The influence of birthweight on arterial blood pressure of children

Background & aims.This study examined the relationship between birthweight and blood pressure in childhood. Methods.Prospective cohort study involving 472 Brazilian children ranging in age from 5 to 8 years. Birthweight, systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI), total cholesterol and fractions (LDL-c, HDL-c), and triglycerides were determined. Total cholesterol, LDL-c, HDL-c, and triglycerides were assessed by automated enzymatic methods. Blood pressure was measured with the HDI/Pulse Wave™ CR-2000 equipment. Multiple regression models were used to investigate the relationship between birthweight and SBP and DBP, controlling for the following variables: gender, age, BMI, total cholesterol, triglycerides, per capita income, and maternal education. Results.When adjusting for gender and BMI, we found a systolic blood pressure increase of 2.9 (95per cent CI = −5.33 to −0.56) mmHg per kilogram birthweight reduction. The unadjusted association was insignificant. Conclusion.Our data suggest that low birthweight is one of the factors contributing to blood pressure elevation at early ages. A way to prevent these diseases is by implementing public policies focused on good nutrition and adequate prenatal care for pregnant women

Women's satisfaction with childbirth's experience in different models of care: a descriptive study

Com o objetivo de comparar a satisfação das mulheres com a experiência do parto em três modelos assistenciais, foi realizada pesquisa descritiva, com abordagem quantitativa, em dois hospitais públicos de São Paulo, um promovendo o modelo "Típico" e o outro com um centro de parto intra-hospitalar (modelo "CPNIH") e um peri-hospitalar (modelo "CPNPH"). A amostra foi constituída por 90 puérperas, 30 de cada modelo. A comparação entre os resultados referentes à satisfação das mulheres com o atendimento prestado pelos profissionais de saúde, com a qualidade da assistência e os motivos de satisfação e insatisfação, com a indicação ou recomendação dos serviços recebidos, com a sensação de segurança no processo e com as sugestões de melhorias, mostrou que o modelo CPHPH foi o melhor avaliado, vindo em seguida o CPNIH e por último o Típico. Conclui-se que o modelo peri-hospitalar de assistência ao parto deveria receber maior apoio do SUS, por se constituir em serviço em que as mulheres se mostram satisfeitas com a atenção recebida

Gênero, saúde materna e o paradoxo perinatal

Nos últimos 20 anos, houve uma melhoria de praticamente todos os indicadores da saúde materna no Brasil, assim como grande ampliação do acesso aos serviços de saúde. Paradoxalmente, não há qualquer evidência de melhoria na mortalidade materna. Este texto tem como objetivo trazer elementos para a compreensão deste paradoxo, através do exame dos modelos típicos de assistência ao parto, no SUS e no setor privado. Analisaremos as propostas de mudança para uma assistência mais baseada em evidências sobre a segurança destes modelos, sua relação com os direitos das mulheres, e com os conflitos de interesse e resistências à mudança dos modelos. Examinamos os pressupostos de gênero que modulam a assistência e os vieses de gênero na pesquisa neste campo, expressos na superestimação dos benefícios da tecnologia, e na subestimação ou na negação dos desconfortos e efeitos adversos das intervenções. Crenças da cultura sexual não raro são tidas como explicações 'científicas' sobre o corpo, a parturição e a sexualidade, e se refletem na imposição de sofrimentos e riscos desnecessários, nas intervenções danosas à integridade genital, e na negação do direito a acompanhantes. Esta 'pessimização do parto' é instrumental para favorecer, por comparação, o modelo da cesárea de rotina. Por fim, discutimos como o uso da categoria gênero pode contribuir para promover direitos e mudanças institucionais, como no caso dos acompanhantes no parto

The full Bayesian significance test for mixture models: results in gene expression clustering

Gene clustering is a useful exploratory technique to group together genes with similar expression levels under distinct cell cycle phases or distinct conditions. It helps the biologist to identify potentially meaningful relationships between genes. In this study, we propose a clustering method based on multivariate normal mixture models, where the number of clusters is predicted via sequential hypothesis tests: at each step, the method considers a mixture model of m components (m = 2 in the first step) and tests if in fact it should be m - 1. If the hypothesis is rejected, m is increased and a new test is carried out. The method continues (increasing m) until the hypothesis is accepted. The theoretical core of the method is the full Bayesian significance test, an intuitive Bayesian approach, which needs no model complexity penalization nor positive probabilities for sharp hypotheses. Numerical experiments were based on a cDNA microarray dataset consisting of expression levels of 205 genes belonging to four functional categories, for 10 distinct strains of Saccharomyces cerevisiae. To analyze the method's sensitivity to data dimension, we performed principal components analysis on the original dataset and predicted the number of classes using 2 to 10 principal components. Compared to Mclust (model-based clustering), our method shows more consistent results.

