Discovering biomarkers for antidepressant response:protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort

Background: Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. Methods: CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. Discussion: From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research. Trial registration: ClinicalTrials.gov identifier NCT01655706. Registered July 27, 2012.

Phase equilibrium studies at normal pressures

A total pressure apparatus has been developed to measure vapour-liquid equilibrium data on binary mixtures at atmospheric and sub-atmospheric pressures. The method gives isothermal data which can be obtained rapidly. Only measurements of total pressure are made as a direct function of composition of synthetic liquid phase composition, the vapour phase composition being deduced through the Gibbs-Duhem relationship. The need to analyse either of the phases is eliminated. As such the errors introduced by sampling and analysis are removed. The essential requirements are that the pure components be degassed completely since any deficiency in degassing would introduce errors into the measured pressures. A similarly essential requirement was that the central apparatus would have to be absolutely leak-tight as any leakage of air either in or out of the apparatus would introduce erroneous pressure readings. The apparatus was commissioned by measuring the saturated vapour pressures of both degassed water and ethanol as a function of temperature. The pressure-temperature data on degassed water measured were directly compared with data in the literature, with good agreement. Similarly the pressure-temperature data were measured for ethanol, methanol and cyclohexane and where possible a direct comparison made with the literature data. Good agreement between the pure component data of this work and those available in the literature demonstrates firstly that a satisfactory degassing procedure has been achieved and that secondly the measurements of pressure-temperature are consistent for any one component; since this is true for a number of components, the measurements of both temperature and pressure are both self-consistent and of sufficient accuracy, with an observed compatibility between the precision/accuracy of the separate means of measuring pressure and temperature. The liquid mixtures studied were of ethanol-water, methanol-water and ethanol-cyclohexane. The total pressure was measured as the composition inside the equilibrium cell was varied at a set temperature. This gave P-T-x data sets for each mixture at a range of temperatures. A standard fitting-package from the literature was used to reduce the raw data to yield y-values to complete the x-y-P-T data sets. A consistency test could not be applied to the P-T-x data set as no y-values were obtained during the experimental measurements. In general satisfactory agreement was found between the data of this work and those available in the literature. For some runs discrepancies were observed, and further work recommended to eliminate the problems identified.

Studies of the effects of molecular encounters on N.M.R. spin-lattice relaxation times

This thesis is concerned with investigations of the effects of molecular encounters on nuclear magnetic resonance spin-lattice relaxation times, with particular reference to mesitylene in mixtures with cyclohexane and TMS. The purpose of the work was to establish the best theoretical description of T1 and assess whether a recently identified mechanism (buffeting), that influences n.m.r. chemical shifts, governs Tl also. A set of experimental conditions are presented that allow reliable measurements of Tl and the N. O. E. for 1H and 13C using both C. W. and F.T. n.m.r. spectroscopy. Literature data for benzene, cyclohexane and chlorobenzene diluted by CC14 and CS2 are used to show that the Hill theory affords the best estimation of their correlation times but appears to be mass dependent. Evaluation of the T1 of the mesitylene protons indicates that a combined Hill-Bloembergen-Purcell-Pound model gives an accurate estimation of T1; subsequently this was shown to be due to cancellation of errors in the calculated intra and intemolecular components. Three experimental methods for the separation of the intra and intermolecular relaxation times are described. The relaxation times of the 13C proton satellite of neat bezene, 1,4 dioxane and mesitylene were measured. Theoretical analyses of the data allow the calculation of Tl intra. Studies of intermolecular NOE's were found to afford a general method of separating observed T1's into their intra and intermolecular components. The aryl 1H and corresponding 13C T1 values and the NOE for the ring carbon of mesitylene in CC14 and C6H12-TMS have been used in combination to determine T1intra and T1inter. The Hill and B.P.P. models are shown to predict similarly inaccurate values for T1linter. A buffeting contribution to T1inter is proposed which when applied to the BPP model and to the Gutowsky-Woessner expression for T1inter gives an inaccuracy of 12% and 6% respectively with respect to theexperimentally based T1inter.

