949 resultados para Discriminant analysis


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Background Depression symptomatology was assessed with the Beck Depression Inventory (BDI) in a sample of Jewish adolescents, in order to compare the frequency and severity of depression with non-Jewish adolescents as well as examine gender difference of the expression of depressive symptomatology. Method Subjects comprised 475 students from Jewish private schools, aged 13-17 years, who were compared with an age-matched non-Jewish sample (n = 899). Kendall`s definition was adopted to classify these adolescents according to level of depressive symptoms. The frequency of depression was calculated for ethnicity, gender and age strata. Discriminant analysis and principal component analysis were performed to assess the importance of depression-specific and non-specific items, along with the factor structure of the BDI, respectively. Results The overall mean score on the BDI in the Jewish and the non-Jewish sample was 9.0 (SD = 6.4) and 8.6 (SD = 7.2), respectively. Jewish girls and boys had comparable mean BDI scores, contrasting with non-Jewish sample, where girls complained more of depressive symptoms than boys (p < 0.001). The frequency of depression, adopting a BDI cutoff of 20, was 5.1% for the Jewish sample and 6.3% for the non-Jewish sample. The frequency of depression for Jewish girls and boys was 5.5% (SE = 1.4) and 4.6% (SE = 1.5), respectively. On the other hand, the frequency of depression for non-Jewish girls and boys was 8.4% (SE = 1.2) and 4.0% (SE = 1.0), respectively. The female/male ratio of frequency of BDI-depression was 1.2 in the Jewish sample, but non-Jewish girls were twice (2.1) as likely to report depression as boys. Discriminant analysis showed that the BDI highly discriminates depressive symptomatology among Jewish adolescents, and measured specific aspects of depression. Factor analysis revealed two meaningful factors for the total sample and each gender (cognitive-affective dimension and somatic dimension), evidencing a difference between Jewish boys and Jewish girls in the symptomatic expression of depression akin to non-Jewish counterparts. Conclusions Ethnic-cultural factor might play a role in the frequency, severity and symptomatic expression of depressive symptoms in Jewish adolescents. The lack of gender effect on depression, which might persist from adolescence to adulthood among Jewish people, should be investigated in prospective studies.

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In this paper, a novel statistical test is introduced to compare two locally stationary time series. The proposed approach is a Wald test considering time-varying autoregressive modeling and function projections in adequate spaces. The covariance structure of the innovations may be also time- varying. In order to obtain function estimators for the time- varying autoregressive parameters, we consider function expansions in splines and wavelet bases. Simulation studies provide evidence that the proposed test has a good performance. We also assess its usefulness when applied to a financial time series.

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In this paper we show the results of a comparison simulation study for three classification techniques: Multinomial Logistic Regression (MLR), No Metric Discriminant Analysis (NDA) and Linear Discriminant Analysis (LDA). The measure used to compare the performance of the three techniques was the Error Classification Rate (ECR). We found that MLR and LDA techniques have similar performance and that they are better than DNA when the population multivariate distribution is Normal or Logit-Normal. For the case of log-normal and Sinh(-1)-normal multivariate distributions we found that MLR had the better performance.

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Chagas disease is nowadays the most serious parasitic health problem. This disease is caused by Trypanosoma cruzi. The great number of deaths and the insufficient effectiveness of drugs against this parasite have alarmed the scientific community worldwide. In an attempt to overcome this problem, a model for the design and prediction of new antitrypanosomal agents was obtained. This used a mixed approach, containing simple descriptors based on fragments and topological substructural molecular design descriptors. A data set was made up of 188 compounds, 99 of them characterized an antitrypanosomal activity and 88 compounds that belong to other pharmaceutical categories. The model showed sensitivity, specificity and accuracy values above 85%. Quantitative fragmental contributions were also calculated. Then, and to confirm the quality of the model, 15 structures of molecules tested as antitrypanosomal compounds (that we did not include in this study) were predicted, taking into account the information on the abovementioned calculated fragmental contributions. The model showed an accuracy of 100% which means that the ""in silico"" methodology developed by our team is promising for the rational design of new antitrypanosomal drugs. (C) 2009 Wiley Periodicals, Inc. J Comput Chem 31: 882-894. 2010

