916 resultados para Logistic regression mixture models
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Amino acids play essential roles in both metabolism and the proteome. Many studies have profiled free amino acids (FAAs) or proteins; however, few have connected the measurement of FAA with individual amino acids in the proteome. In this study, we developed a metabolomics method to comprehensively analyze amino acids in different domains, using two examples of different sample types and disease models. We first examined the responses of FAAs and insoluble-proteome amino acids (IPAAs) to the Myc oncogene in Tet21N human neuroblastoma cells. The metabolic and proteomic amino acid profiles were quite different, even under the same Myc condition, and their combination provided a better understanding of the biological status. In addition, amino acids were measured in 3 domains (FAAs, free and soluble-proteome amino acids (FSPAAs), and IPAAs) to study changes in serum amino acid profiles related to colon cancer. A penalized logistic regression model based on the amino acids from the three domains had better sensitivity and specificity than that from each individual domain. To the best of our knowledge, this is the first study to perform a combined analysis of amino acids in different domains, and indicates the useful biological information available from a metabolomics analysis of the protein pellet. This study lays the foundation for further quantitative tracking of the distribution of amino acids in different domains, with opportunities for better diagnosis and mechanistic studies of various diseases.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Saúde Coletiva - FMB
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Pós-graduação em Doenças Tropicais - FMB
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Bases Gerais da Cirurgia - FMB
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Pós-graduação em Biociências - FCLAS
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Static analysis tools report software defects that may or may not be detected by other verification methods. Two challenges complicating the adoption of these tools are spurious false positive warnings and legitimate warnings that are not acted on. This paper reports automated support to help address these challenges using logistic regression models that predict the foregoing types of warnings from signals in the warnings and implicated code. Because examining many potential signaling factors in large software development settings can be expensive, we use a screening methodology to quickly discard factors with low predictive power and cost-effectively build predictive models. Our empirical evaluation indicates that these models can achieve high accuracy in predicting accurate and actionable static analysis warnings, and suggests that the models are competitive with alternative models built without screening.
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OBJETIVO: Avaliar a relação entre alimentos de origem animal e câncer de boca e orofaringe. MÉTODOS: Estudo caso-controle, de base hospitalar, pareado por sexo e idade (± 5 anos) com a coleta de dados realizada entre julho de 2006 e junho de 2008. A amostra foi composta por 296 pacientes com câncer de boca e orofaringe e 296 pacientes sem histórico de câncer atendidos em quatro hospitais da cidade de São Paulo (SP), Brasil. Foi aplicado um questionário semiestruturado, para a coleta de dados relativos à condição socioeconômica e aos hábitos deletérios (tabaco e bebidas alcoólicas). Para avaliação do consumo alimentar, utilizou-se um questionário de frequência alimentar qualitativo. A análise se deu por meio de modelos de regressão logística multivariada, que consideraram a hierarquia existente entre as características estudadas. RESULTADOS: Entre os alimentos de origem animal, o consumo frequente de carne bovina (OR = 2,73; IC95% = 1,27-5,87; P < 0,001), bacon (OR = 2,48; IC95% = 1,30-4,74; P < 0,001) e ovos (OR = 3,04; IC95% = 1,51-6,15; P < 0,001) estava relacionado ao aumento no risco de câncer de boca e orofaringe, tanto na análise univariada quanto na multivariada. Entre os laticínios, o leite apresentou efeito protetor contra a doença (OR = 0,41; IC95% = 0,21-0,82; P < 0,001). CONCLUSÕES: O presente estudo sustenta a hipótese de que alimentos de origem animal podem estar relacionados à etiologia do câncer de boca e orofaringe. Essa informação pode orientar políticas preventivas contra a doença, gerando benefícios para a saúde pública.
