Estimates of genetic trend for carcass traits in a commercial broiler line

Data from the slaughter of 24,001 chickens that were part of a selection program for the production of commercial broilers were used to estimate genetic trend for absolute carcass (CW), breast meat (BRW), and leg (LW) weights, and relative carcass (CY), breast meat (BRY), and leg (LY) weights. The components of (co) variance and breeding values of individuals were obtained by the restricted maximum likelihood method applied to animal models. The relationship matrix was composed of 132,442 birds. The models included as random effects, maternal additive genetic and permanent environmental for CW, BRW, LW, CY, and BRY, and only maternal permanent environmental for LY, besides the direct additive genetic and residual effects, and as fixed effects, hatch week, parents' mating group and sex. The estimates of genetic trend were obtained by average regression of breeding value on generation, and the average genetic trend was estimated by regression coefficients. The genetic trends for CW (+ 6.0336 g/generation), BRW (+ 3.6723 g/generation), LW (+ 1.5846 g/generation), CY (+ 0.1195%/generation), and BRY (+ 0.1388%/generation) were positive, and they were in accordance with the objectives of the selection program for these traits. The genetic trend for LY(-0.0019%/generation) was negative, possibly due to the strong emphasis on selection for BRY and the negative correlations between these two traits.

Fatores gravimétricos no Brasil para um modelo anelástico de Terra

Geodetic observations are affected by the disturbing potential of the luni-solar tide. Among those observations, the value of g obtained from gravimetric survey needs correction by the gravimetric factor. This correction is derived from the Numbers of Love, which depend on the adopted model of Earth. Because of this, it is necessary to update the correction since the gravimetric factor widely used in Brazil as delta = 1.20 does not consider local rheological variations and they are latitude dependent. A discrepancy of about 1% between the observed tidal gravimetric factors d of the ""Trans World Tidal Gravity Profiles"" (TWTGP), related to Brussels fundamental station, and those obtained by recent observations reported by Freitas and Ducarme ( 1991). Experiments based on inertial force effects also reveal a variation of about 0.5% in the observed d. A same order of magnitude difference is obtained for an anelastic Earth model when compared with a viscous-elastic model and even when different frequencies of tidal perturbations are considered. In this paper regression models are presented for gravimetric factors for the lunar components O(1) and M(2) in Brazil. These models were obtained from observations performed at stations belonging to the Brazilian segment of the TWTGP.

Espacialização da temperatura do ar anual no estado de Alagoas com diferentes modelos digitais de elevação e resoluções espaciais

The aim of this study was to establish a digital elevation model and its horizontal resolution to interpolate the annual air temperature for the Alagoas State by means of multiple linear regression models. A multiple linear regression model was adjusted to series (11 to 34 years) of annual air temperatures obtained from 28 weather stations in the states of Alagoas, Bahia, Pernambuco and Sergipe, in the Northeast of Brazil, in function of latitude, longitude and altitude. The elevation models SRTM and GTOPO30 were used in the analysis, with original resolutions of 90 and 900 m, respectively. The SRTM was resampled for horizontal resolutions of 125, 250, 500, 750 and 900 m. For spatializing the annual mean air temperature for the state of Alagoas, a multiple linear regression model was used for each elevation and spatial resolution on a grid of the latitude and longitude. In Alagoas, estimates based on SRTM data resulted in a standard error of estimate (0.57 degrees C) and dispersion (r(2) = 0.62) lower than those obtained from GTOPO30 (0.93 degrees C and 0.20). In terms of SRTM resolutions, no significant differences were observed between the standard error (0.55 degrees C; 750 m - 0.58 degrees C; 250m) and dispersion (0.60; 500 m - 0.65; 750 m) estimates. The spatialization of annual air temperature in Alagoas, via multiple regression models applied to SRTM data showed higher concordance than that obtained with the GTOPO30, independent of the spatial resolution.

