Agatha Sacramento Rodrigues

Does hierarchy stability influence testosterone and cortisol levels of bearded capuchin monkeys (Sapajus libidinosus) adult males? A comparison between two wild groups

Testosterone and cortisol are hormones expected to play a major role in competitive behaviours (i.e. aggression), and are related to rank and hierarchical stability. Through a non-invasive technique, we analyzed faecal testosterone (FTM(1)) and cortisol (FCM(2)) metabolites of dominant and subordinate males from two wild groups of bearded capuchin monkeys. One group had a stable dominance hierarchy while the other had an unstable hierarchy, with a marked conflict period related to a male take-over. In the unstable hierarchy group (1) the dominant male had higher FTM peaks than subordinates, and (2) basal FTM levels were higher than in the stable group. These findings are in accordance with the Challenge Hypothesis and rank-based predictions, and confirm that in Sapajus libidinosus hierarchy stability, social status, aggression rates and testosterone are closely related. Dominants of both groups had higher basal and peak FCM levels, suggesting that in S. libidinosus the dominant male has a higher allostatic load than subordinates, related to his role in protection against predators, intragroup appeasement, and control of food sources. Finally, we suggest that males of S. libidinosus are resistant to testosterone suppression by cortisol, because in the unstable group in spite of an increase in FCM there was also an increase in FTM during the conflict period. This article is part of a Special Issue entitled: Neotropical Behaviour.

The SURMetaGIT study: Design and rationale for a prospective pan-omics examination of the gastrointestinal response to Roux-en-Y gastric bypass surgery

Objective To describe the protocol of the SURgically induced Metabolic effects on the Human GastroIntestinal Tract (SURMetaGIT) study, a clinical pan-omics study exploring the gastrointestinal tract as a central organ driving remission of type 2 diabetes mellitus (T2DM) after Roux-en-Y gastric bypass (RYGB). The main points considered in the study’s design and challenges faced in its application are detailed. Methods This observational, longitudinal, prospective study involved collection of gastrointestinal biopsy specimens, faeces, urine, and blood from 25 obese women with T2DM who were candidates for RYGB (20 patients for omics assessment and 5 for omics validation). These collections were performed preoperatively and 3 and 24 months postoperatively. Gastrointestinal transcriptomics; faecal metagenomics and metabolomics; plasma proteomics, lipidomics, and metabolomics; and biochemical, nutritional, and metabolic data were assessed to identify their short- and long-term correlations with T2DM remission. Results Data were collected from 20 patients before and 3 months after RYGB. These patients have nearly completed the 2-year follow-up assessments. The five additional patients are currently being selected for omics data validation. Conclusion The multi-integrated pan-omics approach of the SURMetaGIT study enables integrated analysis of data that will contribute to the understanding of molecular mechanisms involved in T2DM remission after RYGB.

Reliability analysis in series systems: An empirical comparison between Bayesian and classical estimators

In Reliability Analysis, coherent systems represent a most important structure. In many situations systems are arranged in a series configuration, meaning that the systems failure is determined by the first component to fail. A problem of fundamental importance is to estimate the survival function parameters for each component, which allows the specification of adequate maintainance policies. However, reliability data for series systems are usually censored, in the sense that one only has information about the first component to fail. In this work, we focus on two components series systems. We discuss and compare, via numerical experiments on simulated datasets, the performances of three estimation methods: Bayesian, Frequetist maximum likelihood and nonparametric Kaplan-Meier estimators. The results of simulation study suggest that maximum likelihood and Bayesian estimatorss are roughly equivalent, while Kaplan-Meier underperforms the other two.

