Bridging topological and functional information in protein interaction networks by short loops profiling

Protein-protein interaction networks (PPINs) have been employed to identify potential novel interconnections between proteins as well as crucial cellular functions. In this study we identify fundamental principles of PPIN topologies by analysing network motifs of short loops, which are small cyclic interactions of between 3 and 6 proteins. We compared 30 PPINs with corresponding randomised null models and examined the occurrence of common biological functions in loops extracted from a cross-validated high-confidence dataset of 622 human protein complexes. We demonstrate that loops are an intrinsic feature of PPINs and that specific cell functions are predominantly performed by loops of different lengths. Topologically, we find that loops are strongly related to the accuracy of PPINs and define a core of interactions with high resilience. The identification of this core and the analysis of loop composition are promising tools to assess PPIN quality and to uncover possible biases from experimental detection methods. More than 96% of loops share at least one biological function, with enrichment of cellular functions related to mRNA metabolic processing and the cell cycle. Our analyses suggest that these motifs can be used in the design of targeted experiments for functional phenotype detection.This research was supported by the Biotechnology and Biological Sciences Research Council (BB/H018409/1 to AP, ACCC and FF, and BB/J016284/1 to NSBT) and by the Leukaemia & Lymphoma Research (to NSBT and FF). SSC is funded by a Leukaemia & Lymphoma Research Gordon Piller PhD Studentship

Results from the European Union MAPEC_LIFE cohort study on air pollution and chromosomal damage in children: are public health policies sufficiently protective?

Background: Children are at high risk of suffering health consequences of air pollution and childhood exposure can increase the risk of developing chronic diseases in adulthood. This study, part of the MAPEC_LIFE project (LIFE12 ENV/IT/000614), aimed to investigate the associations between exposure to urban air pollutants and micronucleus (MN) frequency, as a biomarker of chromosomal damage, in buccal cells of children for supporting implementation and updating of environmental policy and legislation. Methods: This prospective epidemiological cohort study was carried out on 6- to 8-year-old children living in five Italian towns with different levels and features of air pollution. Exfoliated buccal cells of the children were sampled twice, in winter and spring, obtaining 2139 biological samples for genotoxicological investigation. Micronucleus (MN) frequency was investigated in buccal cells of children and its association with air pollution exposure was assessed applying multiple Poisson regression mixed models, including socio-demographic and lifestyle factors as confounders. We also dichotomize air pollutants\u2019 concentration according to the EU Ambient Air Quality Directives and WHO Air Quality Guidelines in all Poisson regression models to assess their risk predictive capacity. Results: Positive and statistically significant associations were found between MN frequency and PM10, PM2.5, benzene, SO2 and ozone. The increment of the risk of having MN in buccal cells for each \u3bcg/m3 increase of pollutant concentration was maximum for benzene (18.9%, 95% CIs 2.2\u201338.4%) and modest for the other pollutants (between 0.2 and 1.4%). An increased risk (between 17.9% and 59.8%) was found also for exposure to PM10, benzene and benzo(a)pyrene levels higher than the threshold limits. Conclusions: Some air pollutants are able to induce chromosomal damage in buccal cells of children even at concentrations below present EU/WHO limits. This type of biological effects may be indicative of the environmental pressure which populations are exposed to in urban areas

PINOT: an intuitive resource for integrating protein-protein interactions

The past decade has seen the rise of omics data, for the understanding of biological systems in health and disease. This wealth of data includes protein-protein interaction (PPI) derived from both low and high-throughput assays, which is curated into multiple databases that capture the extent of available information from the peer-reviewed literature. Although these curation efforts are extremely useful, reliably downloading and integrating PPI data from the variety of available repositories is challenging and time consuming. We here present a novel user-friendly web-resource called PINOT (Protein Interaction Network Online Tool; available at http://www.reading.ac.uk/bioinf/PINOT/PINOT_form.html) to optimise the collection and processing of PPI data from the IMEx consortium associated repositories (members and observers) and from WormBase for constructing, respectively, human and C. elegans PPI networks. Users submit a query containing a list of proteins of interest for which PINOT will mine PPIs. PPI data is downloaded, merged, quality checked, and confidence scored based on the number of distinct methods and publications in which each interaction has been reported. Examples of PINOT applications are provided to highlight the performance, the ease of use and the potential applications of this tool. PINOT is a tool that allows users to survey the literature, extracting PPI data for a list of proteins of interest. The comparison with analogous tools showed that PINOT was able to extract similar numbers of PPIs while incorporating a set of innovative features. PINOT processes both small and large queries, it downloads PPIs live through PSICQUIC and it applies quality control filters on the downloaded PPI annotations (i.e. removing the need of manual inspection by the user). PINOT provides the user with information on detection methods and publication history for each of the downloaded interaction data entry and provides results in a table format that can be easily further customised and/or directly uploaded in a network visualization software

