Short communication: Principal components and factor analytic models for test-day milk yield in Brazilian Holstein cattle

A total of 46,089 individual monthly test-day (TD) milk yields (10 test-days), from 7,331 complete first lactations of Holstein cattle were analyzed. A standard multivariate analysis (MV), reduced rank analyses fitting the first 2, 3, and 4 genetic principal components (PC2, PC3, PC4), and analyses that fitted a factor analytic structure considering 2, 3, and 4 factors (FAS2, FAS3, FAS4), were carried out. The models included the random animal genetic effect and fixed effects of the contemporary groups (herd-year-month of test-day), age of cow (linear and quadratic effects), and days in milk (linear effect). The residual covariance matrix was assumed to have full rank. Moreover, 2 random regression models were applied. Variance components were estimated by restricted maximum likelihood method. The heritability estimates ranged from 0.11 to 0.24. The genetic correlation estimates between TD obtained with the PC2 model were higher than those obtained with the MV model, especially on adjacent test-days at the end of lactation close to unity. The results indicate that for the data considered in this study, only 2 principal components are required to summarize the bulk of genetic variation among the 10 traits.

Respiratory inductive plethysmography: a comparative study between isovolume maneuver calibration and qualitative diagnostic calibration in healthy volunteers assessed in different positions

Objective: To compare two methods of respiratory inductive plethysmography (RIP) calibration in three different positions. Methods: We evaluated 28 healthy subjects (18 women and 10 men), with a mean age of 25.4 +/- 3.9 years. For all of the subjects, isovolume maneuver calibration (ISOCAL) and qualitative diagnostic calibration (QDC) were used in the orthostatic, sitting, and supine positions. In order to evaluate the concordance between the two calibration methods, we used ANOVA and Bland-Altman plots. Results: The values of the constant of proportionality (X) were significantly different between ISOCAL and QDC in the three positions evaluated: 1.6 +/- 0.5 vs. 2.0 +/- 1.2, in the supine position, 2.5 +/- 0.8 vs. 0.6 +/- 0.3 in the sitting position, and 2.0 +/- 0.8 vs. 0.6 +/- 0.3 in the orthostatic position (p < 0.05 for all). Conclusions: Our results suggest that QDC is an inaccurate method for the calibration of RIP. The K values obtained with ISOCAL reveal that RIP should be calibrated for each position evaluated.

Transmission of Human Herpesvirus Type 8 Infection Within Families in American Indigenous Populations From the Brazilian Amazon

Background. The intrafamilial dynamics of endemic infection with human herpesvirus type 8 (HHV-8) in Amerindian populations is unknown. Methods. Serum samples were obtained from 517 Amerindians and tested for HHV-8 anti-latent nuclear antigen (anti-LANA) and antilytic antibodies by immunofluorescence assays. Logistic regression and mixed logistic models were used to estimate the odds of being HHV-8 seropositive among intrafamilial pairs. Results. HHV-8 seroprevalence by either assay was 75.4% (95% confidence interval [CI]: 71.5%-79.1%), and it was age-dependent (P-trend<.001). Familial dependence in HHV-8 seroprevalence by either assay was found between mother-offspring (odds ratio [OR], 5.44; 95% CI: 1.62-18.28) and siblings aged >= 10 years (OR 4.42, 95% CI: 1.70-11.45) or siblings in close age range (<5 years difference) (OR 3.37, 95% CI: 1.21-9.40), or in families with large (>4) number of siblings (OR, 3.20, 95% CI: 1.33-7.67). In separate analyses by serological assay, there was strong dependence in mother-offspring (OR 8.94, 95% CI: 2.94-27.23) and sibling pairs aged >= 10 years (OR, 11.91, 95% CI: 2.23-63.64) measured by LANA but not lytic antibodies. Conclusions. This pattern of familial dependence suggests that, in this endemic population, HHV-8 transmission mainly occurs from mother to offspring and between close siblings during early childhood, probably via saliva. The mother to offspring dependence was derived chiefly from anti-LANA antibodies.

