Potencial envolvimento da adiponectina e seus receptores na modulação da esteroidogênese em corpo lúteo de cadelas ao longo do diestro

No ciclo estral de cadelas a fase luteínica, denominada diestro, compreende um período que varia de 60 a 100 dias em animais não-prenhes, caracterizado pela elevação plasmática de progesterona nos primeiros 20 dias pós ovulação (p.o). A adiponectina é a mais abundante proteína secretada pelo tecido adiposo, porém sua concentração plasmática diminui significativamente em alterações metabólicas como resistência insulínica e Diabetes mellitus tipo2, alterações descritas como relacionadas em algumas cadelas com o período de diestro. O objetivo do estudo foi determinar a expressão e imunolocalização do sistema adiponectina (adiponectina e seus receptores, adipoR1 e adipoR2) no corpo lúteo de cadelas ao longo do diestro, correlacionando-o ao perfil hormonal de 17β-estradiol e progesterona, assim como à expressão de um dos genes alvo do sistema, o PPAR-γ. Para realização do estudo foram coletados corpos lúteos de 28 cadelas durante ovariosalpingohisterectomia de eleição nos dias 10, 20, 30, 40, 50, 60 e 70 pós ovulação (o dia zero da ovulação foi considerado aquele no qual a concentração plasmática de progesterona atingiu 5ng/mL). Os corpos lúteos foram avaliados por imunohistoquímica para adiponectina e seus receptores e a expressão do RNAm do PPAR-γ por PCR em tempo real. A análise estatística da avaliação gênica foi realizada com o teste ANOVA, seguido por comparação múltipla Newman-Keuls. O sinal da adiponectina apresentou-se mais intenso até os primeiros 20 dias p.o, momento de regência da progesterona; houve queda gradativa após este período, coincidindo com a ascensão do 17β-estradiol, cujo pico foi notado próximo do dia 40 p.o. A queda marcante da adiponectina ocorreu após 50 dias p.o. O sinal do adipoR1 mostrou-se bem evidente até os 40 dias p.o e o do adipoR2 até os 50 dias p. o, decaindo posteriormente. Foi observada maior expressão do gene PPAR-γ aos 10, 30 e 70 dias p.o. Estes resultados mostram que a expressão protéica da adiponectina e de seus receptores se altera ao longo do diestro e que estas alterações podem estar relacionados às alterações hormonais e expressão do PPAR- γ, participando do mecanismo fisiológico de desenvolvimento, manutenção, atividade e regressão luteínica em cadelas.

The role of clouds in improving the regression model for hourly values of diffuse solar radiation

The study introduces a new regression model developed to estimate the hourly values of diffuse solar radiation at the surface. The model is based on the clearness index and diffuse fraction relationship, and includes the effects of cloud (cloudiness and cloud type), traditional meteorological variables (air temperature, relative humidity and atmospheric pressure observed at the surface) and air pollution (concentration of particulate matter observed at the surface). The new model is capable of predicting hourly values of diffuse solar radiation better than the previously developed ones (R-2 = 0.93 and RMSE = 0.085). A simple version with a large applicability is proposed that takes into consideration cloud effects only (cloudiness and cloud height) and shows a R-2 = 0.92. (C) 2011 Elsevier Ltd. 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.

Luteal function and follicular growth following follicular aspiration during the peri-luteolysis period in bos indicus and crossbred cattle

Follicular estradiol triggers luteolysis in cattle. Therefore, the control of follicle growth and steroidogenesis is expected to modulate luteal function and might be used as an anti-luteolytic strategy to improve embryo survival. Objectives were to evaluate follicular dynamics, plasma concentrations of estradiol and luteal lifespan in Bos indicus and crossbred cows subjected to sequential follicular aspirations. From D13 to D25 of a synchronized cycle (ovulation = D1), Nelore or crossbred, non-pregnant and non-lactating cows were submitted to daily ultrasound-guided aspiration of follicles >6 mm (n = 10) or to sham aspirations (n = 8). Diameter of the largest follicle on the day of luteolysis (7.4 +/- 1.0 vs 9.7 +/- 1.0 mm; mean +/- SEM), number of days in which follicles >6 mm were present (2.3 +/- 0.4 vs 4.6 +/- 0.5 days) and daily mean diameter of the largest follicle between D15 and D19 (6.4 +/- 0.2 vs 8.5 +/- 0.3 mm) were smaller (p <0.01) in the aspirated group compared with the control group, respectively. Aspiration tended to reduce (p< 0.10) plasma estradiol concentrations between D18 and D20 (2.95 +/- 0.54 vs 4.30 +/- 0.55 pg/ml). The luteal lifespan was similar (p > 0.10) between the groups (19.6 +/- 0.4 days), whereas the oestrous cycle was longer (p <0.01) in the aspirated group (31.4 +/- 1.2 vs 21.2 +/- 1.3 days). Hyperechogenic structures were present at the sites of aspiration and were associated with increase in concentration of progesterone between luteolysis and oestrus. It is concluded that follicular aspiration extended the oestrous cycle and decreased the average follicular diameter on the peri-luteolysis period but failed to delay luteolysis.