Dynamical models for computer viruses propagation

Nowadays, digital computer systems and networks are the main engineering tools, being used in planning, design, operation, and control of all sizes of building, transportation, machinery, business, and life maintaining devices. Consequently, computer viruses became one of the most important sources of uncertainty, contributing to decrease the reliability of vital activities. A lot of antivirus programs have been developed, but they are limited to detecting and removing infections, based on previous knowledge of the virus code. In spite of having good adaptation capability, these programs work just as vaccines against diseases and are not able to prevent new infections based on the network state. Here, a trial on modeling computer viruses propagation dynamics relates it to other notable events occurring in the network permitting to establish preventive policies in the network management. Data from three different viruses are collected in the Internet and two different identification techniques, autoregressive and Fourier analyses, are applied showing that it is possible to forecast the dynamics of a new virus propagation by using the data collected from other viruses that formerly infected the network. Copyright (c) 2008 J. R. C. Piqueira and F. B. Cesar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Evaluation of Antiproliferative, Anti-Type 2 Diabetes, and Antihypertension Potentials of Ellagitannins from Strawberries (Fragaria x ananassa Duch.) Using In Vitro Models

Strawberries represent the main source of ellagic acid derivatives in the Brazilian diet, corresponding to more than 50% of all phenolic compounds found in the fruit. There is a particular interest in the determination of the ellagic acid content in fruits because of possible chemopreventive benefits. In the present study, the potential health benefits of purified ellagitannins from strawberries were evaluated in relation to the antiproliferative activity and in vitro inhibition of alpha-amylase, alpha-glucosidase, and angiotensin I-converting enzyme (ACE) relevant for potential management of hyperglycemia and hypertension. Therefore, a comparison among ellagic acid, purified ellagitannins, and a strawberry extract was done to evaluate the possible synergistic effects of phenolics. In relation to the antiproliferative activity, it was observed that ellagic acid had the highest percentage inhibition of cell proliferation. The strawberry extract had lower efficacy in inhibiting the cell proliferation, indicating that in the case of this fruit there is no synergism. Purified ellagitannins had high alpha-amylase and ACE inhibitory activities. However, these compounds had low alpha-glucosidase inhibitory activity. These results suggested that the ellagitannins and ellagic acid have good potential for the management of hyperglycemia and hypertension linked to type 2 diabetes. However, further studies with animal and human models are needed to advance the in vitro assay-based biochemical rationale from this study.

Evaluation of Antihyperglycemia and Antihypertension Potential of Native Peruvian Fruits Using In Vitro Models

Local food diversity and traditional crops are essential for cost-effective management of the global epidemic of type 2 diabetes and associated complications of hypertension. Water and 12% ethanol extracts of native Peruvian fruits such as Lucuma (Pouteria lucuma), Pacae (Inga feuille), Papayita arequipena (Carica pubescens), Capuli (Prunus capuli), Aguaymanto (Physalis peruviana), and Algarrobo (Prosopis pallida) were evaluated for total phenolics, antioxidant activity based on 2, 2-diphenyl-1-picrylhydrazyl radical scavenging assay, and functionality such as in vitro inhibition of alpha-amylase, alpha-glucosidase, and angiotensin I-converting enzyme (ACE) relevant for potential management of hyperglycemia and hypertension linked to type 2 diabetes. The total phenolic content ranged from 3.2 (Aguaymanto) to 11.4 (Lucuma fruit) mg/g of sample dry weight. A significant positive correlation was found between total phenolic content and antioxidant activity for the ethanolic extracts. No phenolic compound was detected in Lucuma (fruit and powder) and Pacae. Aqueous extracts from Lucuma and Algarrobo had the highest alpha-glucosidase inhibitory activities. Papayita arequipena and Algarrobo had significant ACE inhibitory activities reflecting antihypertensive potential. These in vitro results point to the excellent potential of Peruvian fruits for food-based strategies for complementing effective antidiabetes and antihypertension solutions based on further animal and clinical studies.

