Regressão Simplex aplicada a delineamentos de mistura e utilização do Algoritmo Boosting

In the composition of this work are present two parts. The first part contains the theory used. The second part contains the two articles. The first article examines two models of the class of generalized linear models for analyzing a mixture experiment, which studied the effect of different diets consist of fat, carbohydrate, and fiber on tumor expression in mammary glands of female rats, given by the ratio mice that had tumor expression in a particular diet. Mixture experiments are characterized by having the effect of collinearity and smaller sample size. In this sense, assuming normality for the answer to be maximized or minimized may be inadequate. Given this fact, the main characteristics of logistic regression and simplex models are addressed. The models were compared by the criteria of selection of models AIC, BIC and ICOMP, simulated envelope charts for residuals of adjusted models, odds ratios graphics and their respective confidence intervals for each mixture component. It was concluded that first article that the simplex regression model showed better quality of fit and narrowest confidence intervals for odds ratio. The second article presents the model Boosted Simplex Regression, the boosting version of the simplex regression model, as an alternative to increase the precision of confidence intervals for the odds ratio for each mixture component. For this, we used the Monte Carlo method for the construction of confidence intervals. Moreover, it is presented in an innovative way the envelope simulated chart for residuals of the adjusted model via boosting algorithm. It was concluded that the Boosted Simplex Regression model was adjusted successfully and confidence intervals for the odds ratio were accurate and lightly more precise than the its maximum likelihood version.

Do the Genetic or Environmental Determinants of Anxiety and Depression Change with Age? A Longitudinal Study of Australian Twins

Because the determinants of anxiety and depression in late adolescence and early adulthood may differ from those in later life, we investigated the temporal stability and magnitude of genetic and environmental correlates of symptoms of anxiety and depression across the life span. Data were collected from a population-based Australian sample of 4364 complete twin pairs and 777 singletons aged 20 to 96 years who were followed-up over three studies between 1980 and 1996. Each study contained the 14-item self-report DSSI/sAD scale which was used to measure recently experienced symptoms of anxiety and depression. Symptom scores were then divided and assigned to age intervals according to each subject's age at time of participation. We fitted genetic simplex models to take into account the longitudinal nature of the data. For male anxiety and depression, the best fitting simplex models comprised a single genetic innovation at age 20 which was transmitted, and explained genetic variation in anxiety and depression at ages 30, 40, 50 and 60. Most of the lifetime genetic variation in female anxiety and depression could also be explained by innovations at age 20 which were transmitted to all other ages; however, there were also smaller age-dependent genetic innovations at 30 for anxiety and at 40 and 70 for depression. Although the genetic determinants of anxiety and depression appear relatively stable across the life-span for males and females, there is some evidence to support additional mid-life and late age gene action in females for depression. The fact that mid-life onset for anxiety occurs one decade before depression is also consistent with a causal relationship (anxiety leading to depression) between these conditions. These findings have significance for large scale depression prevention projects.

Genetic time-series analysis identifies a major QTL for in vivo alcohol metabolism not predicted by in vitro studies of structural protein polymorphism at the ADH1B or ADH1C loci

After ingestion of a standardized dose of ethanol, alcohol concentrations were assessed, over 3.5 hours from blood (six readings) and breath (10 readings) in a sample of 412 MZ and DZ twins who took part in an Alcohol Challenge Twin Study (ACTS). Nearly all participants were subsequently genotyped on two polymorphic SNPs in the ADH1B and ADH1C loci known to affect in vitro ADH activity. In the DZ pairs, 14 microsatellite markers covering a 20.5 cM region on chromosome 4 that includes the ADH gene family were assessed, Variation in the timed series of autocorrelated blood and breath alcohol readings was studied using a bivariate simplex design. The contribution of a quantitative trait locus (QTL) or QTL's linked to the ADH region was estimated via a mixture of likelihoods weighted by identity-by-descent probabilities. The effects of allelic substitution at the ADH1B and ADH1C loci were estimated in the means part of the model simultaneously with the effects sex and age. There was a major contribution to variance in alcohol metabolism due to a QTL which accounted for about 64% of the additive genetic covariation common to both blood and breath alcohol readings at the first time point. No effects of the ADH1B*47His or ADH1C*349Ile alleles on in vivo metabolism were observed, although these have been shown to have major effects in vitro. This implies that there is a major determinant of variation for in vivo alcohol metabolism in the ADH region that is not accounted for by these polymorphisms. Earlier analyses of these data suggested that alcohol metabolism is related to drinking behavior and imply that this QTL may be protective against alcohol dependence.

