Antioxidant activities of sulfated polysaccharides from brown and red seaweeds

The in vitro antioxidant activities of the following six sulfated polysaccharides were investigated: iota, kappa and lambda carrageenans, which are widely used in the food industry, fucoidan (homofucan) from the edible seaweed Fucus vesiculosus and fucans (heterofucans) F0.5 and F1.1 from the seaweed Padina gymnospora. With respect to the inhibition of superoxide radical formation, fucoidan had an IC50 (the half maximal inhibitory concentration) of 0.058 mg·mL−1, while the IC50 for the kappa, iota and lambda carrageenans were 0.112, 0.332 and 0.046 mg·mL−1, respectively. All of the samples had an inhibitory effect on the formation of hydroxyl radicals. The results of peroxidation tests showed that fucoidan had an IC50 of 1.250 mg·mL−1 and that the kappa, iota and lambda carrageenans had an IC50 of 2.753 and 2.338 and 0.323 mg·mL−1, respectively. Fucan fractions showed low antioxidant activity relative to fucoidan. These results clearly indicate the beneficial effect of algal polysaccharides as antioxidants

Integrated Assessment of Genomic Correlates of Protein Evolutionary Rate

Rates of evolution differ widely among proteins, but the causes and consequences of such differences remain under debate. With the advent of high-throughput functional genomics, it is now possible to rigorously assess the genomic correlates of protein evolutionary rate. However, dissecting the correlations among evolutionary rate and these genomic features remains a major challenge. Here, we use an integrated probabilistic modeling approach to study genomic correlates of protein evolutionary rate in Saccharomyces cerevisiae. We measure and rank degrees of association between (i) an approximate measure of protein evolutionary rate with high genome coverage, and (ii) a diverse list of protein properties (sequence, structural, functional, network, and phenotypic). We observe, among many statistically significant correlations, that slowly evolving proteins tend to be regulated by more transcription factors, deficient in predicted structural disorder, involved in characteristic biological functions (such as translation), biased in amino acid composition, and are generally more abundant, more essential, and enriched for interaction partners. Many of these results are in agreement with recent studies. In addition, we assess information contribution of different subsets of these protein properties in the task of predicting slowly evolving proteins. We employ a logistic regression model on binned data that is able to account for intercorrelation, non-linearity, and heterogeneity within features. Our model considers features both individually and in natural ensembles (“meta-features”) in order to assess joint information contribution and degree of contribution independence. Meta-features based on protein abundance and amino acid composition make strong, partially independent contributions to the task of predicting slowly evolving proteins; other meta-features make additional minor contributions. The combination of all meta-features yields predictions comparable to those based on paired species comparisons, and approaching the predictive limit of optimal lineage-insensitive features. Our integrated assessment framework can be readily extended to other correlational analyses at the genome scale

A review of exposure assessment methods for epidemiological studies of health effects related to industrially contaminated sites

BACKGROUND: this paper is based upon work from COST Action ICSHNet. Health risks related to living close to industrially contaminated sites (ICSs) are a public concern. Toxicology-based risk assessment of single contaminants is the main approach to assess health risks, but epidemiological studies which investigate the relationships between exposure and health directly in the affected population have contributed important evidence. Limitations in exposure assessment have substantially contributed to uncertainty about associations found in epidemiological studies. OBJECTIVES: to examine exposure assessment methods that have been used in epidemiological studies on ICSs and to provide recommendations for improved exposure assessment in epidemiological studies by comparing exposure assessment methods in epidemiological studies and risk assessments. METHODS: after defining the multi-media framework of exposure related to ICSs, we discussed selected multi-media models applied in Europe. We provided an overview of exposure assessment in 54 epidemiological studies from a systematic review of hazardous waste sites; a systematic review of 41 epidemiological studies on incinerators and 52 additional studies on ICSs and health identified for this review. RESULTS: we identified 10 multi-media models used in Europe primarily for risk assessment. Recent models incorporated estimation of internal biomarker levels. Predictions of the models differ particularly for the routes ‘indoor air inhalation’ and ‘vegetable consumption’. Virtually all of the 54 hazardous waste studies used proximity indicators of exposure, based on municipality or zip code of residence (28 studies) or distance to a contaminated site (25 studies). One study used human biomonitoring. In virtually all epidemiological studies, actual land use was ignored. In the 52 additional studies on contaminated sites, proximity indicators were applied in 39 studies, air pollution dispersion modelling in 6 studies, and human biomonitoring in 9 studies. Exposure assessment in epidemiological studies on incinerators included indicators (presence of source in municipality and distance to the incinerator) and air dispersion modelling. Environmental multi-media modelling methods were not applied in any of the three groups of studies. CONCLUSIONS: recommendations for refined exposure assessment in epidemiological studies included the use of more sophisticated exposure metrics instead of simple proximity indicators where feasible, as distance from a source results in misclassification of exposure as it ignores key determinants of environmental fate and transport, source characteristics, land use, and human consumption behaviour. More validation studies using personal exposure or human biomonitoring are needed to assess misclassification of exposure. Exposure assessment should take more advantage of the detailed multi-media exposure assessment procedures developed for risk assessment. The use of indicators can be substantially improved by linking definition of zones of exposure to existing knowledge of extent of dispersion. Studies should incorporate more often land use and individual behaviour