Antidiabetes and antihypertension potential of commonly consumed carbohydrate sweeteners using in vitro models

Commonly consumed carbohydrate sweeteners derived from sugar cane, palm, and corn (syrups) were investigated to determine their potential to inhibit key enzymes relevant to Type 2 diabetes and hypertension based on the total phenolic content and antioxidant activity using in vitro models. Among sugar cane derivatives, brown sugars showed higher antidiabetes potential than white sugars; nevertheless, no angiotensin I-converting enzyme (ACE) inhibition was detected in both sugar classes. Brown sugar from Peru and Mauritius (dark muscovado) had the highest total phenolic content and 1,1-diphenyl-2-picrylhydrazyl radical scavenging activity, which correlated with a moderate inhibition of yeast alpha-glucosidase without showing a significant effect on porcine pancreatic alpha-amylase activity. In addition, chlorogenic acid quantified by high-performance liquid chromatography was detected in these sugars (128 +/- 6 and 144 +/- 2 mu g/g of sample weight, respectively). Date sugar exhibited high alpha-glucosidase, alpha-amylase, and ACE inhibitory activities that correlated with high total phenolic content and antioxidant activity. Neither phenolic compounds or antioxidant activity was detected in corn syrups, indicating that nonphenolic factors may be involved in their significant ability to inhibit alpha-glucosidase, alpha-amylase, and ACE. This study provides a strong biochemical rationale for further in vivo studies and useful information to make better dietary sweetener choices for Type 2 diabetes and hypertension management.

Data collapse, scaling functions, and analytical solutions of generalized growth models

We consider a nontrivial one-species population dynamics model with finite and infinite carrying capacities. Time-dependent intrinsic and extrinsic growth rates are considered in these models. Through the model per capita growth rate we obtain a heuristic general procedure to generate scaling functions to collapse data into a simple linear behavior even if an extrinsic growth rate is included. With this data collapse, all the models studied become independent from the parameters and initial condition. Analytical solutions are found when time-dependent coefficients are considered. These solutions allow us to perceive nontrivial transitions between species extinction and survival and to calculate the transition's critical exponents. Considering an extrinsic growth rate as a cancer treatment, we show that the relevant quantity depends not only on the intensity of the treatment, but also on when the cancerous cell growth is maximum.

Differential expression of microRNAs in mouse pain models

Background: MicroRNAs (miRNAs) are short non-coding RNAs that inhibit translation of target genes by binding to their mRNAs. The expression of numerous brain-specific miRNAs with a high degree of temporal and spatial specificity suggests that miRNAs play an important role in gene regulation in health and disease. Here we investigate the time course gene expression profile of miR-1, -16, and -206 in mouse dorsal root ganglion (DRG), and spinal cord dorsal horn under inflammatory and neuropathic pain conditions as well as following acute noxious stimulation. Results: Quantitative real-time polymerase chain reaction analyses showed that the mature form of miR-1, -16 and -206, is expressed in DRG and the dorsal horn of the spinal cord. Moreover, CFA-induced inflammation significantly reduced miRs-1 and -16 expression in DRG whereas miR-206 was downregulated in a time dependent manner. Conversely, in the spinal dorsal horn all three miRNAs monitored were upregulated. After sciatic nerve partial ligation, miR-1 and -206 were downregulated in DRG with no change in the spinal dorsal horn. On the other hand, axotomy increases the relative expression of miR-1, -16, and 206 in a time-dependent fashion while in the dorsal horn there was a significant downregulation of miR-1. Acute noxious stimulation with capsaicin also increased the expression of miR-1 and -16 in DRG cells but, on the other hand, in the spinal dorsal horn only a high dose of capsaicin was able to downregulate miR-206 expression. Conclusions: Our results indicate that miRNAs may participate in the regulatory mechanisms of genes associated with the pathophysiology of chronic pain as well as the nociceptive processing following acute noxious stimulation. We found substantial evidence that miRNAs are differentially regulated in DRG and the dorsal horn of the spinal cord under different pain states. Therefore, miRNA expression in the nociceptive system shows not only temporal and spatial specificity but is also stimulus-dependent.

Additive genetic relationship of longevity with fertility and production traits in Nellore cattle based on bivariate models

Survival or longevity is an economically important trait in beef cattle. The main inconvenience for its inclusion in selection criteria is delayed recording of phenotypic data and the high computational demand for including survival in proportional hazard models. Thus, identification of a longevity-correlated trait that could be recorded early in life would be very useful for selection purposes. We estimated the genetic relationship of survival with productive and reproductive traits in Nellore cattle, including weaning weight (WW), post-weaning growth (PWG), muscularity (MUSC), scrotal circumference at 18 months (SC18), and heifer pregnancy (HP). Survival was measured in discrete time intervals and modeled through a sequential threshold model. Five independent bivariate Bayesian analyses were performed, accounting for cow survival and the five productive and reproductive traits. Posterior mean estimates for heritability (standard deviation in parentheses) were 0.55 (0.01) for WW, 0.25 (0.01) for PWG, 0.23 (0.01) for MUSC, and 0.48 (0.01) for SC18. The posterior mean estimates (95% confidence interval in parentheses) for the genetic correlation with survival were 0.16 (0.13-0.19), 0.30 (0.25-0.34), 0.31 (0.25-0.36), 0.07 (0.02-0.12), and 0.82 (0.78-0.86) for WW, PWG, MUSC, SC18, and HP, respectively. Based on the high genetic correlation and heritability (0.54) posterior mean estimates for HP, the expected progeny difference for HP can be used to select bulls for longevity, as well as for post-weaning gain and muscle score.