OPUS: interactive software for solving linear programming models using the simplex algorithm

Includes bibliography

Immunization with DNA vaccines encoding glycoprotein D or glycoprotein B, alone or in combination, induces protective immunity in animal models of herpes simplex virus-2 disease.

DNA vaccines expressing herpes simplex virus type 2 (HSV-2) full-length glycoprotein D (gD), or a truncated form of HSV-2 glycoprotein B (gB) were evaluated for protective efficacy in two experimental models of HSV-2 infection. Intramuscular (i.m.) injection of mice showed that each construction induced neutralizing serum antibodies and protected the mice from lethal HSV-2 infection. Dose-titration studies showed that low doses (< or = 1 microgram) of either DNA construction induced protective immunity, and that a single immunization with the gD construction was effective. The two DNAs were then tested in a low-dosage combination in guinea pigs. Immune sera from DNA-injected animals had antibodies to both gD and gB, and virus neutralizing activity. When challenged by vaginal infection with HSV-2, the DNA-immunized animals were significantly protected from primary genital disease.

Some novel techniques of parameter estimation for the dynamical models in biological systems

Inverse problems based on using experimental data to estimate unknown parameters of a system often arise in biological and chaotic systems. In this paper, we consider parameter estimation in systems biology involving linear and non-linear complex dynamical models, including the Michaelis–Menten enzyme kinetic system, a dynamical model of competence induction in Bacillus subtilis bacteria and a model of feedback bypass in B. subtilis bacteria. We propose some novel techniques for inverse problems. Firstly, we establish an approximation of a non-linear differential algebraic equation that corresponds to the given biological systems. Secondly, we use the Picard contraction mapping, collage methods and numerical integration techniques to convert the parameter estimation into a minimization problem of the parameters. We propose two optimization techniques: a grid approximation method and a modified hybrid Nelder–Mead simplex search and particle swarm optimization (MH-NMSS-PSO) for non-linear parameter estimation. The two techniques are used for parameter estimation in a model of competence induction in B. subtilis bacteria with noisy data. The MH-NMSS-PSO scheme is applied to a dynamical model of competence induction in B. subtilis bacteria based on experimental data and the model for feedback bypass. Numerical results demonstrate the effectiveness of our approach.

Supervised latent dirichlet allocation models for efficient activity representation

Local spatio-temporal features with a Bag-of-visual words model is a popular approach used in human action recognition. Bag-of-features methods suffer from several challenges such as extracting appropriate appearance and motion features from videos, converting extracted features appropriate for classification and designing a suitable classification framework. In this paper we address the problem of efficiently representing the extracted features for classification to improve the overall performance. We introduce two generative supervised topic models, maximum entropy discrimination LDA (MedLDA) and class- specific simplex LDA (css-LDA), to encode the raw features suitable for discriminative SVM based classification. Unsupervised LDA models disconnect topic discovery from the classification task, hence yield poor results compared to the baseline Bag-of-words framework. On the other hand supervised LDA techniques learn the topic structure by considering the class labels and improve the recognition accuracy significantly. MedLDA maximizes likelihood and within class margins using max-margin techniques and yields a sparse highly discriminative topic structure; while in css-LDA separate class specific topics are learned instead of common set of topics across the entire dataset. In our representation first topics are learned and then each video is represented as a topic proportion vector, i.e. it can be comparable to a histogram of topics. Finally SVM classification is done on the learned topic proportion vector. We demonstrate the efficiency of the above two representation techniques through the experiments carried out in two popular datasets. Experimental results demonstrate significantly improved performance compared to the baseline Bag-of-features framework which uses kmeans to construct histogram of words from the feature vectors.