Hepatitis B Infection Is Associated with Asymptomatic Malaria in the Brazilian Amazon

Background: Areas that are endemic for malaria are also highly endemic for hepatitis B virus (HBV) infection. Nevertheless, it is unknown whether HBV infection modifies the clinical presentation of malaria. This study aimed to address this question. Methodology and Findings: An observational study of 636 individuals was performed in Rondonia, western Amazon, Brazil between 2006 and 2007. Active and passive case detections identified Plasmodium infection by field microscopy and nested Polymerase Chain Reaction (PCR). HBV infections were identified by serology and confirmed by real-time PCR. Epidemiological information and plasma cytokine profiles were studied. The data were analyzed using adjusted multinomial logistic regression. Plasmodium-infected individuals with active HBV infection were more likely to be asymptomatic (OR: 120.13, P < 0.0001), present with lower levels of parasitemia and demonstrate a decreased inflammatory cytokine profile. Nevertheless, co-infected individuals presented higher HBV viremia. Plasmodium parasitemia inversely correlated with plasma HBV DNA levels (r=-0.6; P=0.0003). Conclusion: HBV infection diminishes the intensity of malaria infection in individuals from this endemic area. This effect seems related to cytokine balance and control of inflammatory responses. These findings add important insights to the understanding of the factors affecting the clinical outcomes of malaria in endemic regions.

INFERENCE FOR EIGENVALUES AND EIGENVECTORS OF GAUSSIAN SYMMETRIC MATRICES

This article presents maximum likelihood estimators (MLEs) and log-likelihood ratio (LLR) tests for the eigenvalues and eigenvectors of Gaussian random symmetric matrices of arbitrary dimension, where the observations are independent repeated samples from one or two populations. These inference problems are relevant in the analysis of diffusion tensor imaging data and polarized cosmic background radiation data, where the observations are, respectively, 3 x 3 and 2 x 2 symmetric positive definite matrices. The parameter sets involved in the inference problems for eigenvalues and eigenvectors are subsets of Euclidean space that are either affine subspaces, embedded submanifolds that are invariant under orthogonal transformations or polyhedral convex cones. We show that for a class of sets that includes the ones considered in this paper, the MLEs of the mean parameter do not depend on the covariance parameters if and only if the covariance structure is orthogonally invariant. Closed-form expressions for the MLEs and the associated LLRs are derived for this covariance structure.

The impact of measurement errors in the identification of regulatory networks

Background: There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results: This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent) and non-time series (independent) data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models) and dependent (autoregressive models) data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error). The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions: Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.

Non-Cardiac Surgery in Developing Countries: Epidemiological Aspects and Economical Opportunities - The Case of Brazil

Background: Worldwide distribution of surgical interventions is unequal. Developed countries account for the majority of surgeries and information about non-cardiac operations in developing countries is scarce. The purpose of our study was to describe the epidemiological data of non-cardiac surgeries performed in Brazil in the last years. Methods and Findings: This is a retrospective cohort study that investigated the time window from 1995 to 2007. We collected information from DATASUS, a national public health system database. The following variables were studied: number of surgeries, in-hospital expenses, blood transfusion related costs, length of stay and case fatality rates. The results were presented as sum, average and percentage. The trend analysis was performed by linear regression model. There were 32,659,513 non-cardiac surgeries performed in Brazil in thirteen years. An increment of 20.42% was observed in the number of surgeries in this period and nowadays nearly 3 million operations are performed annually. The cost of these procedures has increased tremendously in the last years. The increment of surgical cost was almost 200%. The total expenses related to surgical hospitalizations were more than $10 billion in all these years. The yearly cost of surgical procedures to public health system was more than $1.27 billion for all surgical hospitalizations, and in average, U$445.24 per surgical procedure. The total cost of blood transfusion was near $98 million in all years and annually approximately $10 million were spent in perioperative transfusion. The surgical mortality had an increment of 31.11% in the period. Actually, in 2007, the surgical mortality in Brazil was 1.77%. All the variables had a significant increment along the studied period: r square (r(2)) = 0.447 for the number of surgeries (P = 0.012), r(2) = 0.439 for in-hospital expenses (P = 0.014) and r(2) = 0.907 for surgical mortality (P = 0.0055). Conclusion: The volume of surgical procedures has increased substantially in Brazil through the past years. The expenditure related to these procedures and its mortality has also increased as the number of operations. Better planning of public health resource and strategies of investment are needed to supply the crescent demand of surgery in Brazil.

An oracle approach for interaction neighborhood estimation in random fields

We consider the problem of interaction neighborhood estimation from the partial observation of a finite number of realizations of a random field. We introduce a model selection rule to choose estimators of conditional probabilities among natural candidates. Our main result is an oracle inequality satisfied by the resulting estimator. We use then this selection rule in a two-step procedure to evaluate the interacting neighborhoods. The selection rule selects a small prior set of possible interacting points and a cutting step remove from this prior set the irrelevant points. We also prove that the Ising models satisfy the assumptions of the main theorems, without restrictions on the temperature, on the structure of the interacting graph or on the range of the interactions. It provides therefore a large class of applications for our results. We give a computationally efficient procedure in these models. We finally show the practical efficiency of our approach in a simulation study.

