936 resultados para leave one out cross validation
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As análises biplot que utilizam os modelos de efeitos principais aditivos com inter- ação multiplicativa (AMMI) requerem matrizes de dados completas, mas, frequentemente os ensaios multiambientais apresentam dados faltantes. Nesta tese são propostas novas metodologias de imputação simples e múltipla que podem ser usadas para analisar da- dos desbalanceados em experimentos com interação genótipo por ambiente (G×E). A primeira, é uma nova extensão do método de validação cruzada por autovetor (Bro et al, 2008). A segunda, corresponde a um novo algoritmo não-paramétrico obtido por meio de modificações no método de imputação simples desenvolvido por Yan (2013). Também é incluído um estudo que considera sistemas de imputação recentemente relatados na literatura e os compara com o procedimento clássico recomendado para imputação em ensaios (G×E), ou seja, a combinação do algoritmo de Esperança-Maximização com os modelos AMMI ou EM-AMMI. Por último, são fornecidas generalizações da imputação simples descrita por Arciniegas-Alarcón et al. (2010) que mistura regressão com aproximação de posto inferior de uma matriz. Todas as metodologias têm como base a decomposição por valores singulares (DVS), portanto, são livres de pressuposições distribucionais ou estruturais. Para determinar o desempenho dos novos esquemas de imputação foram realizadas simulações baseadas em conjuntos de dados reais de diferentes espécies, com valores re- tirados aleatoriamente em diferentes porcentagens e a qualidade das imputações avaliada com distintas estatísticas. Concluiu-se que a DVS constitui uma ferramenta útil e flexível na construção de técnicas eficientes que contornem o problema de perda de informação em matrizes experimentais.
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As doenças tropicais negligenciadas (DTNs) causam um imenso sofrimento para a pessoa acometida e em muitos casos podem levar o indivíduo a morte. Elas representam um obstáculo devastador para a saúde e continuam a ser um sério impedimento para a redução da pobreza e desenvolvimento socioeconômico. Das 17 doenças desse grupo, a leishmaniose, incluindo a leishmaniose cutânea, tem grande destaque devido sua alta incidência, os gastos para o tratamento e as complicações geradas em processos de coinfecção. Ainda mais agravante, os investimentos direcionados ao controle, combate e principalmente a inovação em novos produtos é ainda muito limitado. Atualmente, a academia tem um importante papel na luta contra essas doenças através da busca de novos alvos terapêuticos e também de novas moléculas com potencial terapêutico. É nesse contexto que esse projeto teve como meta a implantação de uma plataforma para a identificação de moléculas com atividade leishmanicida. Como alvo terapêutico, optamos pela utilização da enzima diidroorotato desidrogenase de Leishmania Viannia braziliensis (LbDHODH), enzima de extrema importância na síntese de novo de nucleotídeos de pirimidina, cuja principal função é converter o diidroorotato em orotato. Esta enzima foi clonada, expressa e purificada com sucesso em nosso laboratório. Os estudos permitiram que a enzima fosse caracterizada cineticamente e estruturalmente via cristalografia de raios- X. Os primeiros ensaios inibitórios foram realizados com o orotato, produto da catálise e inibidor natural da enzima. O potencial inibitório do orotato foi mensurado através da estimativa do IC50 e a interação proteína-ligante foi caracterizada através de estudos cristalográficos. Estratégias in silico e in vitro foram utilizadas na busca de ligantes, através das quais foram identificados inibidores para a enzima LbDHODH. Ensaios de validação cruzada, utilizando a enzima homóloga humana, permitiram identificar os ligantes com maior índice de seletividade que tiveram seu potencial leishmanicida avaliado in vitro contra as formas promastigota e amastigota de Leishmania braziliensis. A realização do presente projeto permitiu a identificação de uma classe de ligantes que apresentam atividade seletiva contra LbDHODH e que será utilizada no planejamento de futuras gerações de moléculas com atividade terapêutica para o tratamento da leishmaniose. Além disso, a plataforma de ensaios otimizada permitirá a avaliação de novos grupos de moléculas como uma importante estratégia na busca por novos tratamentos contra a leishmaniose
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Purpose. To assess in a sample of normal, keratoconic, and keratoconus (KC) suspect eyes the performance of a set of new topographic indices computed directly from the digitized images of the Placido rings. Methods. This comparative study was composed of a total of 124 eyes of 106 patients from the ophthalmic clinics Vissum Alicante and Vissum Almería (Spain) divided into three groups: control group (50 eyes), KC group (50 eyes), and KC suspect group (24 eyes). In all cases, a comprehensive examination was performed, including the corneal topography with a Placidobased CSO topography system. Clinical outcomes were compared among groups, along with the discriminating performance of the proposed irregularity indices. Results. Significant differences at level 0.05 were found on the values of the indices among groups by means of Mann-Whitney-Wilcoxon nonparametric test and Fisher exact test. Additional statistical methods, such as receiver operating characteristic analysis and K-fold cross validation, confirmed the capability of the indices to discriminate between the three groups. Conclusions. Direct analysis of the digitized images of the Placido mires projected on the cornea is a valid and effective tool for detection of corneal irregularities. Although based only on the data from the anterior surface of the cornea, the new indices performed well even when applied to the KC suspect eyes. They have the advantage of simplicity of calculation combined with high sensitivity in corneal irregularity detection and thus can be used as supplementary criteria for diagnosing and grading KC that can be added to the current keratometric classifications.