THE EFFECTS OF SURFACTANT ON SIMPLEX NOZZLE SPRAY BEHAVIOR AND ITS COMPARISON TO LIQUID FUELS

Pressure-swirl nozzles (simplex nozzles) are used in various field applications such as aero-engines, power generation, spray painting and agricultural irrigation. For this particular nozzle, research in the past decade has dealt with the development of numerical models for predicting droplet distribution profiles. Although these results have been valuable, the experimental results have been contradictory, therefore fundamental understanding of the influence of properties in nozzle is important. This paper experimentally investigates the effect of surfactants on breakup and coalescence. Since most of the fuels and biofuels have low surface tension compared to water, a comparative analysis between a surfactant solution and a liquid fuel is imperative. For this experimental study, a simplex nozzle characterized as flow number 0.4 will be utilized. The injection pressures will range from 0.3 - 4Mpa while altering the surface tension from 72 to 28mN/m. By applying Phase Doppler Particle Anemometry (PDPA) which is a non-intrusive laser diagnostic technique, the differences in spray characteristics due to spray surface tension can be highlighted. The average droplet diameter decreases for a low surface tension fluid in the axial direction in comparison to pure water. The average velocity of droplets is surprisingly lower in the same spray zone. Measurements made in the radial direction show no significant changes, but at the locations close to the nozzle, water droplets have larger diameter and velocity. The results indicate the breakup and coalescence regimes have been altered when surface tension is lowered. A decrease in surface tension alters the breakup length while increasing the spray angle. Moreover, higher injection pressure shortens the breakup length and decrease in overall diameter of the droplets. By performing this experimental study the fundamentals of spray dynamics, such as spray formation, liquid breakup length, and droplet breakup regimes can be observed as a function of surface tension and how a surrogate fuel compares with a real fuel for experimental purposes. This knowledge potentially will lead to designing a better atomizer or new biofuels.

A new distribution on the simplex containing the Dirichlet family

The Dirichlet family owes its privileged status within simplex distributions to easyness of interpretation and good mathematical properties. In particular, we recall fundamental properties for the analysis of compositional data such as closure under amalgamation and subcomposition. From a probabilistic point of view, it is characterised (uniquely) by a variety of independence relationships which makes it indisputably the reference model for expressing the non trivial idea of substantial independence for compositions. Indeed, its well known inadequacy as a general model for compositional data stems from such an independence structure together with the poorness of its parametrisation. In this paper a new class of distributions (called Flexible Dirichlet) capable of handling various dependence structures and containing the Dirichlet as a special case is presented. The new model exhibits a considerably richer parametrisation which, for example, allows to model the means and (part of) the variance-covariance matrix separately. Moreover, such a model preserves some good mathematical properties of the Dirichlet, i.e. closure under amalgamation and subcomposition with new parameters simply related to the parent composition parameters. Furthermore, the joint and conditional distributions of subcompositions and relative totals can be expressed as simple mixtures of two Flexible Dirichlet distributions. The basis generating the Flexible Dirichlet, though keeping compositional invariance, shows a dependence structure which allows various forms of partitional dependence to be contemplated by the model (e.g. non-neutrality, subcompositional dependence and subcompositional non-invariance), independence cases being identified by suitable parameter configurations. In particular, within this model substantial independence among subsets of components of the composition naturally occurs when the subsets have a Dirichlet distribution

Experimental design on the simplex

Optimum experimental designs depend on the design criterion, the model and the design region. The talk will consider the design of experiments for regression models in which there is a single response with the explanatory variables lying in a simplex. One example is experiments on various compositions of glass such as those considered by Martin, Bursnall, and Stillman (2001). Because of the highly symmetric nature of the simplex, the class of models that are of interest, typically Scheff´e polynomials (Scheff´e 1958) are rather different from those of standard regression analysis. The optimum designs are also rather different, inheriting a high degree of symmetry from the models. In the talk I will hope to discuss a variety of modes for such experiments. Then I will discuss constrained mixture experiments, when not all the simplex is available for experimentation. Other important aspects include mixture experiments with extra non-mixture factors and the blocking of mixture experiments. Much of the material is in Chapter 16 of Atkinson, Donev, and Tobias (2007). If time and my research allows, I would hope to finish with a few comments on design when the responses, rather than the explanatory variables, lie in a simplex. References Atkinson, A. C., A. N. Donev, and R. D. Tobias (2007). Optimum Experimental Designs, with SAS. Oxford: Oxford University Press. Martin, R. J., M. C. Bursnall, and E. C. Stillman (2001). Further results on optimal and efficient designs for constrained mixture experiments. In A. C. Atkinson, B. Bogacka, and A. Zhigljavsky (Eds.), Optimal Design 2000, pp. 225–239. Dordrecht: Kluwer. Scheff´e, H. (1958). Experiments with mixtures. Journal of the Royal Statistical Society, Ser. B 20, 344–360. 1

Modelagem matemática: uma abordagem do método gráfico e do método simplex na resolução de problemas de otimização

Pós-graduação em Matemática em Rede Nacional - IBILCE

Molecular basis oh herpes simplex virus entry into the cell and retargeting of the viral tropism for the design of oncolytic herpesviruses

