The Kumaraswamy Gumbel distribution

The Gumbel distribution is perhaps the most widely applied statistical distribution for problems in engineering. We propose a generalization-referred to as the Kumaraswamy Gumbel distribution-and provide a comprehensive treatment of its structural properties. We obtain the analytical shapes of the density and hazard rate functions. We calculate explicit expressions for the moments and generating function. The variation of the skewness and kurtosis measures is examined and the asymptotic distribution of the extreme values is investigated. Explicit expressions are also derived for the moments of order statistics. The methods of maximum likelihood and parametric bootstrap and a Bayesian procedure are proposed for estimating the model parameters. We obtain the expected information matrix. An application of the new model to a real dataset illustrates the potentiality of the proposed model. Two bivariate generalizations of the model are proposed.

Hyaluronidase splice variants are associated with histology and outcome in adenocarcinoma and squamous cell carcinoma of the lung

Heterogeneity of hyaluronidase (HYAL) expression has been identified in tumors and shows promise as an indicator of disease progression. The expression profile of alternatively spliced forms of HYAL was evaluated in tumors and normal lung tissue from 69 resected tumors of patients with adenocarcinomas and squamous cell carcinomas. HYAL1-wild-type (wt) and variants 1 to 5, HYAL2-wt, and HYAL3-wt, and variants 1 to 3 were identified by polymerase chain reaction and direct sequencing. Different proportions of the 3 HYAL-wt and variants were expressed in tumor and normal lung tissues. HYAL1-wt was associated with a poorer prognosis and HYAL3-vl with a better prognosis. HYAL splice variants are associated with histology and outcome, suggesting that strategies aimed at modulating their levels may be effective for lung cancer treatment. (C) 2012 Elsevier Inc. All rights reserved.

Estimation and diagnostics for heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions

An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures of skew-normal (SMSN) distributions is developed. This novel class of models provides a useful generalization of the heteroscedastic symmetrical nonlinear regression models (Cysneiros et al., 2010), since the random term distributions cover both symmetric as well as asymmetric and heavy-tailed distributions such as skew-t, skew-slash, skew-contaminated normal, among others. A simple EM-type algorithm for iteratively computing maximum likelihood estimates of the parameters is presented and the observed information matrix is derived analytically. In order to examine the performance of the proposed methods, some simulation studies are presented to show the robust aspect of this flexible class against outlying and influential observations and that the maximum likelihood estimates based on the EM-type algorithm do provide good asymptotic properties. Furthermore, local influence measures and the one-step approximations of the estimates in the case-deletion model are obtained. Finally, an illustration of the methodology is given considering a data set previously analyzed under the homoscedastic skew-t nonlinear regression model. (C) 2012 Elsevier B.V. All rights reserved.

Lymphatic fluctuation in the parenchymal remodeling stage of acute interstitial pneumonia, organizing pneumonia, nonspecific interstitial pneumonia and idiopathic pulmonary fibrosis

Because the superficial lymphatics in the lungs are distributed in the subpleural, interlobular and peribroncovascular interstitium, lymphatic impairment may occur in the lungs of patients with idiopathic interstitial pneumonias (IIPs) and increase their severity. We investigated the distribution of lymphatics in different remodeling stages of IIPs by immunohistochemistry using the D2-40 antibody. Pulmonary tissue was obtained from 69 patients with acute interstitial pneumonia/diffuse alveolar damage (AIP/DAD, N = 24), cryptogenic organizing pneumonia/organizing pneumonia (COP/OP, N = 6), nonspecific interstitial pneumonia (NSIP/NSIP, N = 20), and idiopathic pulmonary fibrosis/usual interstitial pneumonia (IPF/UIP, N = 19). D2-40+ lymphatic in the lesions was quantitatively determined and associated with remodeling stage score. We observed an increase in the D2-40+ percent from DAD (6.66 +/- 1.11) to UIP (23.45 +/- 5.24, P = 0.008) with the advanced process of remodeling stage of the lesions. Kaplan-Meier survival curves showed a better survival for patients with higher lymphatic D2-40+ expression than 9.3%. Lymphatic impairment occurs in the lungs of IIPs and its severity increases according to remodeling stage. The results suggest that disruption of the superficial lymphatics may impair alveolar clearance, delay organ repair and cause severe disease progress mainly in patients with AIP/DAD. Therefore, lymphatic distribution may serve as a surrogate marker for the identification of patients at greatest risk for death due to IIPs.

