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.

Forest structure of artificial islands in the Tucuruí dam reservoir in northern Brazil: a test core-area model

Construction of hydroelectric dams in tropical regions has been contributing significantly to forest fragmentation. Alterations at edges of forest fragments impact plant communities that suffer increases in tree damage and dead, and decreases in seedling recruitment. This study aimed to test the core-area model in a fragmented landscape caused by construction of a hydroelectric power plant in the Brazilian Amazon. We studied variations in forest structure between the margin and interiors of 17 islands of 8-100 hectares in the Tucuruí dam reservoir, in two plots (30 and >100m from the margin) per island. Mean tree density, basal area, seedling density and forest cover did not significantly differ between marginal and interior island plots. Also, no significant differences were found in liana density, dead tree or damage for margin and interior plots. The peculiar topographic conditions associated with the matrix habitat and shapes of the island seem to extend edge effects to the islands' centers independently of the island size, giving the interior similar physical microclimatic conditions as at the edges. We propose a protocol for assessing the ecological impacts of edge effects in fragments of natural habitat surrounded by induced (artificial) edges. The protocol involves three steps: (1) identification of focal taxa of particular conservation or management interest, (2) measurement of an "edge function" that describes the response of these taxa to induced edges, and (3) use of a "Core-Area Model" to extrapolate edge function parameters to existing or novel situations.

Effects of selection and drift on G matrix evolution in a heterogeneous environment: a multivariate Qst-Fst Test with the freshwater snail Galba truncatula.

Unraveling the effect of selection vs. drift on the evolution of quantitative traits is commonly achieved by one of two methods. Either one contrasts population differentiation estimates for genetic markers and quantitative traits (the Q(st)-F(st) contrast) or multivariate methods are used to study the covariance between sets of traits. In particular, many studies have focused on the genetic variance-covariance matrix (the G matrix). However, both drift and selection can cause changes in G. To understand their joint effects, we recently combined the two methods into a single test (accompanying article by Martin et al.), which we apply here to a network of 16 natural populations of the freshwater snail Galba truncatula. Using this new neutrality test, extended to hierarchical population structures, we studied the multivariate equivalent of the Q(st)-F(st) contrast for several life-history traits of G. truncatula. We found strong evidence of selection acting on multivariate phenotypes. Selection was homogeneous among populations within each habitat and heterogeneous between habitats. We found that the G matrices were relatively stable within each habitat, with proportionality between the among-populations (D) and the within-populations (G) covariance matrices. The effect of habitat heterogeneity is to break this proportionality because of selection for habitat-dependent optima. Individual-based simulations mimicking our empirical system confirmed that these patterns are expected under the selective regime inferred. We show that homogenizing selection can mimic some effect of drift on the G matrix (G and D almost proportional), but that incorporating information from molecular markers (multivariate Q(st)-F(st)) allows disentangling the two effects.

Establishing an association between a peri-operative perfusion score system (PerfSCORE) and post-operative patient morbidity/mortality during CPB cardiac surgery.

BACKGROUND: To date, there is no quality assurance program that correlates patient outcome to perfusion service provided during cardiopulmonary bypass (CPB). A score was devised, incorporating objective parameters that would reflect the likelihood to influence patient outcome. The purpose was to create a new method for evaluating the quality of care the perfusionist provides during CPB procedures and to deduce whether it predicts patient morbidity and mortality. METHODS: We analysed 295 consecutive elective patients. We chose 10 parameters: fluid balance, blood transfused, Hct, ACT, PaO2, PaCO2, pH, BE, potassium and CPB time. Distribution analysis was performed using the Shapiro-Wilcoxon test. This made up the PerfSCORE and we tried to find a correlation to mortality rate, patient stay in the ICU and length of mechanical ventilation. Univariate analysis (UA) using linear regression was established for each parameter. Statistical significance was established when p < 0.05. Multivariate analysis (MA) was performed with the same parameters. RESULTS: The mean age was 63.8 +/- 12.6 years with 70% males. There were 180 CABG, 88 valves, and 27 combined CABG/valve procedures. The PerfSCORE of 6.6 +/- 2.4 (0-20), mortality of 2.7% (8/295), CPB time 100 +/- 41 min (19-313), ICU stay 52 +/- 62 hrs (7-564) and mechanical ventilation of 10.5 +/- 14.8 hrs (0-564) was calculated. CPB time, fluid balance, PaO2, PerfSCORE and blood transfused were significantly correlated to mortality (UA, p < 0.05). Also, CPB time, blood transfused and PaO2 were parameters predicting mortality (MA, p < 0.01). Only pH was significantly correlated for predicting ICU stay (UA). Ultrafiltration (UF) and CPB time were significantly correlated (UA, p < 0.01) while UF (p < 0.05) was the only parameter predicting mechanical ventilation duration (MA). CONCLUSIONS: CPB time, blood transfused and PaO2 are independent risk factors of mortality. Fluid balance, blood transfusion, PaO2, PerfSCORE and CPB time are independent parameters for predicting morbidity. PerfSCORE is a quality of perfusion measure that objectively quantifies perfusion performance.