Herpes simplex virus 1 (HSV-1) infects oral epitelial cells, then spreads to the nerve endings and estabilishes latency in sensory ganglia, from where it may, or may not reactivate. Diseases caused by virus reactivation include mild diseases such as muco-cutaneous lesions, and more severe, and even life-threatening encephalitis, or systemic infections affecting diverse organs. Herpes simplex virus represents the most comprehensive example of virus receptor interaction in Herpesviridae family, and the prototype virus encoding multipartite entry genes. In fact, it encodes 11-12 glycoproteins and a number of additional membrane proteins: five of these proteins play key roles in virus entry into subsceptible cells. Thus, glycoprotein B (gB) and glycoprotein C (gC) interact with heparan sulfate proteoglycan to enable initial attachment to cell surfaces. In the next step, in the entry cascade, gD binds a specific surface receptor such as nectin1 or HVEM. The interaction of glycoprotein D with the receptor alters the conformation of gD to enable the activation of gB, glycoprotein H, and glycoprotein L, a trio of glycoproteins that execute the fusion of the viral envelope with the plasma membrane. In this thesis, I described two distinct projects: I. The retargeting of viral tropism for the design of oncolytic Herpesviruses: • capable of infecting cells through the human epitelial growth factor receptor 2 (HER2), overexpressed in highly malignant mammary and ovarian tumors and correlates with a poor prognosis; • detargeted from its natural receptors, HVEM and nectin1. To this end, we inserted a ligand to HER2 in gD. Because HER2 has no natural ligand, the selected ligand was a single chain antibody (scFv) derived from MAb4D5 (monoclonal antibody to HER2), herein designated scHER2. All recombinant viruses were targeted to HER2 receptor, but only two viruses (R-LM113 and R-LM249) were completely detargeted from HVEM and nectin1. To engineer R-LM113, we removed a large portion at the N-terminus of gD (from aa 6 to aa 38) and inserted scHER2 sequence plus 9-aa serine-glycine flexible linker at position 39. On the other hand, to engineer R-LM249, we replaced the Ig-folded core of gD (from aa 61 to aa 218) with scHER2 flanked by Ser-Gly linkers. In summary, these results provide evidence that: i. gD can tolerate an insert almost as big as gD itself; ii. the Ig-like domain of gD can be removed; iii. the large portion at the N-terminus of gD (from aa 6 to aa 38) can be removed without loss of key function; iv. R-LM113 and R-LM249 recombinants are ready to be assayed in animal models of mammary and ovary tumour. This finding and the avaibility of a large number of scFv greatly increase the collection of potential receptors to which HSV can be redirected. II. The production and purification of recombinant truncated form of the heterodimer gHgL. We cloned a stable insect cell line expressing a soluble form of gH in complex with gL under the control of a metalloprotein inducible promoter and purified the heterodimer by means of ONE-STrEP-tag system by IBA. With respect to biological function, the purified heterodimer is capable: • of reacting to antibodies that recognize conformation dependent epitopes and neutralize virion infectivity; • of binding a variety cells at cell surface. No doubt, the availability of biological active purified gHgL heterodimer, in sufficient quantities, will speed up the efforts to solve its crystal structure and makes it feasible to identify more clearly whether gHgL has a cellular partner, and what is the role of this interaction on virus entry.

Genetic engineering and preclinical evaluation of oncolytic herpes simplex viruses retargeted to cancer-specific receptors

Oncolytic virotherapy exploits the ability of viruses to infect and kill cells. It is suitable as treatment for tumors that are not accessible by surgery and/or respond poorly to the current therapeutic approach. HSV is a promising oncolytic agent. It has a large genome size able to accommodate large transgenes and some attenuated oncolytic HSVs (oHSV) are already in clinical trials phase I and II. The aim of this thesis was the generation of HSV-1 retargeted to tumor-specific receptors and detargeted from HSV natural receptors, HVEM and Nectin-1. The retargeting was achieved by inserting a specific single chain antibody (scFv) for the tumor receptor selected inside the HSV glycoprotein gD. In this research three tumor receptors were considered: epidermal growth factor receptor 2 (HER2) overexpressed in 25-30% of breast and ovarian cancers and gliomas, prostate specific membrane antigen (PSMA) expressed in prostate carcinomas and in neovascolature of solid tumors; and epidermal growth factor receptor variant III (EGFRvIII). In vivo studies on HER2 retargeted viruses R-LM113 and R-LM249 have demonstrated their high safety profile. For R-LM249 the antitumor efficacy has been highlighted by target-specific inhibition of the growth of human tumors in models of HER2-positive breast and ovarian cancer in nude mice. In a murine model of HER2-positive glioma in nude mice, R-LM113 was able to significantly increase the survival time of treated mice compared to control. Up to now, PSMA and EGFRvIII viruses (R-LM593 and R-LM613) are only characterized in vitro, confirming the specific retargeting to selected targets. This strategy has proved to be generally applicable to a broad spectrum of receptors for which a single chain antibody is available.