Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil

A total of 152,145 weekly test-day milk yield records from 7317 first lactations of Holstein cows distributed in 93 herds in southeastern Brazil were analyzed. Test-day milk yields were classified into 44 weekly classes of DIM. The contemporary groups were defined as herd-year-week of test-day. The model included direct additive genetic, permanent environmental and residual effects as random and fixed effects of contemporary group and age of cow at calving as covariable, linear and quadratic effects. Mean trends were modeled by a cubic regression on orthogonal polynomials of DIM. Additive genetic and permanent environmental random effects were estimated by random regression on orthogonal Legendre polynomials. Residual variances were modeled using third to seventh-order variance functions or a step function with 1, 6,13,17 and 44 variance classes. Results from Akaike`s and Schwarz`s Bayesian information criterion suggested that a model considering a 7th-order Legendre polynomial for additive effect, a 12th-order polynomial for permanent environment effect and a step function with 6 classes for residual variances, fitted best. However, a parsimonious model, with a 6th-order Legendre polynomial for additive effects and a 7th-order polynomial for permanent environmental effects, yielded very similar genetic parameter estimates. (C) 2008 Elsevier B.V. All rights reserved.

A Log-Linear Regression Model for the Beta-Weibull Distribution

We introduce the log-beta Weibull regression model based on the beta Weibull distribution (Famoye et al., 2005; Lee et al., 2007). We derive expansions for the moment generating function which do not depend on complicated functions. The new regression model represents a parametric family of models that includes as sub-models several widely known regression models that can be applied to censored survival data. We employ a frequentist analysis, a jackknife estimator, and a parametric bootstrap for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Further, for different parameter settings, sample sizes, and censoring percentages, several simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We define martingale and deviance residuals to evaluate the model assumptions. The extended regression model is very useful for the analysis of real data and could give more realistic fits than other special regression models.

Paclitaxel associated with cholesterol-rich nanoemulsions promotes atherosclerosis regression in the rabbit

A cholesterol-rich nanoemulsion (LDE) that resembles LDL binds to the LDL receptors and after injection into the blood stream may concentrate in cells with LDL receptor overexpression, as occurs in neoplasias and other proliferative processes. Thus, LDE can be used as vehicle to target drugs against those cells. The current study was designed to verify in rabbits whether LDE concentrates in the lesioned rabbit artery and whether a paclitaxel derivative, paclitaxel oleate, associated to LDE could reduce the atherosclerotic lesions. Sixteen male New Zealand rabbits were fed a 1% cholesterol diet for 60 days. Starting from day 30 under cholesterol feeding, eight animals were treated with four weekly intravenous injections of LDE-paclitaxel (4 mg/kg) and eight with four weekly intravenous saline solution injections for additional 30 days. On day 60, the animals were sacrificed for analysis. The uptake of LDE labeled with [C-14]-cholesteryl oleate by the aortic arch of cholesterol-fed rabbits was twice as much that observed in animals fed only regular chow. LDE-paclitaxel reduced the lesion areas of cholesterol-fed animals by 60% and intima-media ratio fourfold and inhibited the macrophage migration and the smooth muscle cell proliferation and invasion of the intima. LDE-paclitaxel treatment had no toxicity. In conclusion, LDE-paclitaxel produced pronounced atherosclerosis regression without toxicity and has shown remarkable potential in cardiovascular therapeutics. (c) 2008 Published by Elsevier Ireland Ltd.

Exploratory Approach to the use of Techniques of Regression Analysis and Pooled Analysis in Studies of Consumer Behavior

This paper is part of a large study to assess the adequacy of the use of multivariate statistical techniques in theses and dissertations of some higher education institutions in the area of marketing with theme of consumer behavior from 1997 to 2006. The regression and conjoint analysis are focused on in this paper, two techniques with great potential of use in marketing studies. The objective of this study was to analyze whether the employement of these techniques suits the needs of the research problem presented in as well as to evaluate the level of success in meeting their premisses. Overall, the results suggest the need for more involvement of researchers in the verification of all the theoretical precepts of application of the techniques classified in the category of investigation of dependence among variables.

Multicollinearity and financial constraint in investment decisions: a Bayesian generalized ridge regression

This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.