Predictors of HIV-protection behaviour in HIV-positive men who have sex with casual male partners: a test of the explanatory power of an extended Information-Motivation-Behavioural Skills model.

This prospective study applies an extended Information-Motivation-Behavioural Skills (IMB) model to establish predictors of HIV-protection behaviour among HIV-positive men who have sex with men (MSM) during sex with casual partners. Data have been collected from anonymous, self-administered questionnaires and analysed by using descriptive and backward elimination regression analyses. In a sample of 165 HIV-positive MSM, 82 participants between the ages of 23 and 78 (M=46.4, SD=9.0) had sex with casual partners during the three-month period under investigation. About 62% (n=51) have always used a condom when having sex with casual partners. From the original IMB model, only subjective norm predicted condom use. More important predictors that increased condom use were low consumption of psychotropics, high satisfaction with sexuality, numerous changes in sexual behaviour after diagnosis, low social support from friends, alcohol use before sex and habitualised condom use with casual partner(s). The explanatory power of the calculated regression model was 49% (p<0.001). The study reveals the importance of personal and social resources and of routines for condom use, and provides information for the research-based conceptualisation of prevention offers addressing especially people living with HIV ("positive prevention").

Test of four colon cancer risk-scores in formalin fixed paraffin embedded microarray gene expression data.

BACKGROUND: Prognosis prediction for resected primary colon cancer is based on the T-stage Node Metastasis (TNM) staging system. We investigated if four well-documented gene expression risk scores can improve patient stratification. METHODS: Microarray-based versions of risk-scores were applied to a large independent cohort of 688 stage II/III tumors from the PETACC-3 trial. Prognostic value for relapse-free survival (RFS), survival after relapse (SAR), and overall survival (OS) was assessed by regression analysis. To assess improvement over a reference, prognostic model was assessed with the area under curve (AUC) of receiver operating characteristic (ROC) curves. All statistical tests were two-sided, except the AUC increase. RESULTS: All four risk scores (RSs) showed a statistically significant association (single-test, P < .0167) with OS or RFS in univariate models, but with HRs below 1.38 per interquartile range. Three scores were predictors of shorter RFS, one of shorter SAR. Each RS could only marginally improve an RFS or OS model with the known factors T-stage, N-stage, and microsatellite instability (MSI) status (AUC gains < 0.025 units). The pairwise interscore discordance was never high (maximal Spearman correlation = 0.563) A combined score showed a trend to higher prognostic value and higher AUC increase for OS (HR = 1.74, 95% confidence interval [CI] = 1.44 to 2.10, P < .001, AUC from 0.6918 to 0.7321) and RFS (HR = 1.56, 95% CI = 1.33 to 1.84, P < .001, AUC from 0.6723 to 0.6945) than any single score. CONCLUSIONS: The four tested gene expression-based risk scores provide prognostic information but contribute only marginally to improving models based on established risk factors. A combination of the risk scores might provide more robust information. Predictors of RFS and SAR might need to be different.

Predictors of trabecular bone score in school children.

UNLABELLED: Trabecular bone score (TBS) is a DXA-based tool that assesses bone texture and reflects microarchitecture. It has been shown to independently predict the risk of osteoporotic fracture in the elderly. In this study, we investigated the determinants of TBS in adolescents. INTRODUCTION: TBS is a gray-level textural measurement derived from lumbar spine DXA images. It appears to be an index of bone microarchitecture that provides skeletal information additional to the standard BMD measurement and clinical risk factors. Our objectives were to characterize the relationship between TBS and both age and pubertal stages and identify other predictors in adolescents. METHODS: We assessed TBS by reanalyzing spine DXA scan images obtained from 170 boys and 168 girls, age range 10-17 years, gathered at study entry and at 1 year, using TBS software. The results are from post hoc analyses obtained using data gathered from a prospective randomized vitamin D trial. Predictors of TBS were assessed using t test or Pearson's correlation and adjusted using regression analyses, as applicable. RESULTS: The mean age of the study population was 13.2 ± 2.1 years, similar between boys and girls. Age, height, weight, sun exposure, spine BMC and BMD, body BMC and BMD, and lean and fat mass are all significantly correlated with TBS at baseline (r = 0.20-0.75, p < 0.035). Correlations mostly noted in late-pubertal stages. However, after adjustment for BMC, age remained an independent predictor only in girls. CONCLUSIONS: In univariate exploratory analyses, age and pubertal stages were determinants of TBS in adolescents. Studies to investigate predictors of TBS and to investigate its value as a prognostic tool of bone fragility in the pediatric population are needed.

Trabecular bone score in kidney transplant recipients.