THE LOG-BURR XII REGRESSION MODEL FOR GROUPED SURVIVAL DATA

The log-Burr XII regression model for grouped survival data is evaluated in the presence of many ties. The methodology for grouped survival data is based on life tables, where the times are grouped in k intervals, and we fit discrete lifetime regression models to the data. The model parameters are estimated by maximum likelihood and jackknife methods. To detect influential observations in the proposed model, diagnostic measures based on case deletion, so-called global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to these measures, the total local influence and influential estimates are also used. We conduct Monte Carlo simulation studies to assess the finite sample behavior of the maximum likelihood estimators of the proposed model for grouped survival. A real data set is analyzed using a regression model for grouped data.

Different morphology, stage and treatment affect immune cell infiltration and long-term outcome in patients with non-small-cell lung carcinoma

Aims: Development of effective immune-based therapies for patients with non-small-cell lung carcinoma (NSCLC) depends on an accurate characterization of complex interactions that occur between immune cells and the tumour environment. Methods and results: Innate and adaptive immune responses were evaluated in relation to prognosis in 65 patients with surgically excised NSCLC. Immunohistochemistry and morphometry were used to determine the abundance and distribution of immune cells. We found low numbers of immune cells and levels of cytokines in the tumour environment when compared with surrounding parenchyma. Smoking was associated inversely with the adaptive immune response and directly with innate immunity. We observed a prominent adaptive immune response in squamous cell carcinomas (SCC) but greater innate immune responses in adenocarcinomas and large cell carcinomas. Cox model analysis showed a low risk of death for smoking <41 packs/year, N-0 tambour stage, squamous carcinoma, CD4(+) > 16.81% and macrophages/monocytes >4.5%. Collectively, the data indicate that in NSCLC there is not a substantive local immune cell infiltrate within the tumour. Conclusion: Although immune cell infiltration is limited in NSCLC it appears to have an impact on prognosis and this may be of relevance for new immunotherapeutic approaches.

High Rates of Detection of Respiratory Viruses in Tonsillar Tissues from Children with Chronic Adenotonsillar Disease

Chronic tonsillar diseases are an important health problem, leading to large numbers of surgical procedures worldwide. Little is known about pathogenesis of these diseases. In order to investigate the role of respiratory viruses in chronic adenotonsillar diseases, we developed a cross-sectional study to determine the rates of viral detections of common respiratory viruses detected by TaqMan real time PCR (qPCR) in nasopharyngeal secretions, tonsillar tissues and peripheral blood from 121 children with chronic tonsillar diseases, without symptoms of acute respiratory infections. At least one respiratory virus was detected in 97.5% of patients. The viral co-infection rate was 69.5%. The most frequently detected viruses were human adenovirus in 47.1%, human enterovirus in 40.5%, human rhinovirus in 38%, human bocavirus in 29.8%, human metapneumovirus in 17.4% and human respiratory syncytial virus in 15.7%. Results of qPCR varied widely between sample sites: human adenovirus, human bocavirus and human enterovirus were predominantly detected in tissues, while human rhinovirus was more frequently detected in secretions. Rates of virus detection were remarkably high in tonsil tissues: over 85% in adenoids and close to 70% in palatine tonsils. In addition, overall virus detection rates were higher in more hypertrophic than in smaller adenoids (p = 0.05), and in the particular case of human enteroviruses, they were detected more frequently (p = 0.05) in larger palatine tonsils than in smaller ones. While persistence/latency of DNA viruses in tonsillar tissues has been documented, such is not the case of RNA viruses. Respiratory viruses are highly prevalent in adenoids and palatine tonsils of patients with chronic tonsillar diseases, and persistence of these viruses in tonsils may stimulate chronic inflammation and play a role in the pathogenesis of these diseases.