Application of electron paramagnetic resonance Spectroscopy for validation of the novel (AN plus DN) solvent polarity scale

Based on solvation studies of polymers, the sum (1: 1) of the electron acceptor (AN) and electron donor (DN) values of solvents has been proposed as an alternative polarity scale. To test this, the electron paramagnetic resonance isotropic hyperfine splitting constant, a parameter known to be dependent on the polarity/proticity of the medium, was correlated with the (AN+DN) term using three paramagnetic probes. The linear regression coefficient calculated for 15 different solvents was approximately 0.9, quite similar to those of other well-known polarity parameters, attesting to the validity of the (AN+DN) term as a novel ""two-parameter"" solvent polarity scale.

Interaction between polymorphisms of the Human Leukocyte Antigen and HPV-16 Variants on the risk of invasive cervical cancer

Background: Persistent infection with oncogenic types of human papillomavirus (HPV) is the major risk factor for invasive cervical cancer (ICC), and non-European variants of HPV-16 are associated with an increased risk of persistence and ICC. HLA class II polymorphisms are also associated with genetic susceptibility to ICC. Our aim is to verify if these associations are influenced by HPV-16 variability. Methods: We characterized HPV-16 variants by PCR in 107 ICC cases, which were typed for HLA-DQA1, DRB1 and DQB1 genes and compared to 257 controls. We measured the magnitude of associations by logistic regression analysis. Results: European ( E), Asian-American ( AA) and African (Af) variants were identified. Here we show that inverse association between DQB1*05 ( adjusted odds ratio [ OR] = 0.66; 95% confidence interval [CI]: 0.39-1.12]) and HPV-16 positive ICC in our previous report was mostly attributable to AA variant carriers ( OR = 0.27; 95% CI: 0.10-0.75). We observed similar proportions of HLA DRB1*1302 carriers in E-P positive cases and controls, but interestingly, this allele was not found in AA cases ( p = 0.03, Fisher exact test). A positive association with DRB1*15 was observed in both groups of women harboring either E ( OR = 2.99; 95% CI: 1.13-7.86) or AA variants ( OR = 2.34; 95% CI: 1.00-5.46). There was an inverse association between DRB1*04 and ICC among women with HPV-16 carrying the 350T [83L] single nucleotide polymorphism in the E6 gene ( OR = 0.27; 95% CI: 0.08-0.96). An inverse association between DQB1*05 and cases carrying 350G (83V) variants was also found ( OR = 0.37; 95% CI: 0.15-0.89). Conclusion: Our results suggest that the association between HLA polymorphism and risk of ICC might be influenced by the distribution of HPV-16 variants.

Definindo a arena política local: sistemas partidários municipais na federação brasileira

This article analyzes the Brazilian political system from the local perspective. Following Cox (1997), we review the problems with electoral coordination that emerge from a given institutional framework. Due to the characteristics of the Brazilian Federal system and its electoral rules, linkage between the three levels of government is not guaranteed a priori, but demands a coordinating effort by the parties' leadership. According to our hypothesis, the parties are capable of coordinating their election strategies at different levels in the party system. Regression models based on two-stage least squares (2SLS) and TOBIT, analyzing a panel of Brazilian municipalities with data from the 1994 and 2000 elections, show that the proportion of votes received by a party in a given election correlates closely with its previous votes in majoritarian elections. Despite institutional incentives, the Brazilian party system shows evidence that it is organized nationally to the extent that it links the competition for votes at the three levels of government (National, State, and Municipal).

Do plant species influence soil CO(2) and N(2)O fluxes in a diverse tropical forest?