Regulatory T Cells Phenotype in Different Clinical Forms of Chagas' Disease

CD25High CD4+ regulatory T cells (Treg cells) have been described as key players in immune regulation, preventing infection-induced immune pathology and limiting collateral tissue damage caused by vigorous anti-parasite immune response. In this review, we summarize data obtained by the investigation of Treg cells in different clinical forms of Chagas' disease. Ex vivo immunophenotyping of whole blood, as well as after stimulation with Trypanosoma cruzi antigens, demonstrated that individuals in the indeterminate (IND) clinical form of the disease have a higher frequency of Treg cells, suggesting that an expansion of those cells could be beneficial, possibly by limiting strong cytotoxic activity and tissue damage. Additional analysis demonstrated an activated status of Treg cells based on low expression of CD62L and high expression of CD40L, CD69, and CD54 by cells from all chagasic patients after T. cruzi antigenic stimulation. Moreover, there was an increase in the frequency of the population of Foxp3+ CD25HighCD4+ cells that was also IL-10+ in the IND group, whereas in the cardiac (CARD) group, there was an increase in the percentage of Foxp3+ CD25High CD4+ cells that expressed CTLA-4. These data suggest that IL-10 produced by Treg cells is effective in controlling disease development in IND patients. However, in CARD patients, the same regulatory mechanism, mediated by IL-10 and CTLA-4 expression is unlikely to be sufficient to control the progression of the disease. These data suggest that Treg cells may play an important role in controlling the immune response in Chagas' disease and the balance between regulatory and effector T cells may be important for the progression and development of the disease. Additional detailed analysis of the mechanisms on how these cells are activated and exert their function will certainly give insights for the rational design of procedure to achieve the appropriate balance between protection and pathology during parasite infections

Fetus-derived DLK1 is required for maternal metabolic adaptations to pregnancy and is associated with fetal growth restriction.

Pregnancy is a state of high metabolic demand. Fasting diverts metabolism to fatty acid oxidation, and the fasted response occurs much more rapidly in pregnant women than in non-pregnant women. The product of the imprinted DLK1 gene (delta-like homolog 1) is an endocrine signaling molecule that reaches a high concentration in the maternal circulation during late pregnancy. By using mouse models with deleted Dlk1, we show that the fetus is the source of maternal circulating DLK1. In the absence of fetally derived DLK1, the maternal fasting response is impaired. Furthermore, we found that maternal circulating DLK1 levels predict embryonic mass in mice and can differentiate healthy small-for-gestational-age (SGA) infants from pathologically small infants in a human cohort. Therefore, measurement of DLK1 concentration in maternal blood may be a valuable method for diagnosing human disorders associated with impaired DLK1 expression and to predict poor intrauterine growth and complications of pregnancy.M.A.M.C. was supported by a PhD studentship from the Cambridge Centre for Trophoblast Research. Research was supported by grants from the MRC (MR/J001597/1 and MR/L002345/1), the Medical College of Saint Bartholomew's Hospital Trust, a Wellcome Trust Investigator Award, EpigeneSys (FP7 Health-257082), EpiHealth (FP7 Health-278414), a Herchel Smith Fellowship (N.T.) and NIH grant RO1 DK89989. The contents are the authors' sole responsibility and do not necessarily represent official NIH views. We thank G. Burton for invaluable support, and M. Constância and I. Sandovici (University of Cambridge) for the Meox2-cre mice. We are extremely grateful to all of the participants in the Pregnancy Outcome Prediction study. This work was supported by the NIHR Cambridge Comprehensive Biomedical Research Centre (Women's Health theme) and project grants from the MRC (G1100221) and Sands (Stillbirth and Neonatal Death Charity). The study was also supported by GE Healthcare (donation of two Voluson i ultrasound systems for this study) and by the NIHR Cambridge Clinical Research Facility, where all research visits took place.This is the author accepted manuscript. The final version is available from Nature Publishing Group via https://doi.org/10.1038/ng.369

Enzymes Are Enriched in Bacterial Essential Genes

Essential genes, those indispensable for the survival of an organism, play a key role in the emerging field, synthetic biology. Characterization of functions encoded by essential genes not only has important practical implications, such as in identifying antibiotic drug targets, but can also enhance our understanding of basic biology, such as functions needed to support cellular life. Enzymes are critical for almost all cellular activities. However, essential genes have not been systematically examined from the aspect of enzymes and the chemical reactions that they catalyze. Here, by comprehensively analyzing essential genes in 14 bacterial genomes in which large-scale gene essentiality screens have been performed, we found that enzymes are enriched in essential genes. Essential enzymes have overrepresented ligases (especially those forming carbon-oxygen bonds and carbon-nitrogen bonds), nucleotidyltransferases and phosphotransferases, while have underrepresented oxidoreductases. Furthermore, essential enzymes tend to associate with more gene ontology domains. These results, from the aspect of chemical reactions, provide further insights into the understanding of functions needed to support natural cellular life, as well as synthetic cells, and provide additional parameters that can be integrated into gene essentiality prediction algorithms