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We examined the psychometric properties of the School Attitude Assessment Survey–Revised in a Spanish population (n = 1,398). Confirmatory factor analysis procedures supported the instrument’s five-factor structure. The results of discriminant analysis demonstrated the predictive power of the School Attitude Assessment Survey–Revised scales as regards academic performance. Implications for education and assessment are discussed.
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Numerical modelling methodologies are important by their application to engineering and scientific problems, because there are processes where analytical mathematical expressions cannot be obtained to model them. When the only available information is a set of experimental values for the variables that determine the state of the system, the modelling problem is equivalent to determining the hyper-surface that best fits the data. This paper presents a methodology based on the Galerkin formulation of the finite elements method to obtain representations of relationships that are defined a priori, between a set of variables: y = z(x1, x2,...., xd). These representations are generated from the values of the variables in the experimental data. The approximation, piecewise, is an element of a Sobolev space and has derivatives defined in a general sense into this space. The using of this approach results in the need of inverting a linear system with a structure that allows a fast solver algorithm. The algorithm can be used in a variety of fields, being a multidisciplinary tool. The validity of the methodology is studied considering two real applications: a problem in hydrodynamics and a problem of engineering related to fluids, heat and transport in an energy generation plant. Also a test of the predictive capacity of the methodology is performed using a cross-validation method.
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Tese de mestrado, Bioinformática e Biologia Computacional (Bioinformática), Universidade de Lisboa, Faculdade de Ciências, 2016
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A staggering one out of every four young people is presently unemployed in Spain. And comparable numbers in Greece, Portugal and Italy are hardly more encouraging. Germany, on the other hand, enjoys a historically low youth unemployment rate of 8% and is experiencing skill shortages in some occupations. Against this background, this Commentary calls upon the European Commission to use its considerable strength and know-how in bringing partners and stakeholders together in order to facilitate the necessary infrastructure to allow better matching across borders of workers and employers. The authors point to the June European Council meeting as offering a good occasion to launch initiatives to this effect.
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Individual analysis of functional Magnetic Resonance Imaging (fMRI) scans requires user-adjustment of the statistical threshold in order to maximize true functional activity and eliminate false positives. In this study, we propose a novel technique that uses radiomic texture analysis (TA) features associated with heterogeneity to predict areas of true functional activity. Scans of 15 right-handed healthy volunteers were analyzed using SPM8. The resulting functional maps were thresholded to optimize visualization of language areas, resulting in 116 regions of interests (ROIs). A board-certified neuroradiologist classified different ROIs into Expected (E) and Non-Expected (NE) based on their anatomical locations. TA was performed using the mean Echo-Planner Imaging (EPI) volume, and 20 rotation-invariant texture features were obtained for each ROI. Using forward stepwise logistic regression, we built a predictive model that discriminated between E and NE areas of functional activity, with a cross-validation AUC and success rate of 79.84% and 80.19% respectively (specificity/sensitivity of 78.34%/82.61%). This study found that radiomic TA of fMRI scans may allow for determination of areas of true functional activity, and thus eliminate clinician bias.