Predicting smear negative pulmonary tuberculosis with classification trees and logistic regression: a cross-sectional study

Abstract Background Smear negative pulmonary tuberculosis (SNPT) accounts for 30% of pulmonary tuberculosis cases reported yearly in Brazil. This study aimed to develop a prediction model for SNPT for outpatients in areas with scarce resources. Methods The study enrolled 551 patients with clinical-radiological suspicion of SNPT, in Rio de Janeiro, Brazil. The original data was divided into two equivalent samples for generation and validation of the prediction models. Symptoms, physical signs and chest X-rays were used for constructing logistic regression and classification and regression tree models. From the logistic regression, we generated a clinical and radiological prediction score. The area under the receiver operator characteristic curve, sensitivity, and specificity were used to evaluate the model's performance in both generation and validation samples. Results It was possible to generate predictive models for SNPT with sensitivity ranging from 64% to 71% and specificity ranging from 58% to 76%. Conclusion The results suggest that those models might be useful as screening tools for estimating the risk of SNPT, optimizing the utilization of more expensive tests, and avoiding costs of unnecessary anti-tuberculosis treatment. Those models might be cost-effective tools in a health care network with hierarchical distribution of scarce resources.

Assessment of variance components in nonlinear mixed-effects elliptical models

The issue of assessing variance components is essential in deciding on the inclusion of random effects in the context of mixed models. In this work we discuss this problem by supposing nonlinear elliptical models for correlated data by using the score-type test proposed in Silvapulle and Silvapulle (1995). Being asymptotically equivalent to the likelihood ratio test and only requiring the estimation under the null hypothesis, this test provides a fairly easy computable alternative for assessing one-sided hypotheses in the context of the marginal model. Taking into account the possible non-normal distribution, we assume that the joint distribution of the response variable and the random effects lies in the elliptical class, which includes light-tailed and heavy-tailed distributions such as Student-t, power exponential, logistic, generalized Student-t, generalized logistic, contaminated normal, and the normal itself, among others. We compare the sensitivity of the score-type test under normal, Student-t and power exponential models for the kinetics data set discussed in Vonesh and Carter (1992) and fitted using the model presented in Russo et al. (2009). Also, a simulation study is performed to analyze the consequences of the kurtosis misspecification.

A model of road effect using line integrals and a test of the performance of two new road indices using the distribution of small mammals in an Atlantic Forest landscape

Effects of roads on wildlife and its habitat have been measured using metrics, such as the nearest road distance, road density, and effective mesh size. In this work we introduce two new indices: (1) Integral Road Effect (IRE), which measured the sum effects of points in a road at a fixed point in the forest; and (2) Average Value of the Infinitesimal Road Effect (AVIRE), which measured the average of the effects of roads at this point. IRE is formally defined as the line integral of a special function (the infinitesimal road effect) along the curves that model the roads, whereas AVIRE is the quotient of IRE by the length of the roads. Combining tools of ArcGIS software with a numerical algorithm, we calculated these and other road and habitat cover indices in a sample of points in a human-modified landscape in the Brazilian Atlantic Forest, where data on the abundance of two groups of small mammals (forest specialists and habitat generalists) were collected in the field. We then compared through the Akaike Information Criterion (AIC) a set of candidate regression models to explain the variation in small mammal abundance, including models with our two new road indices (AVIRE and IRE) or models with other road effect indices (nearest road distance, mesh size, and road density), and reference models (containing only habitat indices, or only the intercept without the effect of any variable). Compared to other road effect indices, AVIRE showed the best performance to explain abundance of forest specialist species, whereas the nearest road distance obtained the best performance to generalist species. AVIRE and habitat together were included in the best model for both small mammal groups, that is, higher abundance of specialist and generalist small mammals occurred where there is lower average road effect (less AVIRE) and more habitat. Moreover, AVIRE was not significantly correlated with habitat cover of specialists and generalists differing from the other road effect indices, except mesh size, which allows for separating the effect of roads from the effect of habitat on small mammal communities. We suggest that the proposed indices and GIS procedures could also be useful to describe other spatial ecological phenomena, such as edge effect in habitat fragments. (C) 2012 Elsevier B.V. All rights reserved.

AGE INFLUENCE ON THE HEART RATE BEHAVIOR ON THE REST-EXERCICIO TRANSITION: AN ANALYSIS BY DELTAS AND LINEAR REGRESSION

Background: Changes in heart rate during rest-exercise transition can be characterized by the application of mathematical calculations, such as deltas 0-10 and 0-30 seconds to infer on the parasympathetic nervous system and linear regression and delta applied to data range from 60 to 240 seconds to infer on the sympathetic nervous system. The objective of this study was to test the hypothesis that young and middle-aged subjects have different heart rate responses in exercise of moderate and intense intensity, with different mathematical calculations. Methods: Seven middle-aged men and ten young men apparently healthy were subject to constant load tests (intense and moderate) in cycle ergometer. The heart rate data were submitted to analysis of deltas (0-10, 0-30 and 60-240 seconds) and simple linear regression (60-240 seconds). The parameters obtained from simple linear regression analysis were: intercept and slope angle. We used the Shapiro-Wilk test to check the distribution of data and the "t" test for unpaired comparisons between groups. The level of statistical significance was 5%. Results: The value of the intercept and delta 0-10 seconds was lower in middle age in two loads tested and the inclination angle was lower in moderate exercise in middle age. Conclusion: The young subjects present greater magnitude of vagal withdrawal in the initial stage of the HR response during constant load exercise and higher speed of adjustment of sympathetic response in moderate exercise.

