Large Differences in Publicly Visible Health Behaviours across Two Neighbourhoods of the Same City

Background: There are socioeconomic disparities in the likelihood of adopting unhealthy behaviours, and success at giving them up. This may be in part because people living in deprived areas are exposed to greater rates of unhealthy behaviour amongst those living around them. Conventional self-report surveys do not capture these differences in exposure, and more ethological methods are required in order to do so. Methodology/Principal Findings: We performed 12 hours of direct behavioural observation in the streets of two neighbourhoods of the same city which were similar in most regards, except that one was much more socioeconomically deprived than the other. There were large differences in the publicly visible health behaviours observed. In the deprived neighbourhood, we observed 266 more adults smoking (rate ratio 3.44), 53 more adults drinking alcohol (rate ratio not calculable), and 38 fewer adults running (rate ratio 0.23), than in the affluent neighbourhood. We used data from the Health Survey for England to calculate the differences we ought to expect to have seen given the individual-level socioeconomic characteristics of the residents. The observed disparities between the two neighbourhoods were considerably greater than this null model predicted. There were also different patterns of smoking in proximity to children in the two neighbourhoods. Conclusions/Significance: The differences in observed smoking, drinking alcohol, and physical activity between these tw

Discrimination of roast and ground coffee aroma

Background: Four analytical approaches were used to evaluate the aroma profile at key stages in roast and ground coffee brew preparation (concentration within the roast and ground coffee and respective coffee brew; concentration in the headspace of the roast and ground coffee and respective brew). Each method was evaluated by the analysis of 15 diverse key aroma compounds that were predefined by odour port analysis. Results: Different methods offered complimentary results for the discrimination of products; the concentration in the coffee brew was found to be the least discriminatory and concentration in the headspace above the roast and ground coffee was shown to be most discriminatory. Conclusions: All approaches should be taken into consideration when classifying roast and ground coffee especially for alignment to sensory perception and consumer insight data as all offer markedly different discrimination abilities due to the variation in volatility, hydrophobicity, air-water partition coefficient and other physicochemical parameters of the key aroma compounds present

Tracing the cosmic growth of supermassive black holes to z~3 with Herschel

We study a sample of Herschel selected galaxies within the Great Observatories Origins Deep Survey-South and the Cosmic Evolution Survey fields in the framework of the Photodetector Array Camera and Spectrometer (PACS) Evolutionary Probe project. Starting from the rich multiwavelength photometric data sets available in both fields, we perform a broad-band spectral energy distribution decomposition to disentangle the possible active galactic nucleus (AGN) contribution from that related to the host galaxy. We find that 37 per cent of the Herschel-selected sample shows signatures of nuclear activity at the 99 per cent confidence level. The probability of revealing AGN activity increases for bright (L 1−1000 > 10 11 L ? ) star-forming galaxies at z > 0.3, becoming about 80 per cent for the brightest (L 1−1000 > 10 12 L ? ) Infrared (IR) galaxies at z≥1. Finally, we reconstruct the AGN bolometric luminosity function and the supermassive black hole growth rate across cosmic time up to z ∼ 3 from a far-IR perspective. This work shows general agreement with most of the panchromatic estimates from the literature, with the global black hole growth peaking at z ∼ 2 and reproducing the observed local black hole mass density with consistent values of the radiative efficiency Erad (∼0.07)

Interaction of β-Sheet Folds with a Gold Surface

The adsorption of proteins on inorganic surfaces is of fundamental biological importance. Further, biomedical and nanotechnological applications increasingly use interfaces between inorganic material and polypeptides. Yet, the underlying adsorption mechanism of polypeptides on surfaces is not well understood and experimentally difficult to analyze. Therefore, we investigate here the interactions of polypeptides with a gold(111) surface using computational molecular dynamics (MD) simulations with a polarizable gold model in explicit water. Our focus in this paper is the investigation of the interaction of polypeptides with β-sheet folds. First, we concentrate on a β-sheet forming model peptide. Second, we investigate the interactions of two domains with high β-sheet content of the biologically important extracellular matrix protein fibronectin (FN). We find that adsorption occurs in a stepwise mechanism both for the model peptide and the protein. The positively charged amino acid Arg facilitates the initial contact formation between protein and gold surface. Our results suggest that an effective gold-binding surface patch is overall uncharged, but contains Arg for contact initiation. The polypeptides do not unfold on the gold surface within the simulation time. However, for the two FN domains, the relative domain-domain orientation changes. The observation of a very fast and strong adsorption indicates that in a biological matrix, no bare gold surfaces will be present. Hence, the bioactivity of gold surfaces (like bare gold nanoparticles) will critically depend on the history of particle administration and the proteins present during initial contact between gold and biological material. Further, gold particles may act as seeds for protein aggregation. Structural re-organization and protein aggregation are potentially of immunological importance

