Search for CP violation in D0 and D+ decays

A high statistics sample of photoproduced charm particles from the FOCUS (E831) experiment at Fermilab has been used to search for CP violation in the Cabibbo suppressed decay modes D+ to K-K+pi+, D0 to K-K+ and D0 to pi-pi+. We have measured the following CP asymmetry parameters: A_CP(K-K+pi+) = +0.006 +/- 0.011 +/- 0.005, A_CP(K-K+) = -0.001 +/- 0.022 +/- 0.015 and A_CP(pi-pi+) = +0.048 +/- 0.039 +/- 0.025 where the first error is statistical and the second error is systematic. These asymmetries are consistent with zero with smaller errors than previous measurements.Comment: 12 pages, 4 figure

Characterizing genomic alterations in cancer by complementary functional associations.

Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of β-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes

Small but crucial : the novel small heat shock protein Hsp21 mediates stress adaptation and virulence in Candida albicans

Peer reviewedPublisher PD

A strategy to incorporate prior knowledge into correlation network cutoff selection

Correlation networks are frequently used to statistically extract biological interactions between omics markers. Network edge selection is typically based on the statistical significance of the correlation coefficients. This procedure, however, is not guaranteed to capture biological mechanisms. We here propose an alternative approach for network reconstruction: a cutoff selection algorithm that maximizes the overlap of the inferred network with available prior knowledge. We first evaluate the approach on IgG glycomics data, for which the biochemical pathway is known and well-characterized. Importantly, even in the case of incomplete or incorrect prior knowledge, the optimal network is close to the true optimum. We then demonstrate the generalizability of the approach with applications to untargeted metabolomics and transcriptomics data. For the transcriptomics case, we demonstrate that the optimized network is superior to statistical networks in systematically retrieving interactions that were not included in the biological reference used for optimization

The stellar halo of the Galaxy

Stellar halos may hold some of the best preserved fossils of the formation history of galaxies. They are a natural product of the merging processes that probably take place during the assembly of a galaxy, and hence may well be the most ubiquitous component of galaxies, independently of their Hubble type. This review focuses on our current understanding of the spatial structure, the kinematics and chemistry of halo stars in the Milky Way. In recent years, we have experienced a change in paradigm thanks to the discovery of large amounts of substructure, especially in the outer halo. I discuss the implications of the currently available observational constraints and fold them into several possible formation scenarios. Unraveling the formation of the Galactic halo will be possible in the near future through a combination of large wide field photometric and spectroscopic surveys, and especially in the era of Gaia.Comment: 46 pages, 16 figures. References updated and some minor changes. Full-resolution version available at http://www.astro.rug.nl/~ahelmi/stellar-halo-review.pd

Talk, trust and time: a longitudinal study evaluating knowledge translation and exchange processes for research on violence against women

<p>Abstract</p> <p>Background</p> <p>Violence against women (VAW) is a major public health problem. Translation of VAW research to policy and practice is an area that remains understudied, but provides the opportunity to examine knowledge translation and exchange (KTE) processes in a complex, multi-stakeholder context. In a series of studies including two randomized trials, the McMaster University VAW Research Program studied one key research gap: evidence about the effectiveness of screening women for exposure to intimate partner violence. This project developed and evaluated KTE strategies to share research findings with policymakers, health and community service providers, and women's advocates.</p> <p>Methods</p> <p>A longitudinal cross-sectional design, applying concurrent mixed data collection methods (surveys, interviews, and focus groups), was used to evaluate the utility of specific KTE strategies, including a series of workshops and a day-long Family Violence Knowledge Exchange Forum, on research sharing, uptake, and use.</p> <p>Results</p> <p>Participants valued the opportunity to meet with researchers, provide feedback on key messages, and make personal connections with other stakeholders. A number of factors specific to the knowledge itself, stakeholders' contexts, and the nature of the knowledge gap being addressed influenced the uptake, sharing, and use of the research. The types of knowledge use changed across time, and were specifically related to both the types of decisions being made, and to stage of decision making; most reported use was conceptual or symbolic, with few examples of instrumental use. Participants did report actively sharing the research findings with their own networks. Further examination of these second-order knowledge-sharing processes is required, including development of appropriate methods and measures for its assessment. Some participants reported that they would not use the research evidence in their decision making when it contradicted professional experiences, while others used it to support apparently contradictory positions. The online wiki-based 'community of interest' requested by participants was not used.</p> <p>Conclusions</p> <p>Mobilizing knowledge in the area of VAW practice and policy is complex and resource-intensive, and must acknowledge and respect the values of identified knowledge users, while balancing the objectivity of the research and researchers. This paper provides important lessons learned about these processes, including attending to the potential unintended consequences of knowledge sharing.</p

A unified data representation theory for network visualization, ordering and coarse-graining

Representation of large data sets became a key question of many scientific disciplines in the last decade. Several approaches for network visualization, data ordering and coarse-graining accomplished this goal. However, there was no underlying theoretical framework linking these problems. Here we show an elegant, information theoretic data representation approach as a unified solution of network visualization, data ordering and coarse-graining. The optimal representation is the hardest to distinguish from the original data matrix, measured by the relative entropy. The representation of network nodes as probability distributions provides an efficient visualization method and, in one dimension, an ordering of network nodes and edges. Coarse-grained representations of the input network enable both efficient data compression and hierarchical visualization to achieve high quality representations of larger data sets. Our unified data representation theory will help the analysis of extensive data sets, by revealing the large-scale structure of complex networks in a comprehensible form.Comment: 13 pages, 5 figure

Novel Crystalline SiO2 Nanoparticles via Annelids Bioprocessing of Agro-Industrial Wastes

The synthesis of nanoparticles silica oxide from rice husk, sugar cane bagasse and coffee husk, by employing vermicompost with annelids (Eisenia foetida) is reported. The product (humus) is calcinated and extracted to recover the crystalline nanoparticles. X-ray diffraction (XRD), transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HRTEM) and dynamic light scattering (DLS) show that the biotransformation allows creating specific crystalline phases, since equivalent particles synthesized without biotransformation are bigger and with different crystalline structure

The impact of social networks on knowledge transfer in long-term care facilities: Protocol for a study

<p>Abstract</p> <p>Background</p> <p>Social networks are theorized as significant influences in the innovation adoption and behavior change processes. Our understanding of how social networks operate within healthcare settings is limited. As a result, our ability to design optimal interventions that employ social networks as a method of fostering planned behavior change is also limited. Through this proposed project, we expect to contribute new knowledge about factors influencing uptake of knowledge translation interventions.</p> <p>Objectives</p> <p>Our specific aims include: To collect social network data among staff in two long-term care (LTC) facilities; to characterize social networks in these units; and to describe how social networks influence uptake and use of feedback reports.</p> <p>Methods and design</p> <p>In this prospective study, we will collect data on social networks in nursing units in two LTC facilities, and use social network analysis techniques to characterize and describe the networks. These data will be combined with data from a funded project to explore the impact of social networks on uptake and use of feedback reports. In this parent study, feedback reports using standardized resident assessment data are distributed on a monthly basis. Surveys are administered to assess report uptake. In the proposed project, we will collect data on social networks, analyzing the data using graphical and quantitative techniques. We will combine the social network data with survey data to assess the influence of social networks on uptake of feedback reports.</p> <p>Discussion</p> <p>This study will contribute to understanding mechanisms for knowledge sharing among staff on units to permit more efficient and effective intervention design. A growing number of studies in the social network literature suggest that social networks can be studied not only as influences on knowledge translation, but also as possible mechanisms for fostering knowledge translation. This study will contribute to building theory to design such interventions.</p