Maternal obesity in high-risk pregnancies and postpartum infectious complications

Objective: To analyze the association between maternal obesity and postnatal infectious complications in high-risk pregnancies. Methods: Prospective study from August 2009 through August 2010 with the following inclusion criteria: women up to the 5th postpartum day; age L 18 years; high-risk pregnancy; singleton pregnancy with live fetus at labor onset; delivery at the institution; maternal weight measured on day of delivery. The nutritional status in late pregnancy was assessed by the body mass index (BMI), with the application of the Atalah et al. curve. Patients were graded as underweight, adequate weight, overweight, or obese. Postpartum complications investigated during the hospital stay and 30 days post-discharge were: surgical wound infection and/or secretion, urinary infection, postpartum infection, fever, hospitalization, antibiotic use, and composite morbidity (at least one of the complications mentioned). Results: 374 puerperal women were included, graded according to the final BMI as: underweight (n = 54, 14.4%); adequate weight (n = 126, 33.7%); overweight (n = 105, 28.1%); and obese (n = 89, 23.8%). Maternal obesity was shown to have a significant association with the following postpartum complications: surgical wound infection (16.7%, p = 0.042), urinary infection (9.0%, p = 0.004), antibiotic use (12.3%, p < 0.001), and composite morbidity (25.6%, p = 0.016). By applying the logistic regression model, obesity in late pregnancy was found to be an independent variable regardless of the composite morbidity predicted (OR: 2.09; 95% CI: 1.15-3.80, p = 0.015). Conclusion: Maternal obesity during late pregnancy in high-risk patients is independently associated with postpartum infectious complications, which demonstrates the need for a closer follow-up of maternal weight gain in these pregnancies.

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.

Bayesian Analysis for Errors in Variables with Changepoint Models

Changepoint regression models have originally been developed in connection with applications in quality control, where a change from the in-control to the out-of-control state has to be detected based on the avaliable random observations. Up to now various changepoint models have been suggested for differents applications like reliability, econometrics or medicine. In many practical situations the covariate cannot be measured precisely and an alternative model are the errors in variable regression models. In this paper we study the regression model with errors in variables with changepoint from a Bayesian approach. From the simulation study we found that the proposed procedure produces estimates suitable for the changepoint and all other model parameters.

MUC1 gene polymorphism in three Nelore lines selected for growth and its association with growth and carcass traits

The objective of this study was to describe the VNTR polymorphism of the mucin 1 gene (MUC1) in three Nelore lines selected for yearling weight to determine whether allele and genotype frequencies of this polymorphism were affected by selection for growth. In addition, the effects of the polymorphism on growth and carcass traits were evaluated. Birth, weaning and yearling weights, rump height, Longissimus muscle area, backfat thickness, and rump fat thickness, were analyzed. A total of 295 Nelore heifers from the Beef Cattle Research Center, Instituto de Zootecnia de Sertozinho, were used, including 41 of the control line, 102 of the selection line and 152 of the traditional. The selection and traditional lines comprise animals selected for higher yearling weight, whereas control line animals are selected for yearling weight close to the average. Five alleles were identified, with allele 1 being the most frequent in the three lines, especially in the lines selected for higher means for yearling weight. Heterozygosity was significantly higher in the control line. Association analyses showed significant effects of allele 1 on birth weight and weaning weight while the allele 3 exert significant effects on yearling weight and back fat thickness. Despite these findings, application of this marker to marker-assisted selection requires more consistent results based on the genotyping of a larger number of animals in order to increase the accuracy of the statistical analyses.

Costs and benefits of temporary brood desertion in a Neotropical harvestman (Arachnida: Opiliones)