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The increasing resistance of Mycobacterium tuberculosis to the existing drugs has alarmed the worldwide scientific community. In an attempt to overcome this problem, two models for the design and prediction of new antituberculosis agents were obtained. The first used a mixed approach, containing descriptors based on fragments and the topological substructural molecular design approach (TOPS-MODE) descriptors. The other model used a combination of two-dimensional (2D) and three-dimensional (3D) descriptors. A data set of 167 compounds with great structural variability, 72 of them antituberculosis agents and 95 compounds belonging to other pharmaceutical categories, was analyzed. The first model showed sensitivity, specificity, and accuracy values above 80% and the second one showed values higher than 75% for these statistical indices. Subsequently, 12 structures of imidazoles not included in this study were designed, taking into account the two models. In both cases accuracy was 100%, showing that the methodology in silico developed by us is promising for the rational design of antituberculosis drugs.

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Os modelos hazard, também conhecidos por modelos de tempo até a falência ou duração, são empregados para determinar quais variáveis independentes têm maior poder explicativo na previsão de falência de empresas. Consistem em uma abordagem alternativa aos modelos binários logit e probit, e à análise discriminante. Os modelos de duração deveriam ser mais eficientes que modelos de alternativas discretas, pois levam em consideração o tempo de sobrevivência para estimar a probabilidade instantânea de falência de um conjunto de observações sobre uma variável independente. Os modelos de alternativa discreta tipicamente ignoram a informação de tempo até a falência, e fornecem apenas a estimativa de falhar em um dado intervalo de tempo. A questão discutida neste trabalho é como utilizar modelos hazard para projetar taxas de inadimplência e construir matrizes de migração condicionadas ao estado da economia. Conceitualmente, o modelo é bastante análogo às taxas históricas de inadimplência e mortalidade utilizadas na literatura de crédito. O Modelo Semiparamétrico Proporcional de Cox é testado em empresas brasileiras não pertencentes ao setor financeiro, e observa-se que a probabilidade de inadimplência diminui sensivelmente após o terceiro ano da emissão do empréstimo. Observa-se também que a média e o desvio-padrão das probabilidades de inadimplência são afetados pelos ciclos econômicos. É discutido como o Modelo Proporcional de Cox pode ser incorporado aos quatro modelos mais famosos de gestão de risco .de crédito da atualidade: CreditRisk +, KMV, CreditPortfolio View e CreditMetrics, e as melhorias resultantes dessa incorporação