Sonographic Markers in the Prediction of Fetal Complex Gastroschisis

Objective: To investigate the ultrasound (US) markers predictive of complex gastroschisis (CG), mortality, and morbidity in fetuses with gastroschisis. Materials and Methods: This was a retrospective cohort study of 186 pregnancies with isolated fetal gastroschisis. Eight US markers were analyzed. The predictions and associations of US markers with CG, mortality, and morbidity were assessed. Combinations of US markers predictive of CG were investigated. Results: Extra-abdominal bowel dilatation (EABD), intra-abdominal bowel dilatation (IABD), and polyhydramnios were predictive of CG. EABD between 25 and 28 weeks had a sensitivity of 64%, a specificity of 89%, a positive predictive value (PPV) of 56.2%, and negative predictive value (NPV) of 91.8%. The predictions of IABD were sensitivity = 26.7%, specificity = 96.7%, PPV = 61.5%, and NPV = 86.8%. The odds ratios for CG in the presence of 1 and 2 US markers, compared with the absence of a US marker, were 18.3 (95% CI, 3.83-87.64) and 73.3 (95% CI, 6.14-876), respectively. Conclusion: US markers predictive of CG were established. The combination of these markers increases the probability of CG.

Spontaneous prematurity in fetuses with congenital diaphragmatic hernia: a retrospective cohort study about prenatal predictive factors

BackgroundTo evaluate possible predictive factors of spontaneous prematurity in fetuses with congenital diaphragmatic hernia (CDH).MethodsA retrospective cohort study was performed. Inclusion criteria were presence of CDH; absence of fetoscopy; absence of karyotype abnormality; maximum of one major malformation associated with diaphragmatic hernia; ultrasound monitoring at the Obstetrics Clinic of Clinicas Hospital at the University of São Paulo School of Medicine, from January 2001 to October 2014. The data were obtained through the electronic records and ultrasound system of our fetal medicine service. The following variables were analyzed: maternal age, primiparity, associated maternal diseases, smoking, previous spontaneous preterm birth, fetal malformation associated with hernia, polyhydramnios, fetal growth restriction, presence of intrathoracic liver, invasive procedures performed, side of hernia and observed-to- expected lung to head ratio (o/e LHR). On individual analysis, variables were assessed using the Chi-square test and the Mann-Whitney test. A multiple logistic regression model was applied to select variables independently influencing the prediction of preterm delivery. A ROC curve was constructed with the significant variable, identifying the values with best sensitivity and specificity to be suggested for use in clinical practice.ResultsEighty fetuses were evaluated, of which, 21 (26.25%) were premature. O/e LHR was the only factor associated with prematurity (p = 0.020). The ROC curve showed 93% sensitivity with 48.4% specificity for the cutoff of 40%.ConclusionO/e LHR was the only predictor of prematurity in this sample.

Frailty models power variance function with cure fraction and latent risk factors negative binomial

ABSTRACT In this article, we propose a flexible cure rate model, which is an extension of Cancho et al. (2011) model, by incorporating a power variance function (PVF) frailty term in latent risk. The model is more flexible in terms of dispersion and it also quantifies the unobservable heterogeneity. The parameter estimation is reached by maximum likelihood estimation procedure and Monte Carlo simulation studies are considered to evaluate the proposed model performance. The practical relevance of the model is illustrated in a real data set of preventing cancer recurrence.

Can we stratify the risk for insulin need in women diagnosed early with gestational diabetes by fasting blood glucose

Abstract Objective: The objective of this study is to evaluate risk factors and propose a model for the prediction of insulin requirement during the treatment of early-diagnosed gestational diabetes mellitus (GDM). Research design and methods: Retrospective cohort analysis of all pregnant women who were diagnosed with GDM by abnormal fasting blood glucose at the first prenatal visit. According to the requirement for insulin therapy to achieve good glycemic control (insulin or diet group), women were compared regarding clinical and laboratory variables. The performance of these variables in predicting insulin need for GDM treatment was identified by a logistic regression model, and a nomogram was created based on the model to facilitate clinical interpretation. Results: In total, 408 women were included for analysis. Among them, 135 (33%) needed insulin therapy. In the logistic regression model, maternal age, prepregnancy body mass index, fasting blood glucose (FBG) value, prior GDM, and family history of diabetes were significant independent variables for the prediction of insulin need. Conclusions: The need for insulin therapy in women with early diagnosis of GDM can be predicted by a logistic regression model, which can be converted to a clinically usable nomogram that could help to properly address follow-up strategies for GDM treatment in regions where health resources are limited.

