Unsupervised Multi-Omic Data Fusion: the Neural Graph Learning Network

In recent years, due to the high availability of omic data, data-driven biology has greatly expanded. However, the analysis of different data sources is still an open challenge. A few multi-omics approaches have been proposed in the literature, none of which takes into consideration the intrinsic topology of each omic, though. In this work, an unsupervised learning method based on a deep neural network is proposed. Foreach omic, a separate network is trained, whose outputs are fused into a single graph; at this purpose, an innovative loss function has been designed to better represent the data cluster manifolds. The graph adjacency matrix is exploited to determine similarities among samples. With this approach, omics having a different number of features are merged into a unique representation. Quantitative and qualitative analyses show that the proposed method has comparable results to the state of the art. The method has great intrinsic flexibility as it can be customized according to the complexity of the tasks and it has a lot of room for future improvements compared to more fine-tuned methods, opening the way for future research

A physical activity intervention to improve the quality of life of patients with a stoma: a feasibility study

Background We hypothesise that a physical activity (PA) intervention will improve the quality of life (QoL) of people with a stoma. A feasibility study of the intervention and trial parameters is necessary to inform a future main trial. Methods Participants received a weekly PA consultation by telephone, video conferencing, or face-to-face for 12 weeks with a PA instructor who prescribed physical activities and supported participants by addressing stoma-related concerns and using behaviour change techniques. A feasibility study of the intervention and trial parameters was conducted in three UK sites using mixed methods. Results The number of eligible patients consenting to the study was 30 out of 174 (17%). Most participants were female (73%); 73% had an ileostomy and 27% a colostomy; mean time since diagnosis was 6 months. A total of 18 (64%) participants completed pre- (baseline) and post-intervention (follow-up) measures. Results show an improvement on all scales measuring QoL and disease-specific fatigue. The median PA consultation rate per participant was eight sessions. Participants reported completing 75% or more of the prescribed PA each week. Eight stoma-related themes were identified from qualitative interviews: fear of hernia, bending down, fatigue, pain, prolapse, surgical wounds, stoma appliance, and stigma. The intervention appeared to address these issues. Conclusion This feasibility study demonstrated that a novel manualised PA intervention for people with a stoma is safe, feasible, and acceptable, and shows promise for improving outcomes. However, difficulties with recruitment will need to be carefully considered to ensure the success of future studies in this area

The Sources of Inflammatory Mediators in the Lung after Silica Exposure

The expression of 10 genes implicated in regulation of the inflammatory processes in the lung was studied after exposure of alveolar macrophages (AMs) to silica in vitro or in vivo. Exposure of AMs to silica in vitro up-regulated the messenger RNA (mRNA) levels of three genes [interleukin-6 (IL-6), monocyte chemoattractant protein-1 (MCP-1), and macrophage inflammatory protein-2 (MIP-2)] without a concomitant increase in the protein levels. AMs isolated after intratracheal instillation of silica up-regulated mRNA levels of four additional genes [granulocyte/macrophage-colony stimulating factor (GM-CSF), IL-1β, IL-10, and inducible nitric oxide synthase]. IL-6, MCP-1, and MIP-2 protein levels were elevated in bronchoalveolar lavage fluid. Fibroblasts under basal culture conditions express much higher levels of IL-6 and GM-CSF compared with AMs. Coculture of AMs and alveolar type II cells, or coculture of AMs and lung fibroblasts, in contact cultures or Transwell chambers, revealed no synergistic effect. Therefore, such interaction does not explain the effects seen in vivo. Identification of the intercellular communication in vivo is still unresolved. However, fibroblasts appear to be an important source of inflammatory mediators in the lung

Random-phase approximation and its applications in computational chemistry and materials science

The random-phase approximation (RPA) as an approach for computing the electronic correlation energy is reviewed. After a brief account of its basic concept and historical development, the paper is devoted to the theoretical formulations of RPA, and its applications to realistic systems. With several illustrating applications, we discuss the implications of RPA for computational chemistry and materials science. The computational cost of RPA is also addressed which is critical for its widespread use in future applications. In addition, current correction schemes going beyond RPA and directions of further development will be discussed.Comment: 25 pages, 11 figures, published online in J. Mater. Sci. (2012

A randomised controlled trial to determine the effect on response of including a lottery incentive in health surveys [ISRCTN32203485]

