14 resultados para consistent and asymptotically normal estimators
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)
Resumo:
Oxidative damage to DNA is thought to play a role in carcinogenesis by causing Mutations, and indeed accumulation of oxidized DNA bases has been observed in samples obtained from tumors but not from surrounding tissue within the same patient. Base excision repair (BER) is the main pathway for the repair of oxidized modifications both in nuclear and mitochondrial, DNA. In order to ascertain whether diminished BER capacity might account for increased levels of oxidative DNA damage in cancer cells, the activities of BER enzymes in three different lung cancer cell lines and their non-cancerous counterparts were measured using oligonucleotide substrates with single DNA lesions to assess specific BER enzymes. The activities of four BER enzymes, OGG1, NTH1, UDG and APE1, were compared in mitochondrial and nuclear extracts. For each specific lesion, the repair activities were similar among the three cell lines used. However, the specific activities and cancer versus control comparison differed significantly between the nuclear and mitochondrial compartments. OGG1 activity, as measured by 8-oxodA incision, was upregulated in cancer cell mitochondria but down-regulated in the nucleus when compared to control cells. Similarly, NTH1 activity was also up-regulated in mitochondrial extracts from cancer cells but did not change significantly in the nucleus. Together, these results support the idea that alterations in BER capacity are associated with carcinogenesis.
Resumo:
Ultraviolet (UV) light generates two major DNA lesions: cyclobutane pyrimidine dimers (CPDs) and pyrimidine-(6-4)-pyrimidone photoproducts (6-4PPs), but the specific participation of these two lesions in the deleterious effects of UV is a longstanding question. In order to discriminate the precise role of unrepaired CPDs and 6-4PPs in UV-induced responses triggering cell death, human fibroblasts were transduced by recombinant adenoviruses carrying the CPD-photolyase or 6-4PP-photolyase cDNAs. Both photolyases were able to prevent UV-induced apoptosis in cells deficient for nucleotide excision repair (NER) to a similar extent, while in NER-proficient cells UV-induced apoptosis was prevented only by CPD-photolyase, with no effects observed when 6-4PPs were removed by the specific photolyase. These results strongly suggest that both CPDs and 6-4PPs contribute to UV-induced apoptosis in NER-deficient cells, while in NER-proficient cells, CPDs are the only lesions responsible for UV-killing, probably due to the rapid repair of 6-4PPs by NER. As a consequence, the difference in skin photosensitivity, including carcinogenesis, of most of the xeroderma pigmentosum patients and of normal people is probably not only a quantitative aspect, but depends on the type of DNA damage induced by sunlight and its rate of repair. (c) 2007 Elsevier B.V. All rights reserved.
Resumo:
The purpose of this paper is to develop a Bayesian analysis for nonlinear regression models under scale mixtures of skew-normal distributions. This novel class of models provides a useful generalization of the symmetrical nonlinear regression models since the error distributions cover both skewness and heavy-tailed distributions such as the skew-t, skew-slash and the skew-contaminated normal distributions. The main advantage of these class of distributions is that they have a nice hierarchical representation that allows the implementation of Markov chain Monte Carlo (MCMC) methods to simulate samples from the joint posterior distribution. In order to examine the robust aspects of this flexible class, against outlying and influential observations, we present a Bayesian case deletion influence diagnostics based on the Kullback-Leibler divergence. Further, some discussions on the model selection criteria are given. The newly developed procedures are illustrated considering two simulations study, and a real data previously analyzed under normal and skew-normal nonlinear regression models. (C) 2010 Elsevier B.V. All rights reserved.
Resumo:
The workplace is a manageable community-based setting for ensuring proper nutrition. This study aimed to evaluate dietary quality and associated factors among adult workers at a cosmetics factory in the metropolitan area of Sao Paulo, Brazil. This factory was actively participating in the Brazilian Workers` Meal Program, which was created to ensure workers` nutritional health. In this cross-sectional study, data on 202 adult workers were assessed using questionnaires (sociodemographic, anthropometric, and lifestyle characteristics) administered during August and September 2006. Dietary intake, measured by 24-hour dietary recall, was used to calculate the modified Healthy Eating Index (HEI). A repeated administration of the 24-hour dietary recall was applied in a random subsample to calculate the modified HEI adjusted for the within-person variation in intake. Mean adjusted modified HEI scores were analyzed using multiple linear regression adjusted for energy. The mean adjusted modified HEI score was 72.3 +/- 8.0. The lowest adjusted modified HEI components scores were ""milk and dairy products"" (4.4 +/- 3.2) and ""sodium"" (3.7 +/- 3.1). Two percent of workers had ""poor diet"" (adjusted modified HEI score <51 points) and the majority (87%) had ""diet that needs modification"" (adjusted modified HEI score between 51 and 80), despite their participation in the meal program. Adjusted modified HEI scores were considerably higher for men (74.7 +/- 7.0) than for women (66.9 +/- 8.2) and for normal body mass index (calculated as kg/m(2)) (73.3 +/- 7.8) than for overweight/obese (70.9 +/- 8.1). Based on these results, the vast majority of workers were found to have diets that needed improvement. Individuals with higher-quality diets were more likely to have lower body mass index and to be male. J Am Diet Assoc. 2010;110:786-790.
