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.

Tapping into Floor Staff: Using the knowledge of floor staff to conduct formative evaluations of exhibits in a Canadian science centre

Most science centres in Canada employ science-educated floor staff to motivate visitorsto have fun while enhancing the educational reach of the exhibits. Although bright andsensitive to visitors’ needs, floor staff are rarely consulted in the planning,implementation, and modification phases of an exhibit. Instead, many developmentteams rely on costly third-party evaluations or skip the front-end and formativeevaluations all together, leading to costly errors that could have been avoided. This studywill seek to reveal a correlation between floor staff’s perception of visitors’ interactionswith an exhibit and visitors’ actual experiences. If a correlation exists, a recommendationcould be made to encourage planning teams to include floor staff in the formative andsummative evaluations of an exhibit. This is especially relevant to science centres withlimited budgets and for whom a divide exists between floor staff and management.In this study, a formative evaluation of one exhibit was conducted, measuring both floorstaff’s perceptions of the visitor experience and visitors’ own perceptions of the exhibit.Floor staff were then trained on visitor evaluation methods. A week later, floor staff andvisitors were surveyed a second time on a different exhibit to determine whether anincrease in accuracy existed.The training session increased the specificity of the motivation and comprehensionresponses and the enthusiasm of the staff, but not their ability to predict observedbehaviours with respect to ergonomics, learning indicators, holding power, and successrates. The results revealed that although floor staff underestimated visitors’ success ratesat the exhibits, staff accurately predicted visitors’ behaviours with respect to holdingpower, ergonomics, learning indicators, motivation and comprehension, both before andafter the staff training.

Can France really stop them? : A study grounded on the realist perspective about the French foreign policy towards Syria as the root cause of the Phenomenon of French Foreign Fighters

During the Syrian conflict the number of European Foreign Fighters has increased exponentially and has become an ever-growing concern for European policymakers. This phenomenon presents host of major security challenges for European policymakers and governments. Among European countries, France provides the highest number of citizens who have gone to Syria to fight against Assad´s regime. The French authorities have estimated that by mid-2014, over 700 French citizens have left France and travelled to Syria to fight. Historically France has had a relationship with Syria which started with its role as a border-drawing colonial power. Grounded in a framework of realism, that emphasizes nation-states as the primary actor within the international system, the analysis concentrates on the role of France´s foreign policy on the Syria as push factor for terrorism and radicalization. This paper attempts to determinate a specific correlation between the policy that France has been conducting towards Syria between 2000 and 2015, and the phenomenon of French Foreign Fighters. Findings suggest that France´s foreign policy towards Syria is the main root cause of the French Foreign Fighters phenomenon.

The Capm and Fama-French models in Brazil: a comparative study

This paper confronts the Capital Asset Pricing Model - CAPM - and the 3-Factor Fama-French - FF - model using both Brazilian and US stock market data for the same Sample period (1999-2007). The US data will serve only as a benchmark for comparative purposes. We use two competing econometric methods, the Generalized Method of Moments (GMM) by (Hansen, 1982) and the Iterative Nonlinear Seemingly Unrelated Regression Estimation (ITNLSUR) by Burmeister and McElroy (1988). Both methods nest other options based on the procedure by Fama-MacBeth (1973). The estimations show that the FF model fits the Brazilian data better than CAPM, however it is imprecise compared with the US analog. We argue that this is a consequence of an absence of clear-cut anomalies in Brazilian data, specially those related to firm size. The tests on the efficiency of the models - nullity of intercepts and fitting of the cross-sectional regressions - presented mixed conclusions. The tests on intercept failed to rejected the CAPM when Brazilian value-premium-wise portfolios were used, contrasting with US data, a very well documented conclusion. The ITNLSUR has estimated an economically reasonable and statistically significant market risk premium for Brazil around 6.5% per year without resorting to any particular data set aggregation. However, we could not find the same for the US data during identical period or even using a larger data set. Este estudo procura contribuir com a literatura empírica brasileira de modelos de apreçamento de ativos. Dois dos principais modelos de apreçamento são Infrontados, os modelos Capital Asset Pricing Model (CAPM)e de 3 fatores de Fama-French. São aplicadas ferramentas econométricas pouco exploradas na literatura nacional na estimação de equações de apreçamento: os métodos de GMM e ITNLSUR. Comparam-se as estimativas com as obtidas de dados americanos para o mesmo período e conclui-se que no Brasil o sucesso do modelo de Fama e French é limitado. Como subproduto da análise, (i) testa-se a presença das chamadas anomalias nos retornos, e (ii) calcula-se o prêmio de risco implícito nos retornos das ações. Os dados revelam a presença de um prêmio de valor, porém não de um prêmio de tamanho. Utilizando o método de ITNLSUR, o prêmio de risco de mercado é positivo e significativo, ao redor de 6,5% ao ano.