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Este trabalho investiga basicamente a validade do Teste Illinois de Habilidades Psicolinguísticas -ITPA -instrumento de avaliação do desenvolvimento da linguagem infantil. Seus autores, S. Kirk e J.J. McCarthy (1961), utilizam o referencial teórico proposto por C. Osgood (1957), a ele incorporando o modelo derivado da Teoria da Informação, o que permite que, na prática clínica, o ITPA possa ser incluído no processo psicodiagnóstico como instrumento de avaliação dos problemas da comunicação em crianças entre três e dez anos. Os objetivos que conduzem e orientam o trabalho apresentado podem ser definidos em três níveis: 1) O que trata dos constructos e suas interrelaç6es -análise crítica da validade teóricado ITPA; 2) O que avalia sua condição de instrumento diagnóstico do desempenho escolar -sensibilidade discriminante do rendimento acadêmico; 3) O que trata da eficácia da prática psicopedagógica proposta pelo mesmo instrumento. O estudo sobre a validade teórica foi realizado com 931 crianças entre três e dez anos de idade, em processo de escolarização, frequentando creches, jardins de infância ou classes regulares da Rede de Ensino do Primeiro Grau no Município do Rio de Janeiro. Utilizou-se a técnica da Análise Fatorial, complementada por uma abordagem lógica que comprovaram algumas das dimensões propostas pelo referencial teórico de Kirk e McCarthy. Para a validade diagnóstica foram avaliadas 71 crianças com dificuldades no desempenho acadêmico, expressas através de conceitos de insuficiência ou deficiência de rendimento e seus resultados foram comparados com os de um subgrupo, aleatoriamente constituído de crianças que participaram do estudo anterior. Utilizou-se a técnica da Análise Discriminante chegando-se à seguinte conclusão: embora a validade de constructo do IIPA não tenha sido completamente confirmada num nível diagnóstico os resultados permitem identificar, com baixa margem de erro, as crianças que pertencem a um ou outro dos grupos de contraste. Quanto ao terceiro nível, foi feita ampla-revelação bibliográfica sobre investigações efetuadas com este instrumento no Brasil e no Exterior. Visou-se avaliar a eficácia da prática psicopedagógica utilizada quando desenvolvida à luz dos recursos de intervenção que o IIPA propõe. Concluiu-se que as pesquisas, até o presente momento efetuadas, não são suficientes para formar um juízo mais seguro da praxis educativa destinada à reabilitação das crianças com problemas da comunicação - o que constitui impedimento a seu desempenho acadêmico - em função das controvérsias que tais pesquisas apresentam.

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Thirty-six Madeira wine samples from Boal, Malvazia, Sercial and Verdelho white grape varieties were analyzed in order to estimate the free fraction of monoterpenols and C13 norisoprenoids (terpenoid compounds) using dynamic headspace solid phase micro-extraction (HS-SPME) technique coupled with gas chromatography–mass spectrometry (GC–MS). The average values from three vintages (1998–2000) show that these wines have characteristic profiles of terpenoid compounds. Malvazia wines exhibits the highest values of total free monoterpenols, contrary to Verdelho wines which had the lowest levels of terpenoids but produced the highest concentration of farnesol. The use of multivariate analysis techniques allows establishing relations between the compounds and the varieties under investigation. Principal component analysis (PCA) and linear discriminant analysis (LDA) were applied to the obtained matrix data. A good separation and classification power between the four groups as a function of their varietal origin was observed.

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Boal, Malvasia, Sercial and Verdelho are the main white grape varieties used in Madeira wine production. To estimate the free fraction of varietal aroma compounds of these varieties, 39 samples of musts were analysed to determine their content of monoterpenols and C13 norisoprenoids (terpenoids), using dynamic headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry. The r-values for linearity studies of the analytical method used, varied between 0.977 (nerolidol) and 0.999 (linalool). The repeatability for each compound varied between 2.5% (citronellol) and 11.8% (β-ionone). The mean values from three vintages (1998, 1999 and 2000) confirmed that these musts have differentiated contents of terpenoids. In opposition to Verdelho musts, Malvasia showed the highest free terpenoids content. In order to establish relations between the compounds and the varieties under investigation, principal component analysis and linear discriminant analysis were applied to the data, revealing a good separation and classification power between the four groups as a function of varietal origin.

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This study determines for the first time Na, K, Ca, Mg, Fe, Cu, Zn, Mn, Sr, Li and Rb contents in wines from the archipelagos of Madeira and Azores (Portugal). The greater part of the mean content for the different parameters fell within the ranges described in the literature, except for sodium whose higher content may be due to the effect of marine spray. ANOVA was used to establish the metals with significant differences in mean content between the wines from both archipelagos, between table and liquor wines of Madeira, and between wines of Pico and Terceira Islands from the Azores archipelago. Principal component analysis shows differences in the wines according to the wine-making process and/or the equipment employed. Stepwise linear discriminant analysis achieves a good classification and validation of wines according to the archipelago of origin, and the island in the case of Azores wines.