General results for the Kumaraswamy-G distribution

For any continuous baseline G distribution [G. M. Cordeiro and M. de Castro, A new family of generalized distributions, J. Statist. Comput. Simul. 81 (2011), pp. 883-898], proposed a new generalized distribution (denoted here with the prefix 'Kw-G'(Kumaraswamy-G)) with two extra positive parameters. They studied some of its mathematical properties and presented special sub-models. We derive a simple representation for the Kw-Gdensity function as a linear combination of exponentiated-G distributions. Some new distributions are proposed as sub-models of this family, for example, the Kw-Chen [Z.A. Chen, A new two-parameter lifetime distribution with bathtub shape or increasing failure rate function, Statist. Probab. Lett. 49 (2000), pp. 155-161], Kw-XTG [M. Xie, Y. Tang, and T.N. Goh, A modified Weibull extension with bathtub failure rate function, Reliab. Eng. System Safety 76 (2002), pp. 279-285] and Kw-Flexible Weibull [M. Bebbington, C. D. Lai, and R. Zitikis, A flexible Weibull extension, Reliab. Eng. System Safety 92 (2007), pp. 719-726]. New properties of the Kw-G distribution are derived which include asymptotes, shapes, moments, moment generating function, mean deviations, Bonferroni and Lorenz curves, reliability, Renyi entropy and Shannon entropy. New properties of the order statistics are investigated. We discuss the estimation of the parameters by maximum likelihood. We provide two applications to real data sets and discuss a bivariate extension of the Kw-G distribution.

Generalized beta-generated distributions

This article introduces generalized beta-generated (GBG) distributions. Sub-models include all classical beta-generated, Kumaraswamy-generated and exponentiated distributions. They are maximum entropy distributions under three intuitive conditions, which show that the classical beta generator skewness parameters only control tail entropy and an additional shape parameter is needed to add entropy to the centre of the parent distribution. This parameter controls skewness without necessarily differentiating tail weights. The GBG class also has tractable properties: we present various expansions for moments, generating function and quantiles. The model parameters are estimated by maximum likelihood and the usefulness of the new class is illustrated by means of some real data sets. (c) 2011 Elsevier B.V. All rights reserved.

Immunophenotyping and extracellular matrix remodeling in pulmonary and extrapulmonary sarcoidosis

Objective: To investigate the significance of cellular immune markers, as well as that of collagen and elastic components of the extracellular matrix, within granulomatous structures in biopsies of patients with pulmonary or extrapulmonary sarcoidosis. Methods: We carried out qualitative and quantitative evaluations of inflammatory cells, collagen fibers, and elastic fibers in granulomatous structures in surgical biopsies of 40 patients with pulmonary and extrapulmonary sarcoidosis using histomorphometry, immunohistochemistry, picrosirius red staining, and Weigert's resorcin-fuchsin staining. Results: The extrapulmonary tissue biopsies presented significantly higher densities of lymphocytes, macrophages, and neutrophils than did the lung tissue biopsies. Pulmonary granulomas showed a significantly higher number of collagen fibers and a lower density of elastic fibers than did extrapulmonary granulomas. The amount of macrophages in the lung samples correlated with FVC (p < 0.05), whereas the amount of CD3+, CD4+, and CD8+ lymphocytes correlated with the FEV1/FVC ratio and VC. There were inverse correlations between TLC and the CD1a+ cell count (p < 0.05), as well as between DLCO and collagen/elastic fiber density (r = -0.90; p = 0.04). Conclusions: Immunophenotyping and remodeling both showed differences between pulmonary and extrapulmonary sarcoidosis in terms of the characteristics of the biopsy samples. These differences correlated with the clinical and spirometric data obtained for the patients, suggesting that two different pathways are involved in the mechanism of antigen clearance, which was more effective in the lungs and lymph nodes.