Physical and psychosocial risk factors for musculoskeletal disorders in Brazilian and Italian nurses
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As part of the international CUPID investigation, we compared physical and psychosocial risk factors for musculoskeletal disorders among nurses in Brazil and Italy. Using questionnaires, we collected information on musculoskeletal disorders and potential risk factors from 751 nurses employed in public hospitals. By fitting country-specific multiple logistic regression models, we investigated the association of stressful physical activities and psychosocial characteristics with site-specific and multisite pain, and associated sickness absence. We found no clear relationship between low back pain and occupational lifting, but neck and shoulder pain were more common among nurses who reported prolonged work with the arms in an elevated position. After adjustment for potential confounding variables, pain in the low back, neck and shoulder, multisite pain, and sickness absence were all associated with somatizing tendency in both countries. Our findings support a role of somatizing tendency in predisposition to musculoskeletal disorders, acting as an important mediator of the individual response to triggering exposures, such as work-load.
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Objective: To investigate the relationship between TXNIP polymorphisms, diabetes and hypertension phenotypes in the Brazilian general population. Methods: Five hundred seventy-six individuals randomly selected from the general urban population according to the MONICA-WHO project guidelines were phenotyped for cardiovascular risk factors. A second, independent, sample composed of 487 family-trios from a different site was also selected. Nine TXNIP polymorphisms were studied. The potential association between TXNIP variability and glucose-phenotypes in children was also explored. TXNIP expression was quantified by real-time PCR in 53 samples from human smooth muscle cells primary culture. Results: TXNIP rs7211 and rs7212 polymorphisms were significantly associated with glucose and blood pressure related phenotypes. In multivariate logistic regression models the studied markers remained associated with diabetes even after adjustment for covariates. TXNIP rs7211 T/rs7212 G haplotype (present in approximately 17% of individuals) was significantly associated to diabetes in both samples. In children, the TXNIP rs7211 T/rs7212 G haplotype was associated with fasting insulin concentrations. Finally, cells harboring TXNIP rs7212 G allele presented higher TXNIP expression levels compared with carriers of TXNIP rs7212 CC genotype (p = 0.02). Conclusion: Carriers of TXNIP genetic variants presented higher TXNIP expression, early signs of glucose homeostasis derangement and increased susceptibility to chronic metabolic conditions such as diabetes and hypertension. Our data suggest that genetic variation in the TXNIP gene may act as a "common ground" modulator of both traits: diabetes and hypertension. (C) 2011 Elsevier Ireland Ltd. All rights reserved.
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Objective To assess several baseline risk factors that may predict patellofemoral and tibiofemoral cartilage loss during a 6-month period. Methods For 177 subjects with chronic knee pain, 3T magnetic resonance imaging (MRI) of both knees was performed at baseline and followup. Knees were semiquantitatively assessed, evaluating cartilage morphology, subchondral bone marrow lesions, meniscal morphology/extrusion, synovitis, and effusion. Age, sex, and body mass index (BMI), bone marrow lesions, meniscal damage/extrusion, synovitis, effusion, and prevalent cartilage damage in the same subregion were evaluated as possible risk factors for cartilage loss. Logistic regression models were applied to predict cartilage loss. Models were adjusted for age, sex, treatment, and BMI. Results Seventy-nine subregions (1.6%) showed incident or worsening cartilage damage at followup. None of the demographic risk factors was predictive of future cartilage loss. Predictors of patellofemoral cartilage loss were effusion, with an adjusted odds ratio (OR) of 3.5 (95% confidence interval [95% CI] 1.39.4), and prevalent cartilage damage in the same subregion with an adjusted OR of 4.3 (95% CI 1.314.1). Risk factors for tibiofemoral cartilage loss were baseline meniscal extrusion (adjusted OR 3.6 [95% CI 1.310.1]), prevalent bone marrow lesions (adjusted OR 4.7 [95% CI 1.119.5]), and prevalent cartilage damage (adjusted OR 15.3 [95% CI 4.947.4]). Conclusion Cartilage loss over 6 months is rare, but may be detected semiquantitatively by 3T MRI and is most commonly observed in knees with Kellgren/Lawrence grade 3. Predictors of patellofemoral cartilage loss were effusion and prevalent cartilage damage in the same subregion. Predictors of tibiofemoral cartilage loss were prevalent cartilage damage, bone marrow lesions, and meniscal extrusion.