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BACKGROUND: Non-invasive diagnostic strategies aimed at identifying biomarkers of cancer are of great interest for early cancer detection. Urine is potentially a rich source of volatile organic metabolites (VOMs) that can be used as potential cancer biomarkers. Our aim was to develop a generally reliable, rapid, sensitive, and robust analytical method for screening large numbers of urine samples, resulting in a broad spectrum of native VOMs, as a tool to evaluate the potential of these metabolites in the early diagnosis of cancer. METHODS: To investigate urinary volatile metabolites as potential cancer biomarkers, urine samples from 33 cancer patients (oncological group: 14 leukaemia, 12 colorectal and 7 lymphoma) and 21 healthy (control group, cancer-free) individuals were qualitatively and quantitatively analysed. Dynamic solid-phase microextraction in headspace mode (dHS-SPME) using a carboxenpolydimethylsiloxane (CAR/PDMS) sorbent in combination with GC-qMS-based metabolomics was applied to isolate and identify the volatile metabolites. This method provides a potential non-invasive method for early cancer diagnosis as a first approach. To fulfil this objective, three important dHS-SPME experimental parameters that influence extraction efficiency (fibre coating, extraction time and temperature of sampling) were optimised using a univariate optimisation design. The highest extraction efficiency was obtained when sampling was performed at 501C for 60min using samples with high ionic strengths (17% sodium chloride, wv 1) and under agitation. RESULTS: A total of 82 volatile metabolites belonging to distinct chemical classes were identified in the control and oncological groups. Benzene derivatives, terpenoids and phenols were the most common classes for the oncological group, whereas ketones and sulphur compounds were the main classes that were isolated from the urine headspace of healthy subjects. The results demonstrate that compound concentrations were dramatically different between cancer patients and healthy volunteers. The positive rates of 16 patients among the 82 identified were found to be statistically different (Po0.05). A significant increase in the peak area of 2-methyl3-phenyl-2-propenal, p-cymene, anisole, 4-methyl-phenol and 1,2-dihydro-1,1,6-trimethyl-naphthalene in cancer patients was observed. On average, statistically significant lower abundances of dimethyl disulphide were found in cancer patients. CONCLUSIONS: Gas chromatographic peak areas were submitted to multivariate analysis (principal component analysis and supervised linear discriminant analysis) to visualise clusters within cases and to detect the volatile metabolites that are able to differentiate cancer patients from healthy individuals. Very good discrimination within cancer groups and between cancer and control groups was achieved.

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In this study the effect of the cultivar on the volatile profile of five different banana varieties was evaluated and determined by dynamic headspace solid-phase microextraction (dHS-SPME) combined with one-dimensional gas chromatography–mass spectrometry (1D-GC–qMS). This approach allowed the definition of a volatile metabolite profile to each banana variety and can be used as pertinent criteria of differentiation. The investigated banana varieties (Dwarf Cavendish, Prata, Maçã, Ouro and Platano) have certified botanical origin and belong to the Musaceae family, the most common genomic group cultivated in Madeira Island (Portugal). The influence of dHS-SPME experimental factors, namely, fibre coating, extraction time and extraction temperature, on the equilibrium headspace analysis was investigated and optimised using univariate optimisation design. A total of 68 volatile organic metabolites (VOMs) were tentatively identified and used to profile the volatile composition in different banana cultivars, thus emphasising the sensitivity and applicability of SPME for establishment of the volatile metabolomic pattern of plant secondary metabolites. Ethyl esters were found to comprise the largest chemical class accounting 80.9%, 86.5%, 51.2%, 90.1% and 6.1% of total peak area for Dwarf Cavendish, Prata, Ouro, Maçã and Platano volatile fraction, respectively. Gas chromatographic peak areas were submitted to multivariate statistical analysis (principal component and stepwise linear discriminant analysis) in order to visualise clusters within samples and to detect the volatile metabolites able to differentiate banana cultivars. The application of the multivariate analysis on the VOMs data set resulted in predictive abilities of 90% as evaluated by the cross-validation procedure.

