety of disciplines; nevertheless, most of these measures are of global character and do not consider complex spatial constraints, high variability and multivariate nature of the events. Therefore, we proposed an statistical framework that takes into account the complexities of the geographical space, where phenomena take place, by introducing the Validity Domain concept and carrying out clustering analyses in data with different constrained geographical spaces, hence, assessing the relative degree of clustering of the real distribution. Moreover, exclusively to the forest fire case, this research proposes two new methodologies to defining and mapping both the Wildland-Urban Interface (WUI) described as the interaction zone between burnable vegetation and anthropogenic infrastructures, and the prediction of fire ignition susceptibility. In this regard, the main objective of this Thesis was to carry out a basic statistical/- geospatial research with a strong application part to analyse and to describe complex phenomena as well as to overcome unsolved methodological problems in the characterisation of space-time patterns, in particular, the forest fire occurrences. Thus, this Thesis provides a response to the increasing demand for both environmental monitoring and management tools for the assessment of natural and anthropogenic hazards and risks, sustainable development, retrospective success analysis, etc. The major contributions of this work were presented at national and international conferences and published in 5 scientific journals. National and international collaborations were also established and successfully accomplished. -- Cette thèse développe une méthodologie statistique complète et flexible pour l'analyse et la détection des structures spatiales, temporelles et spatio-temporelles de données environnementales représentées comme de semis de points. Les méthodes ici développées ont été appliquées aux jeux de données simulées autant qu'A des phénomènes environnementaux réels; nonobstant, seulement le cas des feux forestiers dans le Canton du Tessin (la Suisse) et celui de Portugal sont expliqués dans ce document. Normalement, les phénomènes environnementaux peuvent être modélisés comme des processus ponctuels stochastiques ou chaque événement, par ex. les point d'ignition des feux forestiers, est déterminé par son emplacement spatial et son occurrence dans le temps. De plus, des informations tels que la surface bru^lée, les causes d'ignition, l'utilisation du sol, les caractéristiques topographiques, climatiques et météorologiques, etc., peuvent aussi être utilisées pour caractériser le phénomène étudié. Par conséquent, la définition de la structure spatio-temporelle représente un outil puissant pour compren- dre la distribution du phénomène et sa corrélation avec des processus sous-jacents tels que les facteurs socio-économiques, environnementaux et météorologiques. De ce fait, nous proposons une méthodologie basée sur l'adaptation et l'application de mesures statistiques et fractales des processus ponctuels d'analyse global (par ex. l'indice de Morisita, la dimension fractale par comptage de boîtes, le formalisme multifractal et la fonction K de Ripley) et local (par ex. la statistique de scan). Des nombreuses mesures décrivant les structures spatio-temporelles de phénomènes environnementaux peuvent être trouvées dans la littérature. Néanmoins, la plupart de ces mesures sont de caractère global et ne considèrent pas de contraintes spatiales com- plexes, ainsi que la haute variabilité et la nature multivariée des événements. A cet effet, la méthodologie ici proposée prend en compte les complexités de l'espace géographique ou le phénomène a lieu, à travers de l'introduction du concept de Domaine de Validité et l'application des mesures d'analyse spatiale dans des données en présentant différentes contraintes géographiques. Cela permet l'évaluation du degré relatif d'agrégation spatiale/temporelle des structures du phénomène observé. En plus, exclusif au cas de feux forestiers, cette recherche propose aussi deux nouvelles méthodologies pour la définition et la cartographie des zones périurbaines, décrites comme des espaces anthropogéniques à proximité de la végétation sauvage ou de la forêt, et de la prédiction de la susceptibilité à l'ignition de feu. A cet égard, l'objectif principal de cette Thèse a été d'effectuer une recherche statistique/géospatiale avec une forte application dans des cas réels, pour analyser et décrire des phénomènes environnementaux complexes aussi bien que surmonter des problèmes méthodologiques non résolus relatifs à la caractérisation des structures spatio-temporelles, particulièrement, celles des occurrences de feux forestières. Ainsi, cette Thèse fournit une réponse à la demande croissante de la gestion et du monitoring environnemental pour le déploiement d'outils d'évaluation des risques et des dangers naturels et anthro- pogéniques. Les majeures contributions de ce travail ont été présentées aux conférences nationales et internationales, et ont été aussi publiées dans 5 revues internationales avec comité de lecture. Des collaborations nationales et internationales ont été aussi établies et accomplies avec succès.