Comparison of different models to estimate genetic parameters for carcass traits in a commercial broiler line

The effect of genetic and non-genetic factors for carcass, breast meat and leg weights, and yields of a commercial broiler line were investigated using the restricted maximum likelihood method, considering four different animal models, including or excluding maternal genetic effect with covariance between direct and maternal genetic effects, and maternal permanent environmental effect. The likelihood ratio test was used to determine the most adequate model for each trait. For carcass, breast, and leg weight, and for carcass and breast yield, maternal genetic and permanent environmental effects as well as the covariance between direct and maternal genetic effects were significant. The estimates of direct and maternal heritability were 0.17 and 0.04 for carcass weight, 0.26 and 0.06 for breast weight, 0.22 and 0.02 for leg weight, 0.32 and 0.02 for carcass yield, and 0.52 and 0.04 for breast yield, respectively. For leg yield, maternal permanent environmental effect was important, in addition to direct genetic effects. For that trait, direct heritability and maternal permanent environmental variance as a proportion of the phenotypic variance were 0.43 and 0.02, respectively. The results indicate that ignoring maternal effects in the models, even though they were of small magnitude (0.02 to 0.06), tended to overestimate direct genetic variance and heritability for all traits.

Newtonian perturbations on models with matter creation

Creation of cold dark matter (CCDM) can macroscopically be described by a negative pressure, and, therefore, the mechanism is capable to accelerate the Universe, without the need of an additional dark energy component. In this framework, we discuss the evolution of perturbations by considering a Neo-Newtonian approach where, unlike in the standard Newtonian cosmology, the fluid pressure is taken into account even in the homogeneous and isotropic background equations (Lima, Zanchin, and Brandenberger, MNRAS 291, L1, 1997). The evolution of the density contrast is calculated in the linear approximation and compared to the one predicted by the Lambda CDM model. The difference between the CCDM and Lambda CDM predictions at the perturbative level is quantified by using three different statistical methods, namely: a simple chi(2)-analysis in the relevant space parameter, a Bayesian statistical inference, and, finally, a Kolmogorov-Smirnov test. We find that under certain circumstances, the CCDM scenario analyzed here predicts an overall dynamics (including Hubble flow and matter fluctuation field) which fully recovers that of the traditional cosmic concordance model. Our basic conclusion is that such a reduction of the dark sector provides a viable alternative description to the accelerating Lambda CDM cosmology.

Equation of state for the magnetic-color-flavor-locked phase and its implications for compact star models

Using the solutions of the gap equations of the magnetic-color-flavor-locked (MCFL) phase of paired quark matter in a magnetic field, and taking into consideration the separation between the longitudinal and transverse pressures due to the field-induced breaking of the spatial rotational symmetry, the equation of state of the MCFL phase is self-consistently determined. This result is then used to investigate the possibility of absolute stability, which turns out to require a field-dependent ""bag constant"" to hold. That is, only if the bag constant varies with the magnetic field, there exists a window in the magnetic field vs bag constant plane for absolute stability of strange matter. Implications for stellar models of magnetized (self-bound) strange stars and hybrid (MCFL core) stars are calculated and discussed.

Confronting dark energy models using galaxy cluster number counts

The mass function of cluster-size halos and their redshift distribution are computed for 12 distinct accelerating cosmological scenarios and confronted to the predictions of the conventional flat Lambda CDM model. The comparison with Lambda CDM is performed by a two-step process. First, we determine the free parameters of all models through a joint analysis involving the latest cosmological data, using supernovae type Ia, the cosmic microwave background shift parameter, and baryon acoustic oscillations. Apart from a braneworld inspired cosmology, it is found that the derived Hubble relation of the remaining models reproduces the Lambda CDM results approximately with the same degree of statistical confidence. Second, in order to attempt to distinguish the different dark energy models from the expectations of Lambda CDM, we analyze the predicted cluster-size halo redshift distribution on the basis of two future cluster surveys: (i) an X-ray survey based on the eROSITA satellite, and (ii) a Sunayev-Zeldovich survey based on the South Pole Telescope. As a result, we find that the predictions of 8 out of 12 dark energy models can be clearly distinguished from the Lambda CDM cosmology, while the predictions of 4 models are statistically equivalent to those of the Lambda CDM model, as far as the expected cluster mass function and redshift distribution are concerned. The present analysis suggests that such a technique appears to be very competitive to independent tests probing the late time evolution of the Universe and the associated dark energy effects.