UNLABELLED: It is uncertain whether bone mineral density (BMD) can accurately predict fracture in kidney transplant recipients. Trabecular bone score (TBS) provides information independent of BMD. Kidney transplant recipients had abnormal bone texture as measured by lumbar spine TBS, and a lower TBS was associated with incident fractures in recipients. INTRODUCTION: Trabecular bone score (TBS) is a texture measure derived from dual energy X-ray absorptiometry (DXA) lumbar spine images, providing information independent of bone mineral density. We assessed characteristics associated with TBS and fracture outcomes in kidney transplant recipients. METHODS: We included 327 kidney transplant recipients from Manitoba, Canada, who received a post-transplant DXA (median 106 days post-transplant). We matched each kidney transplant recipient (mean age 45 years, 39 % men) to three controls from the general population (matched on age, sex, and DXA date). Lumbar spine (L1-L4) DXA images were used to derive TBS. Non-traumatic incident fracture (excluding hand, foot, and craniofacial) (n = 31) was assessed during a mean follow-up of 6.6 years. We used multivariable linear regression models to test predictors of TBS, and multivariable Cox proportional hazard regression was used to estimate hazard ratios (HRs) per standard deviation decrease in TBS to express the gradient of risk. RESULTS: Compared to the general population, kidney transplant recipients had a significantly lower lumbar spine TBS (1.365 ± 0.129 versus 1.406 ± 0.125, P < 0.001). Multivariable linear regression revealed that receipt of a kidney transplant was associated with a significantly lower mean TBS compared to controls (-0.0369, 95 % confidence interval [95 % CI] -0.0537 to -0.0202). TBS was associated with fractures independent of the Fracture Risk Assessment score including BMD (adjusted HR per standard deviation decrease in TBS 1.64, 95 % CI 1.15-2.36). CONCLUSION: Kidney transplant recipients had abnormal bone texture as assessed by TBS and a lower lumbar spine TBS was associated with fractures in recipients.

A sparse kernel density estimation algorithm using forward constrained regression

Using the classical Parzen window (PW) estimate as the target function, the sparse kernel density estimator is constructed in a forward constrained regression manner. The leave-one-out (LOO) test score is used for kernel selection. The jackknife parameter estimator subject to positivity constraint check is used for the parameter estimation of a single parameter at each forward step. As such the proposed approach is simple to implement and the associated computational cost is very low. An illustrative example is employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with comparable accuracy to that of the classical Parzen window estimate.

Importance of estimating matrix quality for modeling species distribution in complex tropical landscapes: a test with Atlantic forest small mammals

Information to guide decision making is especially urgent in human dominated landscapes in the tropics, where urban and agricultural frontiers are still expanding in an unplanned manner. Nevertheless, most studies that have investigated the influence of landscape structure on species distribution have not considered the heterogeneity of altered habitats of the matrix, which is usually high in human dominated landscapes. Using the distribution of small mammals in forest remnants and in the four main altered habitats in an Atlantic forest landscape, we investigated 1) how explanatory power of models describing species distribution in forest remnants varies between landscape structure variables that do or do not incorporate matrix quality and 2) the importance of spatial scale for analyzing the influence of landscape structure. We used standardized sampling in remnants and altered habitats to generate two indices of habitat quality, corresponding to the abundance and to the occurrence of small mammals. For each remnant, we calculated habitat quantity and connectivity in different spatial scales, considering or not the quality of surrounding habitats. The incorporation of matrix quality increased model explanatory power across all spatial scales for half the species that occurred in the matrix, but only when taking into account the distance between habitat patches (connectivity). These connectivity models were also less affected by spatial scale than habitat quantity models. The few consistent responses to the variation in spatial scales indicate that despite their small size, small mammals perceive landscape features at large spatial scales. Matrix quality index corresponding to species occurrence presented a better or similar performance compared to that of species abundance. Results indicate the importance of the matrix for the dynamics of fragmented landscapes and suggest that relatively simple indices can improve our understanding of species distribution, and could be applied in modeling, monitoring and managing complex tropical landscapes.

Test score disclosure and school performance

In this paper we test whether the disclosure of test scores has direct impacts on student performance, school composition and school inputs. We take advantage of the discontinuity on the disclosure rules of The National Secondary Education Examination (ENEM) run in Brazil by the Ministry of Education: In 2006 it was established that the 2005 mean score results would be disclosed for schools with ten or more students who took the exam in the previous year. We use a regression discontinuity design to estimate the e ects of test disclosure. Our results indicate that private schools that had their average scores released in 2005 outperformed those that did not by 0.2-0.6 in 2007. We did not nd same results for public schools. Moreover, we did not nd evidence that treated schools adjusted their inputs or that there was major changes in the students composition of treated schools. These ndings allow us to interpret that the main mechanism driving the di erences in performance was the increased levels of students', teachers' and principals' e ort exerted by those in schools that had scores publicized.

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

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Variance component estimates applying random regression models for test-day milk yield in Caracu heifers (Bos taurus Artiodactyla, Bovidae)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Random regression models using Legendre polynomials or linear splines for test-day milk yield of dairy Gyr (Bos indicus) cattle

Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and Bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that, in practice, the same bulls would be selected by both models. The last model, which is less parameterized, is a parsimonious option for fitting dairy Gyr breed test-day milk yield records. © 2013 American Dairy Science Association.