Understanding and Modelling the Effect of Dissolved Metals on Solvent Degradation in Post Combustion CO2 Capture Based on Pilot Plant Experience

© 2017 by the authors. Oxidative degradation is a serious concern for upscaling of amine-based carbon capture technology. Different kinetic models have been proposed based on laboratory experiments, however the kinetic parameters included are limited to those relevant for a lab-scale system and not a capture plant. Besides, most of the models fail to recognize the catalytic effect of metals. The objective of this work is to develop a representative kinetic model based on an apparent auto-catalytic reaction mechanism between solvent degradation, corrosion and ammonia emissions. Measurements from four different pilot plants: (i) EnBW's plant at Heilbronn, Germany (ii) TNO's plant at Maasvlakte, The Netherlands; (iii) CSIRO's plants at Loy Yang and Tarong, Australia and (iv) DONG Energy's plant at Esbjerg, Denmark are utilized to propose a degradation kinetic model for 30 wt % ethanolamine (MEA) as the capture solvent. The kinetic parameters of the model were regressed based on the pilot plant campaign at EnBW. The kinetic model was validated by comparing it with the measurements at the remaining pilot campaigns. The model predicted the trends of ammonia emissions and metal concentration within the same order of magnitude. This study provides a methodology to establish a quantitative approach for predicting the onset of unacceptable degradation levels which can be further used to devise counter-measure strategies such as reclaiming and metal removal

Methane inhibition by Asparagopsis taxiformis with rumen fluid collected from ventral and central location – a pilot study

publishedVersio

Membranes by the Numbers

Many of the most important processes in cells take place on and across membranes. With the rise of an impressive array of powerful quantitative methods for characterizing these membranes, it is an opportune time to reflect on the structure and function of membranes from the point of view of biological numeracy. To that end, in this article, I review the quantitative parameters that characterize the mechanical, electrical and transport properties of membranes and carry out a number of corresponding order of magnitude estimates that help us understand the values of those parameters.Comment: 27 pages, 12 figure

Biophysics across time and space

Understanding the behaviour of almost any biological object is a fundamentally multiscale problem — a challenge that biophysicists have been increasingly embracing, building on two centuries of biophysical studies at a variety of length scales

Nano Random Forests to mine protein complexes and their relationships in quantitative proteomics data

Ever-increasing numbers of quantitative proteomics data sets constitute an underexploited resource for investigating protein function. Multiprotein complexes often follow consistent trends in these experiments, which could provide insights about their biology. Yet, as more experiments are considered, a complex’s signature may become conditional and less identifiable. Previously we successfully distinguished the general proteomic signature of genuine chromosomal proteins from hitchhikers using the Random Forests (RF) machine learning algorithm. Here we test whether small protein complexes can define distinguishable signatures of their own, despite the assumption that machine learning needs large training sets. We show, with simulated and real proteomics data, that RF can detect small protein complexes and relationships between them. We identify several complexes in quantitative proteomics results of wild-type and knockout mitotic chromosomes. Other proteins covary strongly with these complexes, suggesting novel functional links for later study. Integrating the RF analysis for several complexes reveals known interdependences among kinetochore subunits and a novel dependence between the inner kinetochore and condensin. Ribosomal proteins, although identified, remained independent of kinetochore subcomplexes. Together these results show that this complex-oriented RF (NanoRF) approach can integrate proteomics data to uncover subtle protein relationships. Our NanoRF pipeline is available online

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

Lipid analogs reveal features critical for hemolysis and diminish granadaene mediated Group B Streptococcus infection

Although certain microbial lipids are toxins, the structural features important for cytotoxicity remain unknown. Increased functional understanding is essential for developing therapeutics against toxic microbial lipids. Group B Streptococci (GBS) are bacteria associated with preterm births, stillbirths, and severe infections in neonates and adults. GBS produce a pigmented, cytotoxic lipid, known as granadaene. Despite its importance to all manifestations of GBS disease, studies towards understanding granadaene’s toxic activity are hindered by its instability and insolubility in purified form. Here, we report the synthesis and screening of lipid derivatives inspired by granadaene, which reveal features central to toxin function, namely the polyene chain length. Furthermore, we show that vaccination with a non-toxic synthetic analog confers the production of antibodies that inhibit granadaene-mediated hemolysis ex vivo and diminish GBS infection in vivo. This work provides unique structural and functional insight into granadaene and a strategy to mitigate GBS infection, which will be relevant to other toxic lipids encoded by human pathogens.This work was supported by funding from the National Institutes of Health Grants R01AI112619, R01AI133976, R01AI100989, and R21AI125907 and seed funds from Seattle Childrens Research Institute to L.

Religious pro-sociality? Experimental evidence from a sample of 766 Spaniards

This study explores the relationship between several personal religion-related variables and social behaviour, using three paradigmatic economic games: the dictator (DG), ultimatum (UG), and trust (TG) games. A large carefully designed sample of the urban adult population in Granada (Spain) is employed (N = 766). From participants' decisions in these games we obtain measures of altruism, bargaining behaviour and sense of fairness/equality, trust, and positive reciprocity. Three dimensions of religiosity are examined: (i) religious denomination; (ii) intensity of religiosity, measured by active participation at church services; and (iii) conversion out into a different denomination than the one raised in. The major results are: (i) individuals with “no religion” made decisions closer to rational selfish behaviour in the DG and the UG compared to those who affiliate with a “standard” religious denomination; (ii) among Catholics, intensity of religiosity is the key variable that affects social behaviour insofar as religiously-active individuals are generally more pro-social than non-active ones; and (iii) the religion raised in seems to have no effect on pro-sociality, beyond the effect of the current measures of religiosity. Importantly, behaviour in the TG is not predicted by any of the religion-related variables we analyse. While the results partially support the notion of religious pro-sociality, on the other hand, they also highlight the importance of closely examining the multidimensional nature of both religiosity and pro-social behaviour