Resumo:
We study segregation phenomena in 57 groups selected from the 2dF Percolation-Inferred Galaxy Groups (2PIGG) catalogue of galaxy groups. The sample corresponds to those systems located in areas of at least 80 per cent redshift coverage out to 10 times the radius of the groups. The dynamical state of the galaxy systems was determined after studying their velocity distributions. We have used the Anderson-Darling test to distinguish relaxed and non-relaxed systems. This analysis indicates that 84 per cent of groups have galaxy velocities consistent with the normal distribution, while 16 per cent of them have more complex underlying distributions. Properties of the member galaxies are investigated taking into account this classification. Our results indicate that galaxies in Gaussian groups are significantly more evolved than galaxies in non-relaxed systems out to distances of similar to 4R(200), presenting significantly redder (B - R) colours. We also find evidence that galaxies with M(R) <= -21.5 in Gaussian groups are closer to the condition of energy equipartition.
Resumo:
This paper is concerned with the existence of pullback attractors for evolution processes. Our aim is to provide results that extend the following results for autonomous evolution processes (semigroups) (i) An autonomous evolution process which is bounded, dissipative and asymptotically compact has a global attractor. (ii) An autonomous evolution process which is bounded, point dissipative and asymptotically compact has a global attractor. The extension of such results requires the introduction of new concepts and brings up some important differences between the asymptotic properties of autonomous and non-autonomous evolution processes. An application to damped wave problem with non-autonomous damping is considered. (C) 2009 Elsevier Ltd. All rights reserved.
Resumo:
Although the oral cavity is easily accessible to inspection, patients with oral cancer most often present at a late stage, leading to high morbidity and mortality. Autofluorescence imaging has emerged as a promising technology to aid clinicians in screening for oral neoplasia and as an aid to resection, but current approaches rely on subjective interpretation. We present a new method to objectively delineate neoplastic oral mucosa using autofluorescence imaging. Autofluorescence images were obtained from 56 patients with oral lesions and 11 normal volunteers. From these images, 276 measurements from 159 unique regions of interest (ROI) sites corresponding to normal and confirmed neoplastic areas were identified. Data from ROIs in the first 46 subjects were used to develop a simple classification algorithm based on the ratio of red-to-green fluorescence; performance of this algorithm was then validated using data from the ROIs in the last 21 subjects. This algorithm was applied to patient images to create visual disease probability maps across the field of view. Histologic sections of resected tissue were used to validate the disease probability maps. The best discrimination between neoplastic and nonneoplastic areas was obtained at 405 nm excitation; normal tissue could be discriminated from dysplasia and invasive cancer with a 95.9% sensitivity and 96.2% specificity in the training set, and with a 100% sensitivity and 91.4% specificity in the validation set. Disease probability maps qualitatively agreed with both clinical impression and histology. Autofluorescence imaging coupled with objective image analysis provided a sensitive and noninvasive tool for the detection of oral neoplasia.
Resumo:
This paper aims at assessing the performance of a program of thermal simulation (Arquitrop) in different households in the city of Sao Paulo, Brazil. The households were selected for the Wheezing Project which followed up children under 2 years old to monitor the occurrence of respiratory diseases. The results show that in all three study households there is a good approximation between the observed and the simulated indoor temperatures. It was also observed a fairly consistent and realistic behavior between the simulated indoor and the outdoor temperatures, describing the Arquitrop model as an efficient estimator and good representative of the thermal behavior of households in the city of Sao Paulo. The worst simulation is linked to the poorest type of construction. This may be explained by the bad quality of the construction, which the Architrop could not simulate adequately.
Resumo:
Biological invasions threaten the native biota of several countries and this threat is even greater in the tropical regions that have the greatest biodiversity. In order to evaluate the representativeness of studies on invasive plants in tropical countries compared to the world, as well as the region of origin and habits of the most reported invasive plants in research, we analyzed the publications from eight of the most important international journals that address the theme, from January 1995 to December 2004. The articles on biological invasions were classified as theoretical or as case studies, and according to their approach, main question, where the study was conducted, region of origin and habit of the invasive plant. Case studies predominated, as did questions about the environment`s susceptibility to the invasion, the species` invasive power and the impacts it had. The most reported invasive species were herbaceous plants from Asia and Europe. Few articles address tropical environments and only one referred to Brazil. Most referred to North America and Europe. This small number of publications in the tropics indicates the need for a global projection on this subject and underscores the lack of consistent and organized data to understand the phenomenon and propose effective strategies to combat biological invasion.