The use of future Internet technologies in the agriculture and food sectors:integrating the supply chain

The Future Internet is expected to greatly influence how the food and agriculture sector is currently operating. In this paper, we present the specific characteristics of the agri-food sector focusing on how information management in this area will take place under a highly heterogeneous group of actors and services, based on the EU SmartAgriFood project. We also discuss how a new dynamic marketplace will be realized based on the adoption of a number of specialized software modules, called “Generic Enablers” that are currently developed in the context of the EU FI-WARE project. Thus, the paper presents the overall vision for data integration along the supply chain as well as the development and federation of Future Internet services that are expected to revolutionize the agriculture sector.

Multispectral fundus analysis

Purpose - To generate a reflectance model of the fundus that allows an accurate non-invasive quantification of blood and pigments. Methods - A Monte Carlo simulation was used to produce a mathematical model of light interaction with the fundus at different wavelengths. The model predictions were compared with fundus images from normal volunteers in several spectral bands (peaks at 507, 525, 552, 585, 596 and 611nm). Th e model was then used to calculate the concentration and distribution of the known absorbing components of the fundus. Results - The shape of the statistical distribution of the image data generally corresponded to that of the model data; the model however appears to overestimate the reflectance of the fundus in the longer wavelength region.As the absorption by xanthophyll has no significant eff ect on light transport above 534nm, its distribution in the fundus was quantified: the wavelengths where both shape and distribution of image and model data matched (<553nm) were used to train a neural network which was then applied to every point in the image data. The xanthophyll distribution thus found was in agreement with published literature data in normal subjects. Conclusion - We have developed a method for optimising multi-spectral imaging of the fundus and a computer image analysis capable of estimating information about the structure and properties of the fundus. Th e technique successfully calculates the distribution of xanthophyll in the fundus of healthy volunteers. Further improvement of the model is required to allow the deduction of other parameters from images; investigations in known pathology models are also necessary to establish if this method is of clinical use in detecting early chroido-retinopathies, hence providing a useful screening and diagnostic tool.

Enhancing visibility in EPCIS governing agri-food supply chains via linked pedigrees

Data integration for the purposes of tracking, tracing and transparency are important challenges in the agri-food supply chain. The Electronic Product Code Information Services (EPCIS) is an event-oriented GS1 standard that aims to enable tracking and tracing of products through the sharing of event-based datasets that encapsulate the Electronic Product Code (EPC). In this paper, the authors propose a framework that utilises events and EPCs in the generation of "linked pedigrees" - linked datasets that enable the sharing of traceability information about products as they move along the supply chain. The authors exploit two ontology based information models, EEM and CBVVocab within a distributed and decentralised framework that consumes real time EPCIS events as linked data to generate the linked pedigrees. The authors exemplify the usage of linked pedigrees within the fresh fruit and vegetables supply chain in the agri-food sector.

The integration of multi-source data to improve the classification of remotely sensed images

The number of remote sensing platforms and sensors rises almost every year, yet much work on the interpretation of land cover is still carried out using either single images or images from the same source taken at different dates. Two questions could be asked of this proliferation of images: can the information contained in different scenes be used to improve the classification accuracy and, what is the best way to combine the different imagery? Two of these multiple image sources are MODIS on the Terra platform and ETM+ on board Landsat7, which are suitably complementary. Daily MODIS images with 36 spectral bands in 250-1000 m spatial resolution and seven spectral bands of ETM+ with 30m and 16 days spatial and temporal resolution respectively are available. In the UK, cloud cover may mean that only a few ETM+ scenes may be available for any particular year and these may not be at the time of year of most interest. The MODIS data may provide information on land cover over the growing season, such as harvest dates, that is not present in the ETM+ data. Therefore, the primary objective of this work is to develop a methodology for the integration of medium spatial resolution Landsat ETM+ image, with multi-temporal, multi-spectral, low-resolution MODIS \Terra images, with the aim of improving the classification of agricultural land. Additionally other data may also be incorporated such as field boundaries from existing maps. When classifying agricultural land cover of the type seen in the UK, where crops are largely sown in homogenous fields with clear and often mapped boundaries, the classification is greatly improved using the mapped polygons and utilising the classification of the polygon as a whole as an apriori probability in classifying each individual pixel using a Bayesian approach. When dealing with multiple images from different platforms and dates it is highly unlikely that the pixels will be exactly co-registered and these pixels will contain a mixture of different real world land covers. Similarly the different atmospheric conditions prevailing during the different days will mean that the same emission from the ground will give rise to different sensor reception. Therefore, a method is presented with a model of the instantaneous field of view and atmospheric effects to enable different remote sensed data sources to be integrated.