Obstructive Sleep Apnea Is Common and Independently Associated With Atrial Fibrillation in Patients With Hypertrophic Cardiomyopathy

Background: Hypertrophic cardiomyopathy (HCM) is associated with arrhythmias and cardiovascular death. Left atrial enlargement and atrial fibrillation (AF) are considered markers for death due to heart failure in patients with HCM. Obstructive sleep apnea (OSA) is independently associated with heart remodeling and arrhythmias in other populations. We hypothesized that OSA is common and is associated with heart remodeling and AF in patients with HCM. Methods: We evaluated 80 consecutive stable patients with a confirmed diagnosis of HCM by sleep questionnaire, blood tests, echocardiography, and sleep study (overnight respiratory monitoring). Results: OSA (apnea-hypopnea index [AHI] > 15 events/h) was present in 32 patients (40%). Patients with OSA were significantly older (56 [41-64] vs 38.5 [30-53] years, P < .001) and presented higher BMI (28.2 +/- 3.5 vs 25.2 +/- 5.2 kg/m(2), P < .01) and increased left atrial diameter (45 [42-52.8] vs 41 [39-47] mm, P = .01) and aorta diameter (34 [30-37] vs 29 [28-32] mm, P < .001), compared with patients without OSA. Stepwise multiple linear regression showed that the AHI (P = .05) and BMI (P = .06) were associated with left atrial diameter. The AHI was the only variable associated with aorta diameter (P = .01). AF was present in 31% vs 6% of patients with and without OSA, respectively (P < .01). OSA (P = .03) and left atrial diameter (P = .03) were the only factors independently associated with AF. Conclusions: OSA is highly prevalent in patients with HCM and it is associated with left atrial and aortic enlargement. OSA is independently associated with AF, a risk factor for cardiovascular death in this population. CHEST 2010; 137(5):1078-1084

A stepwise approach to stroke surveillance in Brazil: the EMMA (Estudo de Mortalidade e Morbidade do Acidente Vascular Cerebral) study

Background Stroke mortality rates in Brazil are the highest in the Americas. Deaths from cerebrovascular disease surpass coronary heart disease. Aim To verify stroke mortality rates and morbidity in an area of Sao Paulo, Brazil, using the World Health Organization Stepwise Approach to Stroke Surveillance. Methods We used the World Health Organization Stepwise Approach to Stroke Surveillance structure of stroke surveillance. The hospital-based data comprised fatal and nonfatal stroke (Step 1). We gathered stroke-related mortality data in the community using World Health Organization questionnaires (Step 2). The questionnaire determining stroke prevalence was activated door to door in a family-health-programme neighbourhood (Step 3). Results A total of 682 patients 18 years and above, including 472 incident cases, presented with cerebrovascular disease and were enrolled in Step 1 during April-May 2009. Cerebral infarction (84 center dot 3%) and first-ever stroke (85 center dot 2%) were the most frequent. In Step 2, 256 deaths from stroke were identified during 2006-2007. Forty-four per cent of deaths were classified as unspecified stroke, 1/3 as ischaemic stroke, and 1/4 due to haemorrhagic subtype. In Step 3, 577 subjects over 35 years old were evaluated at home, and 244 cases of stroke survival were diagnosed via a questionnaire, validated by a board-certified neurologist. The population demographic characteristics were similar in the three steps, except in terms of age and gender. Conclusion By including data from all settings, World Health Organization stroke surveillance can provide data to help plan future resources that meet the needs of the public-health system.

Echocardiographic predictors of functional capacity in endomyocardial fibrosis patients

Endomyocardial fibrosis (EMF) is a restrictive cardiomyopathy manifested mainly by diastolic heart failure. It is recognized that diastole is an important determinant of exercise capacity. The purpose of this study was to determine whether resting echocardiographic parameters might predict oxygen consumption (VO(2p)) by ergoespirometry and the prognostic role of functional capacity in EMF patients. A total of 32 patients with biventricular EMF (29 women, 55.3 +/- 11.4 years) were studied by echocardiography and ergoespirometry. The relationship between the echocardiographic indexes and the percentage of predicted VO(2p) (%VO(2p)) was investigated by the `stepwise` linear regression analysis. The median VO(2p) was 11 +/- 3 mL/kg/min and the %VO(2p) was 53 +/- 9%. There was a correlation of %VO(2p) with an average of A` at four sites of the mitral annulus (A` peak, r = 0.471, P = 0.023), E`/A` of the inferior mitral annulus (r = -0.433, P = 0.044), and myocardial performance index (r = -0.352, P = 0.048). On multiple regression analysis, only A` peak was an independent predictor of %VO(2p) (%VO(2p)= 26.34 + 332.44 x A` peak). EMF patients with %VO(2p)< 53% had an increased mortality rate with a relative risk of 8.47. In EMF patients, diastolic function plays an important role in determining the limitations to exercise and %VO(2p) has a prognostic value.

