Dynamic Changes in Protein Functional Linkage Networks Revealed by Integration with Gene Expression Data

Response of cells to changing environmental conditions is governed by the dynamics of intricate biomolecular interactions. It may be reasonable to assume, proteins being the dominant macromolecules that carry out routine cellular functions, that understanding the dynamics of protein∶protein interactions might yield useful insights into the cellular responses. The large-scale protein interaction data sets are, however, unable to capture the changes in the profile of protein∶protein interactions. In order to understand how these interactions change dynamically, we have constructed conditional protein linkages for Escherichia coli by integrating functional linkages and gene expression information. As a case study, we have chosen to analyze UV exposure in wild-type and SOS deficient E. coli at 20 minutes post irradiation. The conditional networks exhibit similar topological properties. Although the global topological properties of the networks are similar, many subtle local changes are observed, which are suggestive of the cellular response to the perturbations. Some such changes correspond to differences in the path lengths among the nodes of carbohydrate metabolism correlating with its loss in efficiency in the UV treated cells. Similarly, expression of hubs under unique conditions reflects the importance of these genes. Various centrality measures applied to the networks indicate increased importance for replication, repair, and other stress proteins for the cells under UV treatment, as anticipated. We thus propose a novel approach for studying an organism at the systems level by integrating genome-wide functional linkages and the gene expression data

Parents’ Disclosure of Their HIV Infection to Their Children in the Context of the Family

We interviewed 33 HIV-infected parents from the HIV Cost and Services Utilization Study (HCSUS), 27 of their minor children, 19 adult children, and 15 caregivers about the process of children learning that their parents were HIV positive. We summarize the retrospective descriptions of parents’ disclosure of their HIV status to their children, from the perspective of multiple family members. We analyzed transcripts of these interviews with systematic qualitative methods. Both parents and children reported unplanned disclosure experiences with positive and negative outcomes. Parents sometimes reported that disclosure was not as negative as they feared. However, within-household analysis showed disagreement between parents and children from the same household regarding disclosure outcomes. These findings suggest that disclosure should be addressed within a family context to facilitate communication and children’s coping. Parents should consider negative and positive outcomes, unplanned disclosure and children’s capacity to adapt after disclosure when deciding whether to disclose

Factors contributing to attrition behavior in diabetes self-management programs: A mixed method approach

<p>Abstract</p> <p>Background</p> <p>Diabetes self-management education is a critical component in diabetes care. Despite worldwide efforts to develop efficacious DSME programs, high attrition rates are often reported in clinical practice. The objective of this study was to examine factors that may contribute to attrition behavior in diabetes self-management programs.</p> <p>Methods</p> <p>We conducted telephone interviews with individuals who had Type 2 diabetes (n = 267) and attended a diabetes education centre. Multivariable logistic regression was performed to identify factors associated with attrition behavior. Forty-four percent of participants (n = 118) withdrew prematurely from the program and were asked an open-ended question regarding their discontinuation of services. We used content analysis to code and generate themes, which were then organized under the Behavioral Model of Health Service Utilization.</p> <p>Results</p> <p>Working full and part-time, being over 65 years of age, having a regular primary care physician or fewer diabetes symptoms were contributing factors to attrition behaviour in our multivariable logistic regression. The most common reasons given by participants for attrition from the program were conflict between their work schedules and the centre's hours of operation, patients' confidence in their own knowledge and ability when managing their diabetes, apathy towards diabetes education, distance to the centre, forgetfulness, regular physician consultation, low perceived seriousness of diabetes, and lack of familiarity with the centre and its services. There was considerable overlap between our quantitative and qualitative results.</p> <p>Conclusion</p> <p>Reducing attrition behaviour requires a range of strategies targeted towards delivering convenient and accessible services, familiarizing individuals with these services, increasing communication between centres and their patients, and creating better partnerships between centres and primary care physicians.</p

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research

SASA: a SimulAtor of Self-stabilizing Algorithms

International audienceWe present SASA, an open-source SimulAtor of Self-stabilizing Algorithms. Self-stabilization defines the ability of a distributed algorithm to recover after transient failures. SASA is implemented as a faithful representation of the atomic-state model. This model is the most commonly used in the self-stabilizing area to prove both the correct operation and complexity bounds of self-stabilizing algorithms. SASA encompasses all features necessary to debug, test, and analyze self-stabilizing algorithms. Algorithm's properties can be checked using formal test oracles. Asynchrony is modeled by programmable stochastic daemons playing the role of input sequence generators