Relational diversity, social integration and individual effectiveness: a social self-regulation perspective

Relational demographers and dissimilarity researchers contend that group members who are dissimilar (vs. similar) to their peers in terms of a given diversity attribute (e.g. demographics, attitudes, values or traits) feel less attached to their work group, experience less satisfying and more conflicted relationships with their colleagues, and consequently are less effective. However, qualitative reviews suggest empirical findings tend to be weak and inconsistent (Chattopadhyay, Tluchowska and George, 2004; Riordan, 2000; Tsui and Gutek, 1999), and that it remains unclear when, how and to what extent such differences (i.e. relational diversity) affect group members social integration (i.e. attachment with their work group, satisfaction and conflicted relationships with their peers) and effectiveness (Riordan, 2000). This absence of meta-analytically derived effect size estimates and the lack of an integrative theoretical framework leave practitioners with inconclusive advice regarding whether the effects elicited by relational diversity are practically relevant, and if so how these should be managed. The current research develops an integrative theoretical framework, which it tests by using meta-analysis techniques and adding two further empirical studies to the literature. The first study reports a meta-analytic integration of the results of 129 tests of the relationship between relational diversity with social integration and individual effectiveness. Using meta-analytic and structural equation modelling techniques, it shows different effects of surface- and deep-level relational diversity on social integration Specifically, low levels of interdependence accentuated the negative effects of surface-level relational diversity on social integration, while high levels of interdependence accentuated the negative effects of deep-level relational diversity on social integration. The second study builds on a social self-regulation framework (Abrams, 1994) and suggests that under high levels of interdependence relational diversity is not one but two things: visibility and separation. Using ethnicity as a prominent example it was proposed that separation has a negative effect on group members effectiveness leading for those high in visibility and low in separation to overall positive additive effects, while to overall negative additive effects for those low in visibility and high in separation. These propositions were sustained in a sample of 621 business students working in 135 ethnically diverse work groups in a business simulation course over a period of 24 weeks. The third study suggests visibility has a positive effect on group members self-monitoring, while separation has a negative effect. The study proposed that high levels of visibility and low levels of separation lead to overall positive additive effects on self-monitoring but overall negative additive effects for those low in visibility and high in separation. Results from four waves of data on 261 business students working in 69 ethnically diverse work groups in a business simulation course held over a period of 24 weeks support these propositions.

Knowledge integration for analyzing ChIP-seq

To capture the genomic profiles for histone modification, chromatin immunoprecipitation (ChIP) is combined with next generation sequencing, which is called ChIP-seq. However, enriched regions generated from the ChIP-seq data are only evaluated on the limited knowledge acquired from manually examining the relevant biological literature. This paper proposes a novel framework, which integrates multiple knowledge sources such as biological literature, Gene Ontology, and microarray data. In order to precisely analyze ChIP-seq data for histone modification, knowledge integration is based on a unified probabilistic model. The model is employed to re-rank the enriched regions generated from peak finding algorithms. Through filtering the reranked enriched regions using some predefined threshold, more reliable and precise results could be generated. The combination of the multiple knowledge sources with the peaking finding algorithm produces a new paradigm for ChIP-seq data analysis. © (2012) Trans Tech Publications, Switzerland.

A taxonomy and review of the fuzzy data envelopment analysis literature:two decades in the making

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. Crisp input and output data are fundamentally indispensable in conventional DEA. However, the observed values of the input and output data in real-world problems are sometimes imprecise or vague. Many researchers have proposed various fuzzy methods for dealing with the imprecise and ambiguous data in DEA. In this study, we provide a taxonomy and review of the fuzzy DEA methods. We present a classification scheme with four primary categories, namely, the tolerance approach, the a-level based approach, the fuzzy ranking approach and the possibility approach. We discuss each classification scheme and group the fuzzy DEA papers published in the literature over the past 20 years. To the best of our knowledge, this paper appears to be the only review and complete source of references on fuzzy DEA. © 2011 Elsevier B.V. All rights reserved.