Reconstruction and analysis of surface variation using photometric stereo

In many industrial applications, accurate and fast surface reconstruction is essential for quality control. Variation in surface finishing parameters, such as surface roughness, can reflect defects in a manufacturing process, non-optimal product operational efficiency, and reduced life expectancy of the product. This thesis considers reconstruction and analysis of high-frequency variation, that is roughness, on planar surfaces. Standard roughness measures in industry are calculated from surface topography. A fast and non-contact method to obtain surface topography is to apply photometric stereo in the estimation of surface gradients and to reconstruct the surface by integrating the gradient fields. Alternatively, visual methods, such as statistical measures, fractal dimension and distance transforms, can be used to characterize surface roughness directly from gray-scale images. In this thesis, the accuracy of distance transforms, statistical measures, and fractal dimension are evaluated in the estimation of surface roughness from gray-scale images and topographies. The results are contrasted to standard industry roughness measures. In distance transforms, the key idea is that distance values calculated along a highly varying surface are greater than distances calculated along a smoother surface. Statistical measures and fractal dimension are common surface roughness measures. In the experiments, skewness and variance of brightness distribution, fractal dimension, and distance transforms exhibited strong linear correlations to standard industry roughness measures. One of the key strengths of photometric stereo method is the acquisition of higher frequency variation of surfaces. In this thesis, the reconstruction of planar high-frequency varying surfaces is studied in the presence of imaging noise and blur. Two Wiener filterbased methods are proposed of which one is optimal in the sense of surface power spectral density given the spectral properties of the imaging noise and blur. Experiments show that the proposed methods preserve the inherent high-frequency variation in the reconstructed surfaces, whereas traditional reconstruction methods typically handle incorrect measurements by smoothing, which dampens the high-frequency variation.

Polyphenol intake and mortality risk: a re-analysis of the PREDIMED trial

Background: Polyphenols may lower the risk of cardiovascular disease (CVD) and other chronic diseases due to their antioxidant and anti-inflammatory properties, as well as their beneficial effects on blood pressure, lipids and insulin resistance. However, no previous epidemiological studies have evaluated the relationship between the intake of total polyphenols intake and polyphenol subclasses with overall mortality. Our aim was to evaluate whether polyphenol intake is associated with all-cause mortality in subjects at high cardiovascular risk. Methods: We used data from the PREDIMED study, a 7,447-participant, parallel-group, randomized, multicenter, controlled five-year feeding trial aimed at assessing the effects of the Mediterranean Diet in primary prevention of cardiovascular disease. Polyphenol intake was calculated by matching food consumption data from repeated food frequency questionnaires (FFQ) with the Phenol-Explorer database on the polyphenol content of each reported food. Hazard ratios (HR) and 95% confidence intervals (CI) between polyphenol intake and mortality were estimated using time-dependent Cox proportional hazard models. Results: Over an average of 4.8 years of follow-up, we observed 327 deaths. After multivariate adjustment, we found a 37% relative reduction in all-cause mortality comparing the highest versus the lowest quintiles of total polyphenol intake (hazard ratio (HR) = 0.63; 95% CI 0.41 to 0.97; P for trend = 0.12). Among the polyphenol subclasses, stilbenes and lignans were significantly associated with reduced all-cause mortality (HR =0.48; 95% CI 0.25 to 0.91; P for trend = 0.04 and HR = 0.60; 95% CI 0.37 to 0.97; P for trend = 0.03, respectively), with no significant associations apparent in the rest (flavonoids or phenolic acids). Conclusions: Among high-risk subjects, those who reported a high polyphenol intake, especially of stilbenes and lignans, showed a reduced risk of overall mortality compared to those with lower intakes. These results may be useful to determine optimal polyphenol intake or specific food sources of polyphenols that may reduce the risk of all-cause mortality.

Calculation of the variance in surveys of the economic climate

Public opinion surveys have become progressively incorporated into systems of official statistics. Surveys of the economic climate are usually qualitative because they collect opinions of businesspeople and/or experts about the long-term indicators described by a number of variables. In such cases the responses are expressed in ordinal numbers, that is, the respondents verbally report, for example, whether during a given trimester the sales or the new orders have increased, decreased or remained the same as in the previous trimester. These data allow to calculate the percent of respondents in the total population (results are extrapolated), who select every one of the three options. Data are often presented in the form of an index calculated as the difference between the percent of those who claim that a given variable has improved in value and of those who claim that it has deteriorated.