An extinction-survival-type phase transition in the probabilistic cellular automaton p182-q200

We investigate the critical behaviour of a probabilistic mixture of cellular automata (CA) rules 182 and 200 (in Wolfram`s enumeration scheme) by mean-field analysis and Monte Carlo simulations. We found that as we switch off one CA and switch on the other by the variation of the single parameter of the model, the probabilistic CA (PCA) goes through an extinction-survival-type phase transition, and the numerical data indicate that it belongs to the directed percolation universality class of critical behaviour. The PCA displays a characteristic stationary density profile and a slow, diffusive dynamics close to the pure CA 200 point that we discuss briefly. Remarks on an interesting related stochastic lattice gas are addressed in the conclusions.

A semi-Markov multistate model for estimation of the mean quality-adjusted survival for non-progressive processes

We discuss the estimation of the expected value of the quality-adjusted survival, based on multistate models. We generalize an earlier work, considering the sojourn times in health states are not identically distributed, for a given vector of covariates. Approaches based on semiparametric and parametric (exponential and Weibull distributions) methodologies are considered. A simulation study is conducted to evaluate the performance of the proposed estimator and the jackknife resampling method is used to estimate the variance of such estimator. An application to a real data set is also included.

Regression analysis of mean quality-adjusted survival time based on pseudo-observations

Regression models for the mean quality-adjusted survival time are specified from hazard functions of transitions between two states and the mean quality-adjusted survival time may be a complex function of covariates. We discuss a regression model for the mean quality-adjusted survival (QAS) time based on pseudo-observations, which has the advantage of directly modeling the effect of covariates in the QAS time. Both Monte Carlo Simulations and a real data set are studied. Copyright (C) 2009 John Wiley & Sons, Ltd.

A new class of survival regression models with heavy-tailed errors: robustness and diagnostics

Birnbaum-Saunders models have largely been applied in material fatigue studies and reliability analyses to relate the total time until failure with some type of cumulative damage. In many problems related to the medical field, such as chronic cardiac diseases and different types of cancer, a cumulative damage caused by several risk factors might cause some degradation that leads to a fatigue process. In these cases, BS models can be suitable for describing the propagation lifetime. However, since the cumulative damage is assumed to be normally distributed in the BS distribution, the parameter estimates from this model can be sensitive to outlying observations. In order to attenuate this influence, we present in this paper BS models, in which a Student-t distribution is assumed to explain the cumulative damage. In particular, we show that the maximum likelihood estimates of the Student-t log-BS models attribute smaller weights to outlying observations, which produce robust parameter estimates. Also, some inferential results are presented. In addition, based on local influence and deviance component and martingale-type residuals, a diagnostics analysis is derived. Finally, a motivating example from the medical field is analyzed using log-BS regression models. Since the parameter estimates appear to be very sensitive to outlying and influential observations, the Student-t log-BS regression model should attenuate such influences. The model checking methodologies developed in this paper are used to compare the fitted models.

Estimation of the mean quality-adjusted survival using a multistate model for the sojourn times

In clinical trials, it may be of interest taking into account physical and emotional well-being in addition to survival when comparing treatments. Quality-adjusted survival time has the advantage of incorporating information about both survival time and quality-of-life. In this paper, we discuss the estimation of the expected value of the quality-adjusted survival, based on multistate models for the sojourn times in health states. Semiparametric and parametric (with exponential distribution) approaches are considered. A simulation study is presented to evaluate the performance of the proposed estimator and the jackknife resampling method is used to compute bias and variance of the estimator. (C) 2007 Elsevier B.V. All rights reserved.

QUALITY OF LIFE IN SYSTEMIC LUPUS ERYTHEMATOSUS PATIENTS IN NORTHEASTERN BRAZIL: IS HEALTH-RELATED QUALITY OF LIFE A PREDICTOR OF SURVIVAL FOR THESE PATIENTS?