Resumo:
The multivariate skew-t distribution (J Multivar Anal 79:93-113, 2001; J R Stat Soc, Ser B 65:367-389, 2003; Statistics 37:359-363, 2003) includes the Student t, skew-Cauchy and Cauchy distributions as special cases and the normal and skew-normal ones as limiting cases. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis of repeated measures, pretest/post-test data, under multivariate null intercept measurement error model (J Biopharm Stat 13(4):763-771, 2003) where the random errors and the unobserved value of the covariate (latent variable) follows a Student t and skew-t distribution, respectively. The results and methods are numerically illustrated with an example in the field of dentistry.
Resumo:
In this paper, the generalized log-gamma regression model is modified to allow the possibility that long-term survivors may be present in the data. This modification leads to a generalized log-gamma regression model with a cure rate, encompassing, as special cases, the log-exponential, log-Weibull and log-normal regression models with a cure rate typically used to model such data. The models attempt to simultaneously estimate the effects of explanatory variables on the timing acceleration/deceleration of a given event and the surviving fraction, that is, the proportion of the population for which the event never occurs. The normal curvatures of local influence are derived under some usual perturbation schemes and two martingale-type residuals are proposed to assess departures from the generalized log-gamma error assumption as well as to detect outlying observations. Finally, a data set from the medical area is analyzed.
Resumo:
Alzheimer`s disease is an ultimately fatal neurodegenerative disease, and BACE-1 has become an attractive validated target for its therapy, with more than a hundred crystal structures deposited in the PDB. In the present study, we present a new methodology that integrates ligand-based methods with structural information derived from the receptor. 128 BACE-1 inhibitors recently disclosed by GlaxoSmithKline R&D were selected specifically because the crystal structures of 9 of these compounds complexed to BACE-1, as well as five closely related analogs, have been made available. A new fragment-guided approach was designed to incorporate this wealth of structural information into a CoMFA study, and the methodology was systematically compared to other popular approaches, such as docking, for generating a molecular alignment. The influence of the partial charges calculation method was also analyzed. Several consistent and predictive models are reported, including one with r (2) = 0.88, q (2) = 0.69 and r (pred) (2) = 0.72. The models obtained with the new methodology performed consistently better than those obtained by other methodologies, particularly in terms of external predictive power. The visual analyses of the contour maps in the context of the enzyme drew attention to a number of possible opportunities for the development of analogs with improved potency. These results suggest that 3D-QSAR studies may benefit from the additional structural information added by the presented methodology.
Resumo:
This work presents a Bayesian semiparametric approach for dealing with regression models where the covariate is measured with error. Given that (1) the error normality assumption is very restrictive, and (2) assuming a specific elliptical distribution for errors (Student-t for example), may be somewhat presumptuous; there is need for more flexible methods, in terms of assuming only symmetry of errors (admitting unknown kurtosis). In this sense, the main advantage of this extended Bayesian approach is the possibility of considering generalizations of the elliptical family of models by using Dirichlet process priors in dependent and independent situations. Conditional posterior distributions are implemented, allowing the use of Markov Chain Monte Carlo (MCMC), to generate the posterior distributions. An interesting result shown is that the Dirichlet process prior is not updated in the case of the dependent elliptical model. Furthermore, an analysis of a real data set is reported to illustrate the usefulness of our approach, in dealing with outliers. Finally, semiparametric proposed models and parametric normal model are compared, graphically with the posterior distribution density of the coefficients. (C) 2009 Elsevier Inc. All rights reserved.
Resumo:
We study stochastic billiards on general tables: a particle moves according to its constant velocity inside some domain D R(d) until it hits the boundary and bounces randomly inside, according to some reflection law. We assume that the boundary of the domain is locally Lipschitz and almost everywhere continuously differentiable. The angle of the outgoing velocity with the inner normal vector has a specified, absolutely continuous density. We construct the discrete time and the continuous time processes recording the sequence of hitting points on the boundary and the pair location/velocity. We mainly focus on the case of bounded domains. Then, we prove exponential ergodicity of these two Markov processes, we study their invariant distribution and their normal (Gaussian) fluctuations. Of particular interest is the case of the cosine reflection law: the stationary distributions for the two processes are uniform in this case, the discrete time chain is reversible though the continuous time process is quasi-reversible. Also in this case, we give a natural construction of a chord ""picked at random"" in D, and we study the angle of intersection of the process with a (d - 1) -dimensional manifold contained in D.