The geometric Birnbaum-Saunders regression model with cure rate

In this paper, we propose a cure rate survival model by assuming the number of competing causes of the event of interest follows the Geometric distribution and the time to event follow a Birnbaum Saunders distribution. We consider a frequentist analysis for parameter estimation of a Geometric Birnbaum Saunders model with cure rate. Finally, to analyze a data set from the medical area. (C) 2011 Elsevier B.V. All rights reserved.

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.

Local power properties of some asymptotic tests in symmetric linear regression models

In this paper we obtain asymptotic expansions, up to order n(-1/2) and under a sequence of Pitman alternatives, for the nonnull distribution functions of the likelihood ratio, Wald, score and gradient test statistics in the class of symmetric linear regression models. This is a wide class of models which encompasses the t model and several other symmetric distributions with longer-than normal tails. The asymptotic distributions of all four statistics are obtained for testing a subset of regression parameters. Furthermore, in order to compare the finite-sample performance of these tests in this class of models, Monte Carlo simulations are presented. An empirical application to a real data set is considered for illustrative purposes. (C) 2011 Elsevier B.V. All rights reserved.

Error Autocorrelation and Linear Regression for Temperature-Based Evapotranspiration Estimates Improvement

Estimates of evapotranspiration on a local scale is important information for agricultural and hydrological practices. However, equations to estimate potential evapotranspiration based only on temperature data, which are simple to use, are usually less trustworthy than the Food and Agriculture Organization (FAO)Penman-Monteith standard method. The present work describes two correction procedures for potential evapotranspiration estimates by temperature, making the results more reliable. Initially, the standard FAO-Penman-Monteith method was evaluated with a complete climatologic data set for the period between 2002 and 2006. Then temperature-based estimates by Camargo and Jensen-Haise methods have been adjusted by error autocorrelation evaluated in biweekly and monthly periods. In a second adjustment, simple linear regression was applied. The adjusted equations have been validated with climatic data available for the Year 2001. Both proposed methodologies showed good agreement with the standard method indicating that the methodology can be used for local potential evapotranspiration estimates.

The Poisson-exponential regression model under different latent activation schemes

In this paper, a new family of survival distributions is presented. It is derived by considering that the latent number of failure causes follows a Poisson distribution and the time for these causes to be activated follows an exponential distribution. Three different activation schemes are also considered. Moreover, we propose the inclusion of covariates in the model formulation in order to study their effect on the expected value of the number of causes and on the failure rate function. Inferential procedure based on the maximum likelihood method is discussed and evaluated via simulation. The developed methodology is illustrated on a real data set on ovarian cancer.

Examination of the performance of different pointwise linear regression progression criteria to detect glaucomatous visual field change

Background: We aimed to investigate the performance of five different trend analysis criteria for the detection of glaucomatous progression and to determine the most frequently and rapidly progressing locations of the visual field. Design: Retrospective cohort. Participants or Samples: Treated glaucoma patients with =8 Swedish Interactive Thresholding Algorithm (SITA)-standard 24-2 visual field tests. Methods: Progression was determined using trend analysis. Five different criteria were used: (A) =1 significantly progressing point; (B) =2 significantly progressing points; (C) =2 progressing points located in the same hemifield; (D) at least two adjacent progressing points located in the same hemifield; (E) =2 progressing points in the same Garway-Heath map sector. Main Outcome Measures: Number of progressing eyes and false-positive results. Results: We included 587 patients. The number of eyes reaching a progression endpoint using each criterion was: A = 300 (51%); B = 212 (36%); C = 194 (33%); D = 170 (29%); and E = 186 (31%) (P = 0.03). The numbers of eyes with positive slopes were: A = 13 (4.3%); B = 3 (1.4%); C = 3 (1.5%); D = 2 (1.1%); and E = 3 (1.6%) (P = 0.06). The global slopes for progressing eyes were more negative in Groups B, C and D than in Group A (P = 0.004). The visual field locations that progressed more often were those in the nasal field adjacent to the horizontal midline. Conclusions: Pointwise linear regression criteria that take into account the retinal nerve fibre layer anatomy enhances the specificity of trend analysis for the detection glaucomatous visual field progression.