Objective: To identify social, demographic and clinical characteristics that influence survival of patients with systemic lupus erythematosus (SLE). Methods: Sixty-three patients with a diagnosis of SLE were studied at our medical services in 1999 and then reviewed in 2005. We utilized a protocol to obtain demographic and clinical traits, activity and damage indices, and health-related quality of life via the SF-36. All statistical tests were performed using a significance level of 5%. Results: Out of the 63 patients examined in 1999, six died, four were lost for the follow-up and the previous protocol was applied to the remaining 53 patients. The six patients who died presented the worst recorded health-related quality of fife, in all aspects. The most important observed predictor of death was a mean lower score in the Role-Emotional Domain of the mental health component of the SF-36 (p<0.01). Conclusion: Health-related quality of life may be used as possible predictive factor of mortality among patients with SLE.

Thioredoxin-1 promotes survival in cells exposed to S-nitrosoglutathione: Correlation with reduction of intracellular levels of nitrosothiols and up-regulation of the ERK1/2 MAP Kinases

Accumulating evidence indicates that post-translational protein modifications by nitric oxide and its derived species are critical effectors of redox signaling in cells. These protein modifications are most likely controlled by intracellular reductants. Among them, the importance of the 12 kDa dithiol protein thioredoxin-1 (TRX-1) has been increasingly recognized. However, the effects of TRX-1 in cells exposed to exogenous nitrosothiols remain little understood. We investigated the levels of intracellular nitrosothiols and survival signaling in HeLa cells over-expressing TRX-1 and exposed to S-nitrosoglutahione (GSNO). A role for TRX-1 expression on GSNO catabolism and cell viability was demonstrated by the concentration-dependent effects of GSNO on decreasing TRX-1 expression, activation of capase-3, and increasing cell death. The over-expressaion of TRX-1 in HeLa cells partially attenuated caspase-3 activation and enhanced cell viability upon GSNO treatment. This was correlated with reduction of intracellular levels of nitrosothiols and increasing levels of nitrite and nitrotyrosine. The involvement of ERK, p38 and JNK pathways were investigated in parental cells treated with GSNO. Activation of ERK1/2 MAP kinases was shown to be critical for survival signaling. lit cells over-expressing TRX-1, basal phosphorylation levels of ERK1/2 MAP kinases were higher and further increased after GSNO treatment. These results indicate that the enhanced cell viability promoted by TRX-1 correlates with its capacity to regulate the levels of intracellular nitiosothiols and to up-regulate the survival signaling pathway mediated by the ERK1/2 MAP kinases.

The GATA-type transcriptional activator Gat1 regulates nitrogen uptake and metabolism in the human pathogen Cryptococcus neoformans

Nitrogen uptake and metabolism are essential to microbial growth. Gat1 belongs to a conserved family of zinc finger containing transcriptional regulators known as GATA-factors. These factors activate the transcription of Nitrogen Catabolite Repression (NCR) sensitive genes when preferred nitrogen sources are absent or limiting. Cryptococcus neoformans GAT1 is an ortholog to the Aspergillus nidulans AreA and Candida albicans GAD genes. In an attempt to define the function of this transcriptional regulator in C. neoformans, we generated null mutants (gat1 Delta) of this gene. The gat 1 mutant exhibited impaired growth on all amino acids tested as sole nitrogen sources, with the exception of arginine and proline. Furthermore, the gat1 mutant did not display resistance to rapamycin, an immunosuppressant drug that transiently mimics a low-quality nitrogen source. Gal is not required for C. neoformans survival during macrophage infection or for virulence in a mouse model of cryptococcosis. Microarray analysis allowed the identification of target genes that are regulated by Gat1 in the presence of proline, a poor and non-repressing nitrogen source. Genes involved in ergosterol biosynthesis, iron uptake, cell wall organization and capsule biosynthesis, in addition to NCR-sensitive genes, are Gat1-regulated in C. neoformans. (C) 2010 Elsevier Inc. All rights reserved.