Brood desertion is a life history strategy that allows parents to minimize costs related to parental care and increase their future fecundity. The harvestman Neosadocus maximus is an interesting model organism to study costs and benefits of temporary brood desertion because females abandon their clutches periodically and keep adding eggs to their clutches for some weeks. In this study, we tested if temporary brood desertion (a) imposes a cost to caring females by increasing the risk of egg predation and (b) offers a benefit to caring females by increasing fecundity as a result of increased foraging opportunities. With intensive field observations followed by a model selection approach, we showed that the proportion of consumed eggs was very low during the day and it was not influenced by the frequency of brood desertion. The proportion of consumed eggs was higher at night and it was negatively related to the frequency of brood desertion. However, frequent brood desertion did not result in higher fecundity, measured both as the number of eggs added to the current clutch and the probability of laying a second clutch over the course of the reproductive season. Considering that harvestmen are sensitive to dehydration, brood desertion during the day may attenuate the physiological stress of remaining exposed on the vegetation. Moreover, since brood desertion is higher during the day, when egg predation pressure is lower, caring females could be adjusting their maternal effort to the temporal variation in predation risk, which is regarded as the main cost of brood desertion in ectotherms.

The importance of mesofauna and decomposition environment on leaf decomposition in three forests in southeastern Brazil

We examined the effects of soil mesofauna and the litter decomposition environment (above and belowground) on leaf decomposition rates in three forest types in southeastern Brazil. To estimate decomposition experimentally, we used litterbags with a standard substrate in a full-factorial experimental design. We used model selection to compare three decomposition models and also to infer the importance of forest type, decomposition environment, mesofauna, and their interactions on the decomposition process. Rather than the frequently used simple and double-exponential models, the best model to describe our dataset was the exponential deceleration model, which assumed a single organic compartment with an exponential decrease of the decomposition rate. Decomposition was higher in the wet than in the seasonal forest, and the differences between forest types were stronger aboveground. Regarding litter decomposition environment, decomposition was predominantly higher below than aboveground, but the magnitude of this effect was higher in the seasonal than in wet forests. Mesofauna exclusion treatments had slower decomposition, except aboveground into the Semi-deciduous Forest, where the mesofauna presence did not affect decomposition. Furthermore, the effect of mesofauna was stronger in the wet forests and belowground. Overall, our results suggest that, in a regional scale, both decomposers activity and the positive effect of soil mesofauna in decomposition are constrained by abiotic factors, such as moisture conditions.

Superdiffusion in a non-Markovian random walk model with a Gaussian memory profile

Most superdiffusive Non-Markovian random walk models assume that correlations are maintained at all time scales, e. g., fractional Brownian motion, Levy walks, the Elephant walk and Alzheimer walk models. In the latter two models the random walker can always "remember" the initial times near t = 0. Assuming jump size distributions with finite variance, the question naturally arises: is superdiffusion possible if the walker is unable to recall the initial times? We give a conclusive answer to this general question, by studying a non-Markovian model in which the walker's memory of the past is weighted by a Gaussian centered at time t/2, at which time the walker had one half the present age, and with a standard deviation sigma t which grows linearly as the walker ages. For large widths we find that the model behaves similarly to the Elephant model, but for small widths this Gaussian memory profile model behaves like the Alzheimer walk model. We also report that the phenomenon of amnestically induced persistence, known to occur in the Alzheimer walk model, arises in the Gaussian memory profile model. We conclude that memory of the initial times is not a necessary condition for generating (log-periodic) superdiffusion. We show that the phenomenon of amnestically induced persistence extends to the case of a Gaussian memory profile.

A Bayesian destructive weighted Poisson cure rate model and an application to a cutaneous melanoma data

In this article, we propose a new Bayesian flexible cure rate survival model, which generalises the stochastic model of Klebanov et al. [Klebanov LB, Rachev ST and Yakovlev AY. A stochastic-model of radiation carcinogenesis - latent time distributions and their properties. Math Biosci 1993; 113: 51-75], and has much in common with the destructive model formulated by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)]. In our approach, the accumulated number of lesions or altered cells follows a compound weighted Poisson distribution. This model is more flexible than the promotion time cure model in terms of dispersion. Moreover, it possesses an interesting and realistic interpretation of the biological mechanism of the occurrence of the event of interest as it includes a destructive process of tumour cells after an initial treatment or the capacity of an individual exposed to irradiation to repair altered cells that results in cancer induction. In other words, what is recorded is only the damaged portion of the original number of altered cells not eliminated by the treatment or repaired by the repair system of an individual. Markov Chain Monte Carlo (MCMC) methods are then used to develop Bayesian inference for the proposed model. Also, some discussions on the model selection and an illustration with a cutaneous melanoma data set analysed by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)] are presented.