The log-exponentiated generalized gamma regression model for censored data

For the first time, we introduce a generalized form of the exponentiated generalized gamma distribution [Cordeiro et al. The exponentiated generalized gamma distribution with application to lifetime data, J. Statist. Comput. Simul. 81 (2011), pp. 827-842.] that is the baseline for the log-exponentiated generalized gamma regression model. The new distribution can accommodate increasing, decreasing, bathtub- and unimodal-shaped hazard functions. A second advantage is that it includes classical distributions reported in the lifetime literature as special cases. We obtain explicit expressions for the moments of the baseline distribution of the new regression model. The proposed model can be applied to censored data since it includes as sub-models several widely known regression models. It therefore can be used more effectively in the analysis of survival data. We obtain maximum likelihood estimates for the model parameters by considering censored data. We show that our extended regression model is very useful by means of two applications to real data.

The negative binomial-beta Weibull regression model to predict the cure of prostate cancer

In this article, for the first time, we propose the negative binomial-beta Weibull (BW) regression model for studying the recurrence of prostate cancer and to predict the cure fraction for patients with clinically localized prostate cancer treated by open radical prostatectomy. The cure model considers that a fraction of the survivors are cured of the disease. The survival function for the population of patients can be modeled by a cure parametric model using the BW distribution. We derive an explicit expansion for the moments of the recurrence time distribution for the uncured individuals. The proposed distribution can be used to model survival data when the hazard rate function is increasing, decreasing, unimodal and bathtub shaped. Another advantage is that the proposed model includes as special sub-models some of the well-known cure rate models discussed in the literature. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes. We analyze a real data set for localized prostate cancer patients after open radical prostatectomy.

The McDonald extended distribution: properties and applications

We study a five-parameter lifetime distribution called the McDonald extended exponential model to generalize the exponential, generalized exponential, Kumaraswamy exponential and beta exponential distributions, among others. We obtain explicit expressions for the moments and incomplete moments, quantile and generating functions, mean deviations, Bonferroni and Lorenz curves and Gini concentration index. The method of maximum likelihood and a Bayesian procedure are adopted for estimating the model parameters. The applicability of the new model is illustrated by means of a real data set.

A log-linear regression model for the beta-Birnbaum-Saunders distribution with censored data

The beta-Birnbaum-Saunders (Cordeiro and Lemonte, 2011) and Birnbaum-Saunders (Birnbaum and Saunders, 1969a) distributions have been used quite effectively to model failure times for materials subject to fatigue and lifetime data. We define the log-beta-Birnbaum-Saunders distribution by the logarithm of the beta-Birnbaum-Saunders distribution. Explicit expressions for its generating function and moments are derived. We propose a new log-beta-Birnbaum-Saunders regression model that can be applied to censored data and be used more effectively in survival analysis. We obtain the maximum likelihood estimates of the model parameters for censored data and investigate influence diagnostics. The new location-scale regression model is modified for the possibility that long-term survivors may be presented in the data. Its usefulness is illustrated by means of two real data sets. (C) 2011 Elsevier B.V. All rights reserved.

Effects of cilostazol in kidney and skeletal striated muscle of Wistar rats submitted to acute ischemia and reperfusion of hind limbs

PURPOSE: To investigate the effect of cilostazol, in kidney and skeletal muscle of rats submitted to acute ischemia and reperfusion. METHODS: Fourty three animals were randomized and divided into two groups. Group I received a solution of cilostazol (10 mg/Kg) and group II received saline solution 0.9% (SS) by orogastric tube after ligature of the abdominal aorta. After four hours of ischemia the animals were divided into four subgroups: group IA (Cilostazol): two hours of reperfusion. Group IIA (SS): two hours of reperfusion. Group IB (Cilostazol): six hours of reperfusion. Group IIB (SS) six hours of reperfusion. After reperfusion, a left nephrectomy was performed and removal of the muscles of the hind limb. The histological parameters were studied. In kidney cylinders of myoglobin, vacuolar degeneration and acute tubular necrosis. In muscle interstitial edema, inflammatory infiltrate, hypereosinophilia fiber, cariopicnose and necrosis. Apoptosis was assessed by immunohistochemistry for cleaved caspase-3 and TUNEL. RESULTS: There was no statistically significant difference between groups. CONCLUSION: Cilostazol had no protective effect on the kidney and the skeletal striated muscle in rats submitted to acute ischemia and reperfusion in this model.