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The volatile composition of different apple varieties of Malus domestica Borkh. species from different geographic regions at Madeira Islands, namely Ponta do Pargo (PP), Porto Santo (PS), and Santo da Serra (SS) was established by headspace solid-phase microextraction (HS-SPME) procedure followed by GC-MS (GC-qMS) analysis. Significant parameters affecting sorption process such as fiber coating, extraction temperature,extractiontime,sampleamount,dilutionfactor,ionicstrength,anddesorption time,wereoptimizedanddiscussed.TheSPMEfibercoatedwith50/30 lmdivinylbenzene/carboxen/PDMS (DVB/CAR/PDMS) afforded highest extraction efficiency of volatile compounds, providing the best sensitivity for the target volatiles, particularly whenthesampleswereextractedat508Cfor30 minwithconstantmagneticstirring. A qualitative and semi-quantitative analysis between the investigated apple species has been established. It was possible to identify about 100 of volatile compounds amongpulp(46,45,and39),peel(64,60,and64),andentirefruit(65,43,and50)inPP, PS,andSSapples,respectively.Ethylesters,terpenes,andhigheralcoholswerefound tobethemostrepresentativevolatiles. a-Farnesene,hexan-1-olandhexyl2-methylbutyratewerethecompoundsfoundinthevolatileprofileofstudiedappleswiththelargestGCarea,representing,onaverage,24.71,14.06,and10.80%ofthetotalvolatilefractionfromPP,PS,andSSapples.InPPentireapple,themostabundantcompoundsidentified were a-farnesene (30.49%), the unknown compound m/z (69, 101, 157) (21.82%) andhexylacetate(6.57%).RegardingPSentireapplethemajorcompoundswere a-farnesene(16.87%),estragole(15.43%),hexan-1-ol(10.94),andE-2-hexenal(10.67).a-Farnesene(30.3%),hexan-1-ol(18.90%),2-methylbutanoicacid(4.7%),andpentan-1-ol(4.6%) werealsofoundasSSentireapplevolatilespresentinahigherrelativecontent.Principal component analysis (PCA) of the results clustered the apples into three groups according to geographic origin. Linear discriminant analysis (LDA) was performed in order to detect the volatile compounds able to differentiate the three kinds of apples investigated. The most important contributions to the differentiation of the PP, PS, and SS apples were ethyl hexanoate, hexyl 2-methylbutyrate, E,E-2,4-heptadienal, pethylstyrene,andE-2-hexenal.

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Allergic asthma represents an important public health issue, most common in the paediatric population, characterized by airway inflammation that may lead to changes in volatiles secreted via the lungs. Thus, exhaled breath has potential to be a matrix with relevant metabolomic information to characterize this disease. Progress in biochemistry, health sciences and related areas depends on instrumental advances, and a high throughput and sensitive equipment such as comprehensive two-dimensional gas chromatography–time of flight mass spectrometry (GC × GC–ToFMS) was considered. GC × GC–ToFMS application in the analysis of the exhaled breath of 32 children with allergic asthma, from which 10 had also allergic rhinitis, and 27 control children allowed the identification of several hundreds of compounds belonging to different chemical families. Multivariate analysis, using Partial Least Squares-Discriminant Analysis in tandem with Monte Carlo Cross Validation was performed to assess the predictive power and to help the interpretation of recovered compounds possibly linked to oxidative stress, inflammation processes or other cellular processes that may characterize asthma. The results suggest that the model is robust, considering the high classification rate, sensitivity, and specificity. A pattern of six compounds belonging to the alkanes characterized the asthmatic population: nonane, 2,2,4,6,6-pentamethylheptane, decane, 3,6-dimethyldecane, dodecane, and tetradecane. To explore future clinical applications, and considering the future role of molecular-based methodologies, a compound set was established to rapid access of information from exhaled breath, reducing the time of data processing, and thus, becoming more expedite method for the clinical purposes.