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Thesis (Master's)--University of Washington, 2016-06
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Thesis (Ph.D.)--University of Washington, 2016-06
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Thesis (Master's)--University of Washington, 2016-06
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Thesis (Master's)--University of Washington, 2016-06
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Background While much attention has been given to the prediction of violent offending behaviour amongst people with psychotic disorders, less attention has been given to the fact that these same individuals are often the victims of violence. In this paper, we examine victimisation amongst participants in a prevalence study of psychosis, and describe demographic and clinical correlates of victimisation. Method The study was based on the Australian National Survey of Mental Health and Wellbeing - Low Prevalence (Psychotic) Disorders. The participants were asked if they had been a victim of violence in the previous year. The association between selected demographic and clinical variables and being a victim of violence was examined using logistic regression. Results Of the 962 individuals with psychosis, 172 reported being a victim of violence in the past 12 months (17.9 %). The odds of being a victim were increased in those who: (a) were female, (b) were homeless, (c) had a lifetime history of substance abuse, (d) had been arrested in the previous 12 months, (e) had poorer social and occupational function, and (f) had higher scores on the disorganisation summary score. Conclusions Clinicians should remain mindful that one out of every six individuals with a psychotic disorder reports being a victim of violence in the previous year. Models of care that address issues related to symptom relief, accommodation, and exposure to high-crime areas may reduce the rates of victimisation amongst those with psychotic disorders.
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Objectives: Obesity is a disease with excess body fat where health is adversely affected. Therefore it is prudent to make the diagnosis of obesity based on the measure of percentage body fat. Body composition of a group of Australian children of Sri Lankan origin were studied to evaluate the applicability of some bedside techniques in the measurement of percentage body fat. Methods: Height (H) and weight (W) was measured and BMI (W/H-2) calculated. Bioelectrical impedance analysis (BIA) was measured using tetra polar technique with an 800 mu A current of 50 Hz frequency. Total body water was used as a reference method and was determined by deuterium dilution and fat free mass and hence fat mass (FM) derived using age and gender specific constants. Percentage FM was estimated using four predictive equations, which used BIA and anthropometric measurements. Results: Twenty-seven boys and 15 girls were studied with mean ages being 9.1 years and 9.6 years, respectively. Girls had a significantly higher FM compared to boys. The mean percentage FM of boys (22.9 +/- 8.7%) was higher than the limit for obesity and for girls (29.0 +/- 6.0%) it was just below the cut-off. BMI was comparatively low. All but BIA equation in boys under estimated the percentage FM. The impedance index and weight showed a strong association with total body water (r(2)= 0.96, P < 0.001). Except for BIA in boys all other techniques under diagnosed obesity. Conclusions: Sri Lankan Australian children appear to have a high percentage of fat with a low BMI and some of the available indirect techniques are not helpful in the assessment of body composition. Therefore ethnic and/or population specific predictive equations have to be developed for the assessment of body composition, especially in a multicultural society using indirect methods such as BIA or anthropometry.
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Therapeutic monitoring with dosage individualization of sirolimus drug therapy is standard clinical practice for organ transplant recipients. For several years sirolimus monitoring has been restricted as a result of lack of an immunoassay. The recent reintroduction of the microparticle enzyme immunoassay (MEIA (R)) for sirolimus on the IMx (R) analyser has the potential to address this situation. This Study, using patient samples, has compared the MEIA (R) sirolimus method with an established HPLC-tandem mass spectrometry method (HPLC-MS/MS). An established HPLC-UV assay was used for independent cross-validation. For quality control materials (5, 11, 22 mu g/L), the MEIA (R) showed acceptable validation criteria based on intra-and inter-run precision (CV) and accuracy (bias) of < 8% and < 13%, respectively. The lower limit of quantitation was found to be approximately 3 mu g/L. The performance of the immunoassay was compared with HPLC-MS/MS using EDTA whole-blood samples obtained from various types of organ transplant recipients (n = 116). The resultant Deming regression line was: MEIA = 1.3 x HPLC-MS/MS+ 1.3 (r = 0.967, s(y/x) = 1) with a mean bias of 49.2% +/- 23.1 % (range, -2.4% to 128%; P < 0.001). The reason for the large and variable bias was not explored in this study, but the sirolimus-metabolite cross-reactivity with the MEIA (R) antibody could be a substantive contributing factor. Whereas the MEIA (R) sirolimus method may be an adjunct to sirolimus dosage individualization in transplant recipients, users must consider the implications of the substantial and variable bias when interpreting results. In selected patients where difficult clinical issues arise, reference to a specific chromatographic method may be required.