Bartlett corrections in Birnbaum-Saunders nonlinear regression models

Lemonte and Cordeiro [Birnbaum-Saunders nonlinear regression models, Comput. Stat. Data Anal. 53 (2009), pp. 4441-4452] introduced a class of Birnbaum-Saunders (BS) nonlinear regression models potentially useful in lifetime data analysis. We give a general matrix Bartlett correction formula to improve the likelihood ratio (LR) tests in these models. The formula is simple enough to be used analytically to obtain several closed-form expressions in special cases. Our results generalize those in Lemonte et al. [Improved likelihood inference in Birnbaum-Saunders regressions, Comput. Stat. DataAnal. 54 (2010), pp. 1307-1316], which hold only for the BS linear regression models. We consider Monte Carlo simulations to show that the corrected tests work better than the usual LR tests.

Classification and regression tree (CART) model to predict pulmonary tuberculosis in hospitalized patients

Background: Tuberculosis (TB) remains a public health issue worldwide. The lack of specific clinical symptoms to diagnose TB makes the correct decision to admit patients to respiratory isolation a difficult task for the clinician. Isolation of patients without the disease is common and increases health costs. Decision models for the diagnosis of TB in patients attending hospitals can increase the quality of care and decrease costs, without the risk of hospital transmission. We present a predictive model for predicting pulmonary TB in hospitalized patients in a high prevalence area in order to contribute to a more rational use of isolation rooms without increasing the risk of transmission. Methods: Cross sectional study of patients admitted to CFFH from March 2003 to December 2004. A classification and regression tree (CART) model was generated and validated. The area under the ROC curve (AUC), sensitivity, specificity, positive and negative predictive values were used to evaluate the performance of model. Validation of the model was performed with a different sample of patients admitted to the same hospital from January to December 2005. Results: We studied 290 patients admitted with clinical suspicion of TB. Diagnosis was confirmed in 26.5% of them. Pulmonary TB was present in 83.7% of the patients with TB (62.3% with positive sputum smear) and HIV/AIDS was present in 56.9% of patients. The validated CART model showed sensitivity, specificity, positive predictive value and negative predictive value of 60.00%, 76.16%, 33.33%, and 90.55%, respectively. The AUC was 79.70%. Conclusions: The CART model developed for these hospitalized patients with clinical suspicion of TB had fair to good predictive performance for pulmonary TB. The most important variable for prediction of TB diagnosis was chest radiograph results. Prospective validation is still necessary, but our model offer an alternative for decision making in whether to isolate patients with clinical suspicion of TB in tertiary health facilities in countries with limited resources.

Response plateau models fitting via isotonic regression

Within the nutritional context, the supplementation of microminerals in bird food is often made in quantities exceeding those required in the attempt to ensure the proper performance of the animals. The experiments of type dosage x response are very common in the determination of levels of nutrients in optimal food balance and include the use of regression models to achieve this objective. Nevertheless, the regression analysis routine, generally, uses a priori information about a possible relationship between the response variable. The isotonic regression is a method of estimation by least squares that generates estimates which preserves data ordering. In the theory of isotonic regression this information is essential and it is expected to increase fitting efficiency. The objective of this work was to use an isotonic regression methodology, as an alternative way of analyzing data of Zn deposition in tibia of male birds of Hubbard lineage. We considered the models of plateau response of polynomial quadratic and linear exponential forms. In addition to these models, we also proposed the fitting of a logarithmic model to the data and the efficiency of the methodology was evaluated by Monte Carlo simulations, considering different scenarios for the parametric values. The isotonization of the data yielded an improvement in all the fitting quality parameters evaluated. Among the models used, the logarithmic presented estimates of the parameters more consistent with the values reported in literature.

Latent residual analysis in binary regression with skewed link

Model diagnostics is an integral part of model determination and an important part of the model diagnostics is residual analysis. We adapt and implement residuals considered in the literature for the probit, logistic and skew-probit links under binary regression. New latent residuals for the skew-probit link are proposed here. We have detected the presence of outliers using the residuals proposed here for different models in a simulated dataset and a real medical dataset.

A log-Birnbaum-Saunders regression model with asymmetric errors

This paper introduces a skewed log-Birnbaum-Saunders regression model based on the skewed sinh-normal distribution proposed by Leiva et al. [A skewed sinh-normal distribution and its properties and application to air pollution, Comm. Statist. Theory Methods 39 (2010), pp. 426-443]. Some influence methods, such as the local influence and generalized leverage, are presented. Additionally, we derived the normal curvatures of local influence under some perturbation schemes. An empirical application to a real data set is presented in order to illustrate the usefulness of the proposed model.