Hypothesis testing in an errors-in-variables model with heteroscedastic measurement errors

In many epidemiological studies it is common to resort to regression models relating incidence of a disease and its risk factors. The main goal of this paper is to consider inference on such models with error-prone observations and variances of the measurement errors changing across observations. We suppose that the observations follow a bivariate normal distribution and the measurement errors are normally distributed. Aggregate data allow the estimation of the error variances. Maximum likelihood estimates are computed numerically via the EM algorithm. Consistent estimation of the asymptotic variance of the maximum likelihood estimators is also discussed. Test statistics are proposed for testing hypotheses of interest. Further, we implement a simple graphical device that enables an assessment of the model`s goodness of fit. Results of simulations concerning the properties of the test statistics are reported. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease. Copyright (C) 2008 John Wiley & Sons, Ltd.

A compound class of Weibull and power series distributions

In this paper we introduce the Weibull power series (WPS) class of distributions which is obtained by compounding Weibull and power series distributions where the compounding procedure follows same way that was previously carried out by Adamidis and Loukas (1998) This new class of distributions has as a particular case the two-parameter exponential power series (EPS) class of distributions (Chahkandi and Gawk 2009) which contains several lifetime models such as exponential geometric (Adamidis and Loukas 1998) exponential Poisson (Kus 2007) and exponential logarithmic (Tahmasbi and Rezaei 2008) distributions The hazard function of our class can be increasing decreasing and upside down bathtub shaped among others while the hazard function of an EPS distribution is only decreasing We obtain several properties of the WPS distributions such as moments order statistics estimation by maximum likelihood and inference for a large sample Furthermore the EM algorithm is also used to determine the maximum likelihood estimates of the parameters and we discuss maximum entropy characterizations under suitable constraints Special distributions are studied in some detail Applications to two real data sets are given to show the flexibility and potentiality of the new class of distributions (C) 2010 Elsevier B V All rights reserved

Horseradish peroxidase compound I as a tool to investigate reactive protein-cysteine residues: from quantification to kinetics

Proteins containing reactive cysteine residues (protein-Cys) are receiving increased attention as mediators of hydrogen peroxide signaling. These proteins are mainly identified by mining the thiol proteomes of oxidized protein-Cys in cells and tissues. However, it is difficult to determine if oxidation occurs through a direct reaction with hydrogen peroxide or by thiol-disulfide exchange reactions. Kinetic studies with purified proteins provide invaluable information about the reactivity of protein-Cys residues with hydrogen peroxide. Previously, we showed that the characteristic UV-Vis spectrum of horseradish peroxidase compound I, produced from the oxidation of horseradish peroxidase by hydrogen peroxide, is a simple, reliable, and useful tool to determine the second-order rate constant of the reaction of reactive protein-Cys with hydrogen peroxide and peroxynitrite. Here, the method is fully described and extended to quantify reactive protein-Cys residues and micromolar concentrations of hydrogen peroxide. Members of the peroxiredoxin family were selected for the demonstration and validation of this methodology. In particular, we determined the pK(a) of the peroxidatic thiol of rPrx6 (5.2) and the second-order rate constant of its reactions with hydrogen peroxide ((3.4 +/- 0.2) x 10(7) M(-1) s(-1)) and peroxynitrite ((3.7 +/- 0.4) x 10(5) M(-1) s(-1)) at pH 7.4 and 25 degrees C. (C) 2011 Elsevier Inc. All rights reserved.

Bcl-2 expression and apoptosis induction in human HL60 leukaemic cells treated with a novel organotellurium(IV) compound RT-04

Organotellurium(]V) compounds have been reported to have multiple biological activities including cysteine protease-inhibitory activity, mainly cathepsin B. As cathepsin B is a highly predictive indicator for prognosis and diagnosis of cancer, a possible antitumor potential for these new compounds is expected. In this work, it was investigated the effectiveness of organotellurium(IV) RT-04 to produce lethal effects in the human promyelocytic leukaemia cell line HL60. Using the MTT tetrazolium reduction test, and trypan blue exclusion assay, the IC50 for the compound after 24 h incubation was 6.8 and 0.35 mu M, respectively. Moreover, the compound was found to trigger apoptosis in HL60 cells, inducing DNA fragmentation and caspase-3, -6, and -9 activations. The apoptsosis-induced by RT-04 is probably related to the diminished Bcl-2 expression, observed by RT-PCR, in HL60-treated cells. In vivo studies demonstrated that the RT-04 treatment (2.76 mg/kg given for three consecutive days) produces no significant toxic effects for bone marrow and spleen CFU-GM. However, higher doses (5.0 and 10 mg/kg) produced a dose-dependent reduction in the number of CFU-GM of RT-04-treated mice. These results suggest that RT-04 is able to induce apoptosis in HL60 cells by Bcl-2 expression down-modulation. Further studies are necessary to better clarify the effects of this compound on bone marrow normal cells. (C) 2008 Elsevier Ltd. All rights reserved.

Expression Profile of Rat Hippocampal Neurons Treated with the Neuroprotective Compound 2,4-Dinitrophenol: Up-Regulation of cAMP Signaling Genes

2,4-Dinitrophenol (DNP) is classically known as a mitochondrial uncoupler and, at high concentrations, is toxic to a variety of cells. However, it has recently been shown that, at subtoxic concentrations, DNP protects neurons against a variety of insults and promotes neuronal differentiation and neuritogenesis. The molecular and cellular mechanisms underlying the beneficial neuroactive properties of DNP are still largely unknown. We have now used DNA microarray analysis to investigate changes in gene expression in rat hippocampal neurons in culture treated with low micromolar concentrations of DNP. Under conditions that did not affect neuronal viability, high-energy phosphate levels or mitochondrial oxygen consumption, DNP induced up-regulation of 275 genes and down-regulation of 231 genes. Significantly, several up-regulated genes were linked to intracellular cAMP signaling, known to be involved in neurite outgrowth, synaptic plasticity, and neuronal survival. Differential expression of specific genes was validated by quantitative RT-PCR using independent samples. Results shed light on molecular mechanisms underlying neuroprotection by DNP and point to possible targets for development of novel therapeutics for neurodegenerative disorders.