Different protocols to produce artificial dentine carious lesions in vitro and in situ: hardness and mineral content correlation

This study compared dentine demineralization induced by in vitro and in situ models, and correlated dentine surface hardness (SH), cross-sectional hardness (CSH) and mineral content by transverse microradiography (TMR). Bovine dentine specimens (n = 15/group) were demineralized in vitro with the following: MC gel (6% carboxymethylcellulose gel and 0.1 m lactic acid, pH 5.0, 14 days); buffer I (0.05 m acetic acid solution with calcium, phosphate and fluoride, pH 4.5, 7 days); buffer II (0.05 m acetic acid solution with calcium and phosphate, pH 5.0, 7 days), and TEMDP (0.05 m lactic acid with calcium, phosphate and tetraethyl methyl diphosphonate, pH 5.0, 7 days). In an in situ study, 11 volunteers wore palatal appliances containing 2 bovine dentine specimens, protected with a plastic mesh to allow biofilm development. The volunteers dripped a 20% sucrose solution on each specimen 4 times a day for 14 days. In vitro and in situ lesions were analyzed using TMR and statistically compared by ANOVA. TMR and CSH/SH were submitted to regression and correlation analysis (p < 0.05). The in situ model produced a deep lesion with a high R value, but with a thin surface layer. Regarding the in vitro models, MC gel produced only a shallow lesion, while buffers I and II as well as TEMDP induced a pronounced subsurface lesion with deep demineralization. The relationship between CSH and TMR was weak and not linear. The artificial dentine carious lesions induced by the different models differed significantly, which in turn might influence further de- and remineralization processes. Hardness analysis should not be interpreted with respect to dentine mineral loss

Complexity of inferences in polytree-shaped semi-qualitative probabilistic networks

Semi-qualitative probabilistic networks (SQPNs) merge two important graphical model formalisms: Bayesian networks and qualitative probabilistic networks. They provade a very Complexity of inferences in polytree-shaped semi-qualitative probabilistic networks and qualitative probabilistic networks. They provide a very general modeling framework by allowing the combination of numeric and qualitative assessments over a discrete domain, and can be compactly encoded by exploiting the same factorization of joint probability distributions that are behind the bayesian networks. This paper explores the computational complexity of semi-qualitative probabilistic networks, and takes the polytree-shaped networks as its main target. We show that the inference problem is coNP-Complete for binary polytrees with multiple observed nodes. We also show that interferences can be performed in time linear in the number of nodes if there is a single observed node. Because our proof is construtive, we obtain an efficient linear time algorithm for SQPNs under such assumptions. To the best of our knowledge, this is the first exact polynominal-time algorithm for SQPn. Together these results provide a clear picture of the inferential complexity in polytree-shaped SQPNs.

Testing phenomenological and theoretical models of dark matter density profiles with galaxy clusters

We use the stacked gravitational lensingmass profile of four high-mass (M 1015M ) galaxy clusters around z≈0.3 from Umetsu et al. to fit density profiles of phenomenological [Navarro– Frenk–White (NFW), Einasto, S´ersic, Stadel, Baltz–Marshall–Oguri (BMO) and Hernquist] and theoretical (non-singular Isothermal Sphere, DARKexp and Kang & He) models of the dark matter distribution. We account for large-scale structure effects, including a two-halo term in the analysis.We find that the BMO model provides the best fit to the data as measured by the reduced χ2. It is followed by the Stadel profile, the generalized NFW profile with a free inner slope and by the Einasto profile. The NFW model provides the best fit if we neglect the two-halo term, in agreement with results from Umetsu et al. Among the theoretical profiles, the DARKexp model with a single form parameter has the best performance, very close to that of the BMO profile. This may indicate a connection between this theoretical model and the phenomenology of dark matter haloes, shedding light on the dynamical basis of empirical profiles which emerge from numerical simulations.