912 resultados para REGRESSION MODEL


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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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A total of 3.035 lactations of Holstein cows from four farms in the Southeast, to check the influence of data structure of milk yield on the genetic parameters. Four dataset with different structures were tested, weekly controls (CW) with 122.842 controls, monthly controls (CM) 30.883, bimonthly controls (CB) with 15,837 and quarterly controls (CQ) with 12,702. The random regression model was used and was considered as random additive genetic and permanent environment effects, fixed effects of the contemporary groups (herd-year-month of test-day) and age of cow (linear and quadratic effects). Heritability estimates showed similar trends among the data files analyzed, with the greatest similarity between dataset CS, CM and CB. The dataset submitted all the CB estimates of genetic parameters analyzed with the same trend and similar magnitude to the CS and CM dataset, allowing the claim that there was no influence of the data structure on estimates of covariance components for the dataset CS, CM and CB. Thus, milk recording could be accomplished in a CB structure.

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Infection with human papilloma virus (HPV) is the most common sexually transmitted disease in the world. Among the 630 million new cases of HPV that occur each year, 30 million develop anogenital warts. Although subclinical infection with HPV is the most common cause, genital warts are also associated with immunosuppression caused by HIV. In view of the high prevalence of HPV/HIV co-infection particularly among men who have sex with men, the objectives of this study were to determine the prevalence of anogenital warts in men with HIV/AIDS and to identify associated factors. A cross-sectional study was conducted on 159 men with HIV/AIDS consecutively selected at a referral service in Botucatu, São Paulo, Brazil, in which the association between sociodemographic, behavioral and clinical variables and the presence of anogenital warts was evaluated. After hierarchical analysis of the data, variables presenting a p value ≤ 0.2 were entered into an unconditional multivariate logistic regression model. Forty-nine (31%) of the HIV-positive patients had anogenital warts. The mean age was 44.6 ± 9.6 years. The main factors associated with the presence of anogenital warts were irregular antiretroviral treatment and genital herpes(HSV). The present study demonstrate that anogenital warts occur in almost one-third of the male population infected with HIV and factors associated with a higher risk of being diagnosed with anogenital warts were irregular cART use and co-infection with HSV, other variables could not be associated.

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To evaluate the associations of HPA polymorphisms -1, -3, and -5 with HIV/HCV coinfection were included in this study 60 HIV/HCV-coinfected patients from the Sao Paulo State health service centers. Data reported by Verdichio-Moraes et al. (2009: J. Med Virol 81:757-759) were used as the non-infected and HCV monoinfected groups. Human Platelet Polymorphism genotyping was performed in 60 Patients co-infected with HIV/HCV by PCR-SSP or PCR-RFLP. HIV subtyping and HCV genotyping was performed by RT-PCR followed sequencing. The data analyses were performed using the χ2 test or Fisher's Exact Test and the logistic regression model. Patients coinfected with HIV/HCV presented HCV either genotype 1 (78.3%) or non-1 (21.7%) and HIV either subtype B (85.0%) or non-B (15%). The Human Platelet Polymorphism-1a/1b genotype was more frequent (P < 0.05) in HIV/HCV coinfection than in HCV monoinfection and the allelic frequency of Human Platelet Polymorphism-5b in the Patients coinfected with HIV/HCV was higher (P < 0.05) than in HCV monoinfected cases and non-infected individuals. These data suggest that the presence of specific HPA allele on platelets could favor the existence of coinfection. On the other hand, Human Platelet Polymorphism-5a/5b was more frequent (P < 0.05) in HIV/HCV coinfected and HCV monoinfected groups than in the non-infected individuals, suggesting that this platelet genotype is related to HCV infection, regardless of HIV presence. Results suggest that the Human Platelet Polymorphism profile in HIV/HCV coinfected individuals differs from the one of both HCV monoinfected and non-infected population. So, the Human Platelet Polymorphism can be a genetic marker associated with HIV/HCV coinfection.

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Pós-graduação em Fisiopatologia em Clínica Médica - FMB

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Pós-graduação em Enfermagem - FMB

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