Breastfeeding Twins: Factors Related to Weaning:

Background: Many factors may influence a woman’s decision to start and maintain breastfeeding. Research aim: This study aimed to investigate the factors associated with breastfeeding cessation in twin infants during the first 6 months after birth and to describe the main reasons for weaning cited by mothers of twins. Methods: This is a secondary data analysis of a prospective randomized trial conducted in Brazil. Data were obtained through longitudinal quantitative and qualitative self-reported interviews. One hundred twenty-eight women pregnant with twins and their 256 infants were followed for up to approximately 6 months, during which time breastfeeding data were obtained through face-to-face interviews at three different points after birth: 30 to 40 days (Time 1), 90 days (Time 2), and 180 days (Time 3). The association between weaning and the investigated factors was examined using survival analysis methodologies. Results: Nonexclusive breastfeeding (p = .004, Cox proportional hazards regression model), a lack of support during the lactation period (p = .001), difficulty breastfeeding (p = .003), a breastfeeding duration shorter than 12 months in a previous pregnancy (p = .001), and infants’ birth weight less than 2,300 g (p < .001) were the factors associated with breastfeeding cessation. The main reasons for weaning cited by mothers of twins were insufficient human milk supply, infants’ behavior, and returning to work. Conclusion: We have identified the factors associated with weaning in twin infants during the first 180 days of life. This knowledge can help improve strategies to increase breastfeeding rates in twins.

Defective models induced by gamma frailty term for survival data with cured fraction

ABSTRACT In this paper, we propose a defective model induced by a frailty term for modeling the proportion of cured. Unlike most of the cure rate models, defective models have advantage of modeling the cure rate without adding any extra parameter in model. The introduction of an unobserved heterogeneity among individuals has bring advantages for the estimated model. The influence of unobserved covariates is incorporated using a proportional hazard model. The frailty term assumed to follow a gamma distribution is introduced on the hazard rate to control the unobservable heterogeneity of the patients. We assume that the baseline distribution follows a Gompertz and inverse Gaussian defective distributions. Thus we propose and discuss two defective distributions: the defective gamma-Gompertz and gamma-inverse Gaussian regression models. Simulation studies are performed to verify the asymptotic properties of the maximum likelihood estimator. Lastly, in order to illustrate the proposed model, we present three applications in real data sets, in which one of them we are using for the first time, related to a study about breast cancer in the A.C.Camargo Cancer Center, São Paulo, Brazil.

An unfavorable intrauterine environment may determine renal functional capacity in adulthood: a meta-analysis

Since studies show that an unfavorable environment during intrauterine development predisposes individuals to several diseases in adulthood, our objective is to assess the relation between fetal growth restriction and chronic renal disease in adults. We searched four different electronic databases through November 2017: CENTRAL, EMBASE, LILACS and MEDLINE. We selected studies with longitudinal or transversal designs associating kidney function in adulthood with low birth weight. Two reviewers evaluated the inclusion criteria and the risk of bias and extracted data from the included papers. Thirteen studies were selected for the systematic review and meta-analysis. We observed increased risks of presenting end-stage renal disease (risk ratio 1.31, 95% confidence interval: 1.17, 1.47), a lower glomerular filtration rate (ml/min) (mean difference 7.14; 95% confidence interval: -12.12, -2.16), microalbuminuria (risk ratio 1.40; 95% confidence interval: 1.28, 1.52) and a small increase in the albumin/creatinine ratio (mean difference 0.46; 95% confidence interval: 0.03, 0.90) in the low birth weight patients, compared with control group. These findings suggest that low birth weight is associated with renal dysfunction in adults.