BACKGROUND: Postal questionnaires are an economical and simple method of data collection for research purposes but are subject to non-response bias. Several studies have explored the effect of monetary and non-monetary incentives on response. Recent meta-analyses conclude that financial incentives are an effective way of increasing response rates. However, large surveys rarely have the resources to reward individual participants. Three previous papers report on the effectiveness of lottery incentives with contradictory results. This study aimed to determine the effect of including a lottery-style incentive on response rates to a postal health survey. METHODS: Randomised controlled trial. Setting: North and West Birmingham. 8,645 patients aged 18 or over randomly selected from registers of eight general practices (family physician practices). Intervention: Inclusion of a flyer and letter with a health questionnaire informing patients that returned questionnaires would be entered into a lottery-style draw for £100 of gift vouchers. Control: Health questionnaire accompanied only by standard letter of explanation. Main outcome measures: Response rate and completion rate to questionnaire. RESULTS: 5,209 individuals responded with identical rates in both groups (62.1%). Practice, patient age, sex and Townsend score (a postcode based deprivation measure) were identified as predictive of response, with higher response related to older age, being female and living in an area with a lower Townsend score (less deprived). CONCLUSION: This RCT, using a large community based sample, found that the offer of entry into a lottery style draw for £100 of High Street vouchers has no effect on response rates to a postal health questionnaire

Graphene: A sub-nanometer trans-electrode membrane

Isolated, atomically thin conducting membranes of graphite, called graphene, have recently been the subject of intense research with the hope that practical applications in fields ranging from electronics to energy science will emerge. Here, we show that when immersed in ionic solution, a layer of graphene takes on new electrochemical properties that make it a trans-electrode. The trans-electrode's properties are the consequence of the atomic scale proximity of its two opposing liquid-solid interfaces together with graphene's well known in-plane conductivity. We show that several trans-electrode properties are revealed by ionic conductivity measurements on a CVD grown graphene membrane that separates two aqueous ionic solutions. Despite this membrane being only one to two atomic layers thick, we find it is a remarkable ionic insulator with a very small stable conductivity that depends on the ion species in solution. Electrical measurements on graphene membranes in which a single nanopore has been drilled show that the membrane's effective insulating thickness is less than one nanometer. This small effective thickness makes graphene an ideal substrate for very high-resolution, high throughput nanopore based single molecule detectors. Sensors based on modulation of graphene's in-plane electronic conductivity in response to trans-electrode environments and voltage biases will provide new insights into atomic processes at the electrode surfaces.Comment: Submitted 12 April 2010 to Nature, where it is under revie

PhyloPattern: regular expressions to identify complex patterns in phylogenetic trees

<p>Abstract</p> <p>Background</p> <p>To effectively apply evolutionary concepts in genome-scale studies, large numbers of phylogenetic trees have to be automatically analysed, at a level approaching human expertise. Complex architectures must be recognized within the trees, so that associated information can be extracted.</p> <p>Results</p> <p>Here, we present a new software library, PhyloPattern, for automating tree manipulations and analysis. PhyloPattern includes three main modules, which address essential tasks in high-throughput phylogenetic tree analysis: node annotation, pattern matching, and tree comparison. PhyloPattern thus allows the programmer to focus on: i) the use of predefined or user defined annotation functions to perform immediate or deferred evaluation of node properties, ii) the search for user-defined patterns in large phylogenetic trees, iii) the pairwise comparison of trees by dynamically generating patterns from one tree and applying them to the other.</p> <p>Conclusion</p> <p>PhyloPattern greatly simplifies and accelerates the work of the computer scientist in the evolutionary biology field. The library has been used to automatically identify phylogenetic evidence for domain shuffling or gene loss events in the evolutionary histories of protein sequences. However any workflow that relies on phylogenetic tree analysis, could be automated with PhyloPattern.</p

Species Specificity in Major Urinary Proteins by Parallel Evolution

Species-specific chemosignals, pheromones, regulate social behaviors such as aggression, mating, pup-suckling, territory establishment, and dominance. The identity of these cues remains mostly undetermined and few mammalian pheromones have been identified. Genetically-encoded pheromones are expected to exhibit several different mechanisms for coding 1) diversity, to enable the signaling of multiple behaviors, 2) dynamic regulation, to indicate age and dominance, and 3) species-specificity. Recently, the major urinary proteins (Mups) have been shown to function themselves as genetically-encoded pheromones to regulate species-specific behavior. Mups are multiple highly related proteins expressed in combinatorial patterns that differ between individuals, gender, and age; which are sufficient to fulfill the first two criteria. We have now characterized and fully annotated the mouse Mup gene content in detail. This has enabled us to further analyze the extent of Mup coding diversity and determine their potential to encode species-specific cues