Using Graph Components Derived from an Associative Concept Dictionary to Predict fMRI Neural Activation Patterns that Represent the Meaning of Nouns

In this study, we introduce an original distance definition for graphs, called the Markov-inverse-F measure (MiF). This measure enables the integration of classical graph theory indices with new knowledge pertaining to structural feature extraction from semantic networks. MiF improves the conventional Jaccard and/or Simpson indices, and reconciles both the geodesic information (random walk) and co-occurrence adjustment (degree balance and distribution). We measure the effectiveness of graph-based coefficients through the application of linguistic graph information for a neural activity recorded during conceptual processing in the human brain. Specifically, the MiF distance is computed between each of the nouns used in a previous neural experiment and each of the in-between words in a subgraph derived from the Edinburgh Word Association Thesaurus of English. From the MiF-based information matrix, a machine learning model can accurately obtain a scalar parameter that specifies the degree to which each voxel in (the MRI image of) the brain is activated by each word or each principal component of the intermediate semantic features. Furthermore, correlating the voxel information with the MiF-based principal components, a new computational neurolinguistics model with a network connectivity paradigm is created. This allows two dimensions of context space to be incorporated with both semantic and neural distributional representations.

Introducing the CTA concept

The Cherenkov Telescope Array (CTA) is a new observatory for very high-energy (VHE) gamma rays. CTA has ambitions science goals, for which it is necessary to achieve full-sky coverage, to improve the sensitivity by about an order of magnitude, to span about four decades of energy, from a few tens of GeV to above 100 TeV with enhanced angular and energy resolutions over existing VHE gamma-ray observatories. An international collaboration has formed with more than 1000 members from 27 countries in Europe, Asia, Africa and North and South America. In 2010 the CTA Consortium completed a Design Study and started a three-year Preparatory Phase which leads to production readiness of CTA in 2014. In this paper we introduce the science goals and the concept of CTA, and provide an overview of the project. © 2013 Elsevier B.V. All rights reserved.

Biomarker responses to folic acid intervention in healthy adults: a meta-analysis of randomized controlled trials

BACKGROUND: The task of revising dietary folate recommendations for optimal health is complicated by a lack of data quantifying the biomarker response that reliably reflects a given folate intake.

OBJECTIVE: We conducted a dose-response meta-analysis in healthy adults to quantify the typical response of recognized folate biomarkers to a change in folic acid intake.

DESIGN: Electronic and bibliographic searches identified 19 randomized controlled trials that supplemented with folic acid and measured folate biomarkers before and after the intervention in apparently healthy adults aged ≥18 y. For each biomarker response, the regression coefficient (β) for individual studies and the overall pooled β were calculated by using random-effects meta-analysis.

RESULTS: Folate biomarkers (serum/plasma and red blood cell folate) increased in response to folic acid in a dose-response manner only up to an intake of 400 μg/d. Calculation of the overall pooled β for studies in the range of 50 to 400 μg/d indicated that a doubling of folic acid intake resulted in an increase in serum/plasma folate by 63% (71% for microbiological assay; 61% for nonmicrobiological assay) and red blood cell folate by 31% (irrespective of whether microbiological or other assay was used). Studies that used the microbiological assay indicated lower heterogeneity compared with studies using nonmicrobiological assays for determining serum/plasma (I(2) = 13.5% compared with I(2) = 77.2%) and red blood cell (I(2) = 45.9% compared with I(2) = 70.2%) folate.

CONCLUSIONS: Studies administering >400 μg folic acid/d show no dose-response relation and thus will not yield meaningful results for consideration when generating dietary folate recommendations. The calculated folate biomarker response to a given folic acid intake may be more robust with the use of a microbiological assay rather than alternative methods for blood folate measurement.

Embracing an integromic approach to tissue biomarker research in cancer: Perspectives and lessons learned

Modern approaches to biomedical research and diagnostics targeted towards precision medicine are generating ‘big data’ across a range of high-throughput experimental and analytical platforms. Integrative analysis of this rich clinical, pathological, molecular and imaging data represents one of the greatest bottlenecks in biomarker discovery research in cancer and other diseases. Following on from the publication of our successful framework for multimodal data amalgamation and integrative analysis, Pathology Integromics in Cancer (PICan), this article will explore the essential elements of assembling an integromics framework from a more detailed perspective. PICan, built around a relational database storing curated multimodal data, is the research tool sitting at the heart of our interdisciplinary efforts to streamline biomarker discovery and validation. While recognizing that every institution has a unique set of priorities and challenges, we will use our experiences with PICan as a case study and starting point, rationalizing the design choices we made within the context of our local infrastructure and specific needs, but also highlighting alternative approaches that may better suit other programmes of research and discovery. Along the way, we stress that integromics is not just a set of tools, but rather a cohesive paradigm for how modern bioinformatics can be enhanced. Successful implementation of an integromics framework is a collaborative team effort that is built with an eye to the future and greatly accelerates the processes of biomarker discovery, validation and translation into clinical practice.