Predictive Factors for Positive Surgical Margins and Their Locations After Robot-Assisted Laparoscopic Radical Prostatectomy

Background: Positive surgical margin (PSM) after radical prostatectomy (RP) has been shown to be an independent predictive factor for cancer recurrence. Several investigations have correlated clinical and histopathologic findings with surgical margin status after open RP. However, few studies have addressed the predictive factors for PSM after robot-assisted laparoscopic RP (RARP). Objective: We sought to identify predictive factors for PSMs and their locations after RARP. Design, setting, and participants: We prospectively analyzed 876 consecutive patients who underwent RARP from January 2008 to May 2009. Intervention: All patients underwent RARP performed by a single surgeon with previous experience of > 1500 cases. Measurements: Stepwise logistic regression was used to identify potential predictive factors for PSM. Three logistic regression models were built: (1) one using preoperative variables only, (2) another using all variables (preoperative, intraoperative, and postoperative) combined, and (3) one created to identify potential predictive factors for PSM location. Preoperative variables entered into the models included age, body mass index (BMI), prostate-specific antigen, clinical stage, number of positive cores, percentage of positive cores, and American Urological Association symptom score. Intra-and postoperative variables analyzed were type of nerve sparing, presence of median lobe, percentage of tumor in the surgical specimen, gland size, histopathologic findings, pathologic stage, and pathologic Gleason grade. Results and limitations: In the multivariable analysis including preoperative variables, clinical stage was the only independent predictive factor for PSM, with a higher PSM rate for T3 versus T1c (odds ratio [OR]: 10.7; 95% confidence interval [CI], 2.6-43.8) and for T2 versus T1c (OR: 2.9; 95% CI, 1.9-4.6). Considering pre-, intra-, and postoperative variables combined, percentage of tumor, pathologic stage, and pathologic Gleason score were associated with increased risk of PSM in the univariable analysis (p < 0.001 for all variables). However, in the multivariable analysis, pathologic stage (pT2 vs pT1; OR: 2.9; 95% CI, 1.9-4.6) and percentage of tumor in the surgical specimen (OR: 8.7; 95% CI, 2.2-34.5; p = 0.0022) were the only independent predictive factors for PSM. Finally, BMI was shown to be an independent predictive factor(OR: 1.1; 95% CI, 1.0-1.3; p = 0.0119) for apical PSMs, with increasing BMI predicting higher incidence of apex location. Because most of our patients were referred from other centers, the biopsy technique and the number of cores were not standardized in our series. Conclusions: Clinical stage was the only preoperative variable independently associated with PSM after RARP. Pathologic stage and percentage of tumor in the surgical specimen were identified as independent predictive factors for PSMs when analyzing pre-, intra-, and postoperative variables combined. BMI was shown to be an independent predictive factor for apical PSMs. (C) 2010 European Association of Urology. Published by Elsevier B. V. All rights reserved.

Regression of glomerular injury by losartan in experimental diabetic nephropathy

Many features of chronic kidney disease may be reversed, but it is unclear whether advanced lesions, such as adhesions of sclerotic glomerular tufts to Bowman`s capsule (synechiae), can resolve during treatment. We previously showed, using a renal ablation model, that the renoprotective effect of the AT-1 receptor blocker, losartan, is dose-dependent. Here we determined if moderate and advanced glomerular lesions, associated with streptozotocin-induced diabetes, regress with conventional or high-dose losartan treatment. Using daily insulin injection for 10 months, we maintained diabetic adult male Munich-Wistar rats in a state of moderate hyperglycemia. Following this period, some rats continued to receive insulin with or without conventional or high-dose losartan for an additional 2 months. Diabetic rats pretreated with insulin for 10 months and age-matched non-diabetic rats served as controls. Mesangial expansion was found in the control diabetic rats and was exacerbated in those rats maintained on only insulin for an additional 2 months. Conventional and high-dose losartan treatments reduced this mesangial expansion and the severity of synechiae lesions below that found prior to treatment; however, the frequency of the latter was unchanged. There was no dose-response effect of losartan. Our results show that regression of mesangial expansion and contraction of sclerotic lesions is feasible in the treatment of diabetes, but complete resolution of advanced glomerulosclerosis may be hard to achieve.

