Endocrine disruptors and spontaneous premature labor: a case control study

<p>Abstract</p> <p>Background</p> <p>Premature labor is a poorly understood condition. Estrogen is thought to play a key role and therefore the labor process may be affected by endocrine disruptors. We sought to determine whether or not an environmental toxicant, DDE, or dietary derived endocrine disruptors, daidzein and genistein, are associated with spontaneous preterm labor.</p> <p>Methods</p> <p>Cases were defined as primiparous patients having a preterm delivery at or before 35 weeks following the spontaneous onset of labor. Controls were defined as primiparous women who delivered on the same day as the cases but at term gestation.</p> <p>Over approximately 1 year, 26 cases and 52 controls were recruited. Subjects agreed to have blood tests on day one postpartum for DDE and for the phytoestrogens genistein and daidzein.</p> <p>Results</p> <p>The mean concentration of DDE was similar in the case and control groups: 4.29 vs 4.32 ng/g lipid p = .85. In the case group, 13/26 had detectable levels of daidzein (range 0.20 – 1.56 ng/ml) compared to 25/52 controls (range 0.21 – 3.26 ng/ml). The mean concentration of daidzein was similar in cases compared to controls: 0.30 vs .34 ng/ml p = 0.91. Of the case group,14/26 had detectable levels of genistein (range 0.20 – 2.19 ng/ml) compared to 32/52 controls (range 0.21 – 2.55 ng/ml). The mean concentration of genistein was similar in cases compared to controls: 0.39 vs 0.31 ng/ml, p = 0.61.</p> <p>Conclusion</p> <p>The serum levels of DDE in this population were found to be low.</p> <p>There appears to be no relationship between serum concentrations of DDE, daidzein, and genistein and spontaneous preterm labor in our population. The inability to identify an effect may be related to the comparatively low concentrations of DDE in our population and the rapid and variable reduction of phytoestrogens from women in labor.</p

Identification of Mannose Interacting Residues Using Local Composition

BACKGROUND: Mannose binding proteins (MBPs) play a vital role in several biological functions such as defense mechanisms. These proteins bind to mannose on the surface of a wide range of pathogens and help in eliminating these pathogens from our body. Thus, it is important to identify mannose interacting residues (MIRs) in order to understand mechanism of recognition of pathogens by MBPs. RESULTS: This paper describes modules developed for predicting MIRs in a protein. Support vector machine (SVM) based models have been developed on 120 mannose binding protein chains, where no two chains have more than 25% sequence similarity. SVM models were developed on two types of datasets: 1) main dataset consists of 1029 mannose interacting and 1029 non-interacting residues, 2) realistic dataset consists of 1029 mannose interacting and 10320 non-interacting residues. In this study, firstly, we developed standard modules using binary and PSSM profile of patterns and got maximum MCC around 0.32. Secondly, we developed SVM modules using composition profile of patterns and achieved maximum MCC around 0.74 with accuracy 86.64% on main dataset. Thirdly, we developed a model on a realistic dataset and achieved maximum MCC of 0.62 with accuracy 93.08%. Based on this study, a standalone program and web server have been developed for predicting mannose interacting residues in proteins (http://www.imtech.res.in/raghava/premier/). CONCLUSIONS: Compositional analysis of mannose interacting and non-interacting residues shows that certain types of residues are preferred in mannose interaction. It was also observed that residues around mannose interacting residues have a preference for certain types of residues. Composition of patterns/peptide/segment has been used for predicting MIRs and achieved reasonable high accuracy. It is possible that this novel strategy may be effective to predict other types of interacting residues. This study will be useful in annotating the function of protein as well as in understanding the role of mannose in the immune system

Greenhouse gas emission associated with sugar production in southern Brazil

<p>Abstract</p> <p>Background</p> <p>Since sugarcane areas have increased rapidly in Brazil, the contribution of the sugarcane production, and, especially, of the sugarcane harvest system to the greenhouse gas emissions of the country is an issue of national concern. Here we analyze some data characterizing various activities of two sugarcane mills during the harvest period of 2006-2007 and quantify the carbon footprint of sugar production.</p> <p>Results</p> <p>According to our calculations, 241 kg of carbon dioxide equivalent were released to the atmosphere per a ton of sugar produced (2406 kg of carbon dioxide equivalent per a hectare of the cropped area, and 26.5 kg of carbon dioxide equivalent per a ton of sugarcane processed). The major part of the total emission (44%) resulted from residues burning; about 20% resulted from the use of synthetic fertilizers, and about 18% from fossil fuel combustion.</p> <p>Conclusions</p> <p>The results of this study suggest that the most important reduction in greenhouse gas emissions from sugarcane areas could be achieved by switching to a green harvest system, that is, to harvesting without burning.</p

Cost-effectiveness of opportunistic screening and minimal contact psychotherapy to prevent depression in primary care patients

Background: Depression causes a large burden of disease worldwide. Effective prevention has the potential to reduce that burden considerably. This study aimed to investigate the cost-effectiveness of minimal contact psychotherapy, based on Lewinsohn's 'Coping with depression' course, targeted at opportunistically screened individuals with sub-threshold depression. Methods and Results: Using a Markov model, future health effects and costs of an intervention scenario and a current practice scenario were estimated. The time horizon was five years. Incremental cost-effectiveness ratios were expressed in euro per Disability Adjusted Life Year (DALY) averted. Probabilistic sensitivity analysis was employed to study the effect of uncertainty in the model parameters. From the health care perspective the incremental cost-effectiveness ratio was € 1,400 per DALY, and from the societal perspective the intervention was cost-saving. Although the estimated incremental costs and effects were surrounded with large uncertainty, given a willingness to pay of € 20,000 per DALY, the probability that the intervention is cost-effective was around 80%. Conclusion: This modelling study showed that opportunistic screening in primary care for sub-threshold depression in combination with minimal contact psychotherapy may be cost-effective in the prevention of major depression