Integration of semantically annotated data by the KnoFuss architecture

Most of the existing work on information integration in the Semantic Web concentrates on resolving schema-level problems. Specific issues of data-level integration (instance coreferencing, conflict resolution, handling uncertainty) are usually tackled by applying the same techniques as for ontology schema matching or by reusing the solutions produced in the database domain. However, data structured according to OWL ontologies has its specific features: e.g., the classes are organized into a hierarchy, the properties are inherited, data constraints differ from those defined by database schema. This paper describes how these features are exploited in our architecture KnoFuss, designed to support data-level integration of semantic annotations.

Supply chain integration framework using literature review

Definitions and measures of supply chain integration (SCI) are diverse. More empirical research, with clear definition and appropriate measures are needed. The purpose of this article is to identify dimensions and variables for SCI and develop an integrated framework to facilitate this. A literature review of the relevant academic papers in international journals in Logistics, Supply Chain Management and Operations Management for the period 1995-2009 has been undertaken. This study reveals that information integration, coordination and resource sharing and organisational relationship linkage are three major dimensions for SCI. The proposed framework helps integrate both upstream suppliers and downstream customers with the focal organisation. It also allows measuring SCI using both qualitative and quantitative approach. This study encourages researchers and practitioners to identify dimensions and variables for SCI and analyses how it affects the overall supply chain (SC) performance in terms of efficiency and responsiveness. Although there is extensive research in the area of SCI, a comprehensive and integrated approach is missing. This study bridges the gap by developing a framework for measuring SCI, which enables any organisation to identify critical success factors for integrating their SC, measures the degree of integration qualitatively and quantitatively and suggest improvement measures. © 2013 Copyright Taylor and Francis Group, LLC.

Leader-member exchange and attitudes:a theoretical and empirical integration

The central proposition of this thesis is that there are key benefits to examining leadership perceptions as an attitude towards the leader. In particular, it is argued that doing so can provide an enhanced understanding of leadership perceptions and therefore advance theory in this area. To provide empirical support for this theoretcial integration, the current research focused on one of the most popular leadership theories, leader-member exchange (LMX), and demonstrated how the concept of attitude strength could advance understanding of how and when LMX influenced employee job performance. Although the measurement of LMX requires employees to provide a cognitive evaluation of their relationship with their leader, previous research has, to date, not considered this evaluation to be an attitude. This thesis provides a justification for doing so and develops two novel constructs: LMX importance and LMX ambivalence. Both of these variables are argued to represent previously unconsidered facets of the LMX relationship, which, according to attitude theory, provide a more multifaceted understanding of leadership perceptions than previously envisaged. Such an understanding can provide a more detailed understanding of how such perceptions influence outcomes. Two studies provided an empirical test of the above reasoning. Study 1, a longitudinal field study, demonstrated initial support for many of the hypotheses. LMX amivalence was shown to lead to poorer task performance and organisational citizenship behaviour, mediated by the experience of negative affect. Evidence was also found for the moderating effect of LMX importance, although felt obligations was not found to mediate this moderated effect. While Study 1 used project groups as its participants, Study 2 provided a first test of the construct in an organisational setting; with three companies proving data. Again, strong support was found for the negative effects of LMX ambivalence on employee outcomes, with evidence also found for the role of perceived organisational support in mitigating these negative effects. Support was also found for the moderated mediation hypothesis related to LMX importance, although this was only found in the largest organisation sample. Some of the main theoretical and methodological implications of viewing leadership perceptions as attitudes to the wider leadership area were discussed. The cross-fertilisation of research from the attitudes literature to understanding leadership perceptions provides new insights into leadership processes and potential avenues for further research.

Decision support based on genomics:integration of data-and knowledge-driven reasoning

The breadth and depth of available clinico-genomic information, present an enormous opportunity for improving our ability to study disease mechanisms and meet the individualised medicine needs. A difficulty occurs when the results are to be transferred 'from bench to bedside'. Diversity of methods is one of the causes, but the most critical one relates to our inability to share and jointly exploit data and tools. This paper presents a perspective on current state-of-the-art in the analysis of clinico-genomic data and its relevance to medical decision support. It is an attempt to investigate the issues related to data and knowledge integration. Copyright © 2010 Inderscience Enterprises Ltd.