Identification of Functional Differences in Metabolic Networks Using Comparative Genomics and Constraint-Based Models

Genome-scale network reconstructions are useful tools for understanding cellular metabolism, and comparisons of such reconstructions can provide insight into metabolic differences between organisms. Recent efforts toward comparing genome-scale models have focused primarily on aligning metabolic networks at the reaction level and then looking at differences and similarities in reaction and gene content. However, these reaction comparison approaches are time-consuming and do not identify the effect network differences have on the functional states of the network. We have developed a bilevel mixed-integer programming approach, CONGA, to identify functional differences between metabolic networks by comparing network reconstructions aligned at the gene level. We first identify orthologous genes across two reconstructions and then use CONGA to identify conditions under which differences in gene content give rise to differences in metabolic capabilities. By seeking genes whose deletion in one or both models disproportionately changes flux through a selected reaction (e.g., growth or by-product secretion) in one model over another, we are able to identify structural metabolic network differences enabling unique metabolic capabilities. Using CONGA, we explore functional differences between two metabolic reconstructions of Escherichia coli and identify a set of reactions responsible for chemical production differences between the two models. We also use this approach to aid in the development of a genome-scale model of Synechococcus sp. PCC 7002. Finally, we propose potential antimicrobial targets in Mycobacterium tuberculosis and Staphylococcus aureus based on differences in their metabolic capabilities. Through these examples, we demonstrate that a gene-centric approach to comparing metabolic networks allows for a rapid comparison of metabolic models at a functional level. Using CONGA, we can identify differences in reaction and gene content which give rise to different functional predictions. Because CONGA provides a general framework, it can be applied to find functional differences across models and biological systems beyond those presented here

Euclid preparation: XXX. Performance assessment of the NISP red grism through spectroscopic simulations for the wide and deep surveys

This work focusses on the pilot run of a simulation campaign aimed at investigating the spectroscopic capabilities of the Euclid Near-Infrared Spectrometer and Photometer (NISP), in terms of continuum and emission line detection in the context of galaxy evolutionary studies. To this purpose, we constructed, emulated, and analysed the spectra of 4992 star-forming galaxies at 0:3 ≥ z ≥ 2:5 using the NISP pixel-level simulator. We built the spectral library starting from public multi-wavelength galaxy catalogues, with value-added information on spectral energy distribution (SED) fitting results, and stellar population templates from Bruzual & Charlot (2003, MNRAS, 344, 1000). Rest-frame optical and near-IR nebular emission lines were included using empirical and theoretical relations. Dust attenuation was treated using the Calzetti extinction law accounting for the differential attenuation in line-emitting regions with respect to the stellar continuum. The NISP simulator was configured including instrumental and astrophysical sources of noise such as the dark current, read-out noise, zodiacal background, and out-of-field stray light. In this preliminary study, we avoided contamination due to the overlap of the slitless spectra. For this purpose, we located the galaxies on a grid and simulated only the first order spectra.We inferred the 3.5δ NISP red grism spectroscopic detection limit of the continuum measured in the H band for star-forming galaxies with a median disk half-light radius of 0: 004 at magnitude H = 19:5 = 0:2ABmag for the Euclid Wide Survey and at H = 20:8 = 0:6ABmag for the Euclid Deep Survey. We found a very good agreement with the red grism emission line detection limit requirement for the Wide and Deep surveys. We characterised the effect of the galaxy shape on the detection capability of the red grism and highlighted the degradation of the quality of the extracted spectra as the disk size increased. In particular, we found that the extracted emission line signal-to-noise ratio (S/N) drops by 45% when the disk size ranges from 0: 0025 to 100. These trends lead to a correlation between the emission line S/N and the stellar mass of the galaxy and we demonstrate the effect in a stacking analysis unveiling emission lines otherwise too faint to detect

The Indian cobra reference genome and transcriptome enables comprehensive identification of venom toxins

Snakebite envenoming is a serious and neglected tropical disease that kills ~100,000 people annually. High-quality, genome-enabled comprehensive characterization of toxin genes will facilitate development of effective humanized recombinant antivenom. We report a de novo near-chromosomal genome assembly of Naja naja, the Indian cobra, a highly venomous, medically important snake. Our assembly has a scaffold N50 of 223.35 Mb, with 19 scaffolds containing 95% of the genome. Of the 23,248 predicted protein-coding genes, 12,346 venom-gland-expressed genes constitute the \u27venom-ome\u27 and this included 139 genes from 33 toxin families. Among the 139 toxin genes were 19 \u27venom-ome-specific toxins\u27 (VSTs) that showed venom-gland-specific expression, and these probably encode the minimal core venom effector proteins. Synthetic venom reconstituted through recombinant VST expression will aid in the rapid development of safe and effective synthetic antivenom. Additionally, our genome could serve as a reference for snake genomes, support evolutionary studies and enable venom-driven drug discovery