To test whether plant species influence greenhouse gas production in diverse ecosystems, we measured wet season soil CO(2) and N(2)O fluxes close to similar to 300 large (>35 cm in diameter at breast height (DBH)) trees of 15 species at three clay-rich forest sites in central Amazonia. We found that soil CO(2) fluxes were 38% higher near large trees than at control sites >10 m away from any tree (P < 0.0001). After adjusting for large tree presence, a multiple linear regression of soil temperature, bulk density, and liana DBH explained 19% of remaining CO(2) flux variability. Soil N(2)O fluxes adjacent to Caryocar villosum, Lecythis lurida, Schefflera morototoni, and Manilkara huberi were 84%-196% greater than Erisma uncinatum and Vochysia maxima, both Vochysiaceae. Tree species identity was the most important explanatory factor for N(2)O fluxes, accounting for more than twice the N(2)O flux variability as all other factors combined. Two observations suggest a mechanism for this finding: (1) sugar addition increased N(2)O fluxes near C. villosum twice as much (P < 0.05) as near Vochysiaceae and (2) species mean N(2)O fluxes were strongly negatively correlated with tree growth rate (P = 0.002). These observations imply that through enhanced belowground carbon allocation liana and tree species can stimulate soil CO(2) and N(2)O fluxes (by enhancing denitrification when carbon limits microbial metabolism). Alternatively, low N(2)O fluxes potentially result from strong competition of tree species with microbes for nutrients. Species-specific patterns in CO(2) and N(2)O fluxes demonstrate that plant species can influence soil biogeochemical processes in a diverse tropical forest.

Near infrared spectroscopy for soil bulk density assessment

P>Soil bulk density values are needed to convert organic carbon content to mass of organic carbon per unit area. However, field sampling and measurement of soil bulk density are labour-intensive, costly and tedious. Near-infrared reflectance spectroscopy (NIRS) is a physically non-destructive, rapid, reproducible and low-cost method that characterizes materials according to their reflectance in the near-infrared spectral region. The aim of this paper was to investigate the ability of NIRS to predict soil bulk density and to compare its performance with published pedotransfer functions. The study was carried out on a dataset of 1184 soil samples originating from a reforestation area in the Brazilian Amazon basin, and conventional soil bulk density values were obtained with metallic ""core cylinders"". The results indicate that the modified partial least squares regression used on spectral data is an alternative method for soil bulk density predictions to the published pedotransfer functions tested in this study. The NIRS method presented the closest-to-zero accuracy error (-0.002 g cm-3) and the lowest prediction error (0.13 g cm-3) and the coefficient of variation of the validation sets ranged from 8.1 to 8.9% of the mean reference values. Nevertheless, further research is required to assess the limits and specificities of the NIRS method, but it may have advantages for soil bulk density predictions, especially in environments such as the Amazon forest.

Soil organic carbon and fertility interactions affected by a tillage chronosequence in a Brazilian Oxisol

No-till (NT) adoption is an essential tool for development of sustainable agricultural systems, and how NT affects the soil organic C (SOC) dynamics is a key component of these systems. The effect of a plow tillage (PT) and NT age chronosequence on SOC concentration and interactions with soil fertility were assessed in a variable charge Oxisol, located in the South Center quadrant of Parana State, Brazil (50 degrees 23`W and 24 degrees 36`S). The chronosequence consisted of the following six sites: (i) native field (NF); (ii) PT of the native field (PNF-1) involving conversion of natural vegetation to cropland; (iii) NT for 10 years (NT-10); (iv) NT for 20 years (NT-20); (v) NT for 22 years (NT-22); and (vi) conventional tillage for 22 years (CT-22) involving PT with one disking after summer harvest and one after winter harvest to 20 cm depth plus two harrow disking. Soil samples were collected from five depths (0-2.5; 2.5-5; 5-10; 10-20; and 20-40 cm) and SOC, pH (in H(2)O and KCl), Delta pH, potential acidity, exchangeable bases, and cation exchangeable capacity (CEC) were measured. An increase in SOC concentration positively affected the pH, the negative charge and the CEC and negatively impacted potential acidity. Regression analyses indicated a close relationship between the SOC concentration and other parameters measured in this study. The regression fitted between SOC concentration and CEC showed a close relationship. There was an increase in negative charge and CEC with increase in SOC concentration: CEC increased by 0.37 cmol(c) kg(-1) for every g of C kg(-1) soil. The ratio of ECEC:SOC was 0.23 cmol(c) kg(-1) for NF and increased to 0.49 cmol(c) kg(-1) for NT-22. The rates of P and K for 0-10 cm depth increased by 9.66 kg ha(-1) yr(-1) and 17.93 kg ha(-1) yr(-1), respectively, with NF as a base line. The data presented support the conclusion that long-term NT is a useful strategy for improving fertility of soils with variable charge. (C) 2008 Elsevier B.V. All rights reserved.