Expression of fibroblast growth factor receptors during development and regression of the bovine corpus luteum

There is evidence that fibroblast growth factors (FGFs) are involved in the regulation of growth and regression of the corpus luteum (CL). However, the expression pattern of most FGF receptors (FGFRs) during CL lifespan is still unknown. The objective of the present study was to determine the pattern of expression of `B` and `C` splice variants of FGFRs in the bovine CL. Bovine CL were collected from an abattoir and classed as corpora hemorrhagica (Stage I), developing (Stage II), developed (Stage III) or regressed (Stage IV) CL. Expression of FGFR mRNA was measured by semiquantitative reverse transcription-polymerase chain reaction and FGFR protein was localised by immunohistochemistry. Expression of mRNA encoding the `B` and `C` spliced forms of FGFR1 and FGFR2 was readily detectable in the bovine CL and was accompanied by protein localisation. FGFR1C and FGFR2C mRNA expression did not vary throughout CL lifespan, whereas FGFR1B was upregulated in the developed (Stage III) CL. FGFR3B, FGFR3C and FGFR4 expression was inconsistent in the bovine CL. The present data indicate that FGFR1 and FGFR2 splice variants are the main receptors for FGF action in the bovine CL.

BisGMA/TEGDMA ratio and filler content effects on shrinkage stress

Objective. To investigate the contributions of BisGMA:TEGDMA and filler content on polymerization stress, along with the influence of variables associated with stress development, namely, degree of conversion, reaction rate, shrinkage, elastic modulus and loss tangent for a series of experimental dental composites. Methods. Twenty formulations with BisGMA: TEGDMA ratios of 3: 7, 4: 6, 5: 5, 6: 4 and 7: 3 and barium glass filler levels of 40, 50, 60 or 70 wt% were studied. Polymerization stress was determined in a tensilometer, inserting the composite between acrylic rods fixed to clamps of a universal test machine and dividing the maximum load recorded by the rods cross-sectional area. Conversion and reaction rate were determined by infra-red spectroscopy. Shrinkage was measured by mercury dilatometer. Modulus was obtained by three-point bending. Loss tangent was determined by dynamic nanoindentation. Regression analyses were performed to estimate the effect of organic and inorganic contents on each studied variable, while a stepwise forward regression identified significant variables for polymerization stress. Results. All variables showed dependence on inorganic concentration and monomeric content. The resin matrix showed a stronger influence on polymerization stress, conversion and reaction rate, whereas filler fraction showed a stronger influence on shrinkage, modulus and loss tangent. Shrinkage and conversion were significantly related to polymerization stress. Significance. Both the inorganic filler concentration and monomeric content affect polymerization stress, but the stronger influence of the resin matrix suggests that it may be possible to reduce stress by modifying resin composition without sacrificing filler content. The main challenge is to develop formulations with low shrinkage without sacrificing degree of conversion. (C) 2011 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Heteroscedastic Nonlinear Regression Models

In this article, we present a generalization of the Bayesian methodology introduced by Cepeda and Gamerman (2001) for modeling variance heterogeneity in normal regression models where we have orthogonality between mean and variance parameters to the general case considering both linear and highly nonlinear regression models. Under the Bayesian paradigm, we use MCMC methods to simulate samples for the joint posterior distribution. We illustrate this algorithm considering a simulated data set and also considering a real data set related to school attendance rate for children in Colombia. Finally, we present some extensions of the proposed MCMC algorithm.

Regression Models with Heteroscedasticity using Bayesian Approach

In this paper, we compare the performance of two statistical approaches for the analysis of data obtained from the social research area. In the first approach, we use normal models with joint regression modelling for the mean and for the variance heterogeneity. In the second approach, we use hierarchical models. In the first case, individual and social variables are included in the regression modelling for the mean and for the variance, as explanatory variables, while in the second case, the variance at level 1 of the hierarchical model depends on the individuals (age of the individuals), and in the level 2 of the hierarchical model, the variance is assumed to change according to socioeconomic stratum. Applying these methodologies, we analyze a Colombian tallness data set to find differences that can be explained by socioeconomic conditions. We also present some theoretical and empirical results concerning the two models. From this comparative study, we conclude that it is better to jointly modelling the mean and variance heterogeneity in all cases. We also observe that the convergence of the Gibbs sampling chain used in the Markov Chain Monte Carlo method for the jointly modeling the mean and variance heterogeneity is quickly achieved.