Fast automated cell phenotype image classification

BACKGROUND: The genomic revolution has led to rapid growth in sequencing of genes and proteins, and attention is now turning to the function of the encoded proteins. In this respect, microscope imaging of a protein's sub-cellular localisation is proving invaluable, and recent advances in automated fluorescent microscopy allow protein localisations to be imaged in high throughput. Hence there is a need for large scale automated computational techniques to efficiently quantify, distinguish and classify sub-cellular images. While image statistics have proved highly successful in distinguishing localisation, commonly used measures suffer from being relatively slow to compute, and often require cells to be individually selected from experimental images, thus limiting both throughput and the range of potential applications. Here we introduce threshold adjacency statistics, the essence which is to threshold the image and to count the number of above threshold pixels with a given number of above threshold pixels adjacent. These novel measures are shown to distinguish and classify images of distinct sub-cellular localization with high speed and accuracy without image cropping. RESULTS: Threshold adjacency statistics are applied to classification of protein sub-cellular localization images. They are tested on two image sets (available for download), one for which fluorescently tagged proteins are endogenously expressed in 10 sub-cellular locations, and another for which proteins are transfected into 11 locations. For each image set, a support vector machine was trained and tested. Classification accuracies of 94.4% and 86.6% are obtained on the endogenous and transfected sets, respectively. Threshold adjacency statistics are found to provide comparable or higher accuracy than other commonly used statistics while being an order of magnitude faster to calculate. Further, threshold adjacency statistics in combination with Haralick measures give accuracies of 98.2% and 93.2% on the endogenous and transfected sets, respectively. CONCLUSION: Threshold adjacency statistics have the potential to greatly extend the scale and range of applications of image statistics in computational image analysis. They remove the need for cropping of individual cells from images, and are an order of magnitude faster to calculate than other commonly used statistics while providing comparable or better classification accuracy, both essential requirements for application to large-scale approaches

"I should live and finish it": A qualitative inquiry into Turkish women's menopause experience

<p>Abstract</p> <p>Background</p> <p>While bio-medically, menopause could be treated as an illness, from a psychosocial and cultural perspective it could be seen as a "natural" process without requiring medication unless severe symptoms are present.</p> <p>Our objective is to explore the perceptions of Turkish women regarding menopause and Hormone Therapy (HT) to provide health care workers with an insight into the needs and expectations of postmenopausal women.</p> <p>Methods</p> <p>A qualitative inquiry through semi-structured, in-depth interviews was used to explore the study questions. We used a purposive sampling and included an equal number of participants who complained about the climacteric symptoms and those who visited the outpatient department for a problem other than climacteric symptoms but when asked declared that they had been experiencing climacteric symptoms. The interview questions focused on two areas; 1) knowledge, experiences, attitudes and beliefs about menopause and; 2) menopause-related experiences and ways to cope with menopause and perception of HT.</p> <p>Results</p> <p>Most of the participants defined menopause as a natural transition process that one should go through. Cleanliness, maturity, comfort of not having a period and positive changes in health behaviour were the concepts positively attributed to menopause, whereas hot flushes, getting old and difficulties in relationships were the negatives. Osteoporosis was an important concern for most of the participants. To deal with the symptoms, the non-pharmacological options were mostly favoured.</p> <p>Conclusion</p> <p>To our knowledge, this is the first qualitative study which focuses on Turkish women's menopausal experiences. Menopause was thought to be a natural process which was characterised by positive and negative features. Understanding these features and their implications in these women's lives may assist healthcare workers in helping their clients with menopause.</p

Research Blogs and the Discussion of Scholarly Information

The research blog has become a popular mechanism for the quick discussion of scholarly information. However, unlike peer-reviewed journals, the characteristics of this form of scientific discourse are not well understood, for example in terms of the spread of blogger levels of education, gender and institutional affiliations. In this paper we fill this gap by analyzing a sample of blog posts discussing science via an aggregator called ResearchBlogging.org (RB). ResearchBlogging.org aggregates posts based on peer-reviewed research and allows bloggers to cite their sources in a scholarly manner. We studied the bloggers, blog posts and referenced journals of bloggers who posted at least 20 items. We found that RB bloggers show a preference for papers from high-impact journals and blog mostly about research in the life and behavioral sciences. The most frequently referenced journal sources in the sample were: Science, Nature, PNAS and PLoS One. Most of the bloggers in our sample had active Twitter accounts connected with their blogs, and at least 90% of these accounts connect to at least one other RB-related Twitter account. The average RB blogger in our sample is male, either a graduate student or has been awarded a PhD and blogs under his own name

Qualitative thematic analysis of consent forms used in cancer genome sequencing

<p>Abstract</p> <p>Background</p> <p>Large-scale whole genome sequencing (WGS) studies promise to revolutionize cancer research by identifying targets for therapy and by discovering molecular biomarkers to aid early diagnosis, to better determine prognosis and to improve treatment response prediction. Such projects raise a number of ethical, legal, and social (ELS) issues that should be considered. In this study, we set out to discover how these issues are being handled across different jurisdictions.</p> <p>Methods</p> <p>We examined informed consent (IC) forms from 30 cancer genome sequencing studies to assess (1) stated purpose of sample collection, (2) scope of consent requested, (3) data sharing protocols (4) privacy protection measures, (5) described risks of participation, (6) subject re-contacting, and (7) protocol for withdrawal.</p> <p>Results</p> <p>There is a high degree of similarity in how cancer researchers engaged in WGS are protecting participant privacy. We observed a strong trend towards both using samples for additional, unspecified research and sharing data with other investigators. IC forms were varied in terms of how they discussed re-contacting participants, returning results and facilitating participant withdrawal. Contrary to expectation, there were no consistent trends that emerged over the eight year period from which forms were collected.</p> <p>Conclusion</p> <p>Examining IC forms from WGS studies elucidates how investigators are handling ELS challenges posed by this research. This information is important for ensuring that while the public benefits of research are maximized, the rights of participants are also being appropriately respected.</p