Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks

Evaluating similarity between graphs is of major importance in several computer vision and pattern recognition problems, where graph representations are often used to model objects or interactions between elements. The choice of a distance or similarity metric is, however, not trivial and can be highly dependent on the application at hand. In this work, we propose a novel metric learning method to evaluate distance between graphs that leverages the power of convolutional neural networks, while exploiting concepts from spectral graph theory to allow these operations on irregular graphs. We demonstrate the potential of our method in the field of connectomics, where neuronal pathways or functional connections between brain regions are commonly modelled as graphs. In this problem, the definition of an appropriate graph similarity function is critical to unveil patterns of disruptions associated with certain brain disorders. Experimental results on the ABIDE dataset show that our method can learn a graph similarity metric tailored for a clinical application, improving the performance of a simple k-nn classifier by 11.9% compared to a traditional distance metric.Comment: International Conference on Medical Image Computing and Computer-Assisted Interventions (MICCAI) 201

Extracting the Groupwise Core Structural Connectivity Network: Bridging Statistical and Graph-Theoretical Approaches

Finding the common structural brain connectivity network for a given population is an open problem, crucial for current neuro-science. Recent evidence suggests there's a tightly connected network shared between humans. Obtaining this network will, among many advantages , allow us to focus cognitive and clinical analyses on common connections, thus increasing their statistical power. In turn, knowledge about the common network will facilitate novel analyses to understand the structure-function relationship in the brain. In this work, we present a new algorithm for computing the core structural connectivity network of a subject sample combining graph theory and statistics. Our algorithm works in accordance with novel evidence on brain topology. We analyze the problem theoretically and prove its complexity. Using 309 subjects, we show its advantages when used as a feature selection for connectivity analysis on populations, outperforming the current approaches

Spectral Graph Convolutions for Population-based Disease Prediction

Exploiting the wealth of imaging and non-imaging information for disease prediction tasks requires models capable of representing, at the same time, individual features as well as data associations between subjects from potentially large populations. Graphs provide a natural framework for such tasks, yet previous graph-based approaches focus on pairwise similarities without modelling the subjects' individual characteristics and features. On the other hand, relying solely on subject-specific imaging feature vectors fails to model the interaction and similarity between subjects, which can reduce performance. In this paper, we introduce the novel concept of Graph Convolutional Networks (GCN) for brain analysis in populations, combining imaging and non-imaging data. We represent populations as a sparse graph where its vertices are associated with image-based feature vectors and the edges encode phenotypic information. This structure was used to train a GCN model on partially labelled graphs, aiming to infer the classes of unlabelled nodes from the node features and pairwise associations between subjects. We demonstrate the potential of the method on the challenging ADNI and ABIDE databases, as a proof of concept of the benefit from integrating contextual information in classification tasks. This has a clear impact on the quality of the predictions, leading to 69.5% accuracy for ABIDE (outperforming the current state of the art of 66.8%) and 77% for ADNI for prediction of MCI conversion, significantly outperforming standard linear classifiers where only individual features are considered.Comment: International Conference on Medical Image Computing and Computer-Assisted Interventions (MICCAI) 201

Longitudinal impact of process-oriented guided inquiry learning on the attitudes, self-efficacy and experiences of pre-medical chemistry students

A follow-up study was conducted with foundation-year chemistry students who were taught in an inquiry- and role-based, small-group active learning environment in order to evaluate their attitudes, experiences and self-efficacy during pre-medical chemistry courses. The study adopted a mixedmethods research design that involved both experimental and comparison groups. Using the CAEQ (Chemistry Attitudes and Experiences Questionnaire) and the ASCI v2 (Attitude toward the Study of Chemistry Inventory), the findings of this study indicated that inquiry-based chemistry learning experience improves the students’ intellectual accessibility and emotional satisfaction as well as develops their self-efficacy levels while pursuing intensive pre-medical courses in chemistry. The results of the qualitative data analyses using a course experience questionnaire indicated that the process-oriented guided inquiry learning (POGIL) experience helped the students succeed in rigorous pre-medical chemistry courses and gained some process skills required in the medical programme as listed by the AAMC (American Association of Medical Colleges)

NKX2-5 regulates vessel remodelling in scleroderma-associated pulmonary arterial hypertension.

NKX2-5 is a member of the homeobox-containing transcription factors critical in regulating tissue differentiation in development. Here, we report a role for NKX2-5 in vascular smooth muscle cell phenotypic modulation in vitro and in vascular remodelling in vivo. NKX2-5 is up-regulated in scleroderma (SSc) patients with pulmonary arterial hypertension. Suppression of NKX2-5 expression in smooth muscle cells, halted vascular smooth muscle proliferation and migration, enhanced contractility and blocked the expression of the extracellular matrix genes. Conversely, overexpression of NKX2-5 suppressed the expression of contractile genes (ACTA2, TAGLN, CNN1) and enhanced the expression of matrix genes (COL1) in vascular smooth muscle cells. In vivo, conditional deletion of NKX2-5 attenuated blood vessel remodelling and halted the progression to hypertension in the mouse chronic hypoxia mouse model. This study revealed that signals related to injury such as serum and low confluence, which induce NKX2-5 expression in cultured cells, is potentiated by TGFβ and further enhanced by hypoxia. The effect of TGFβ was sensitive to ERK5 and PI3K inhibition. Our data suggest a pivotal role for NKX2-5 in the phenotypic modulation of smooth muscle cells during pathological vascular remodelling and provide proof of concept for therapeutic targeting of NKX2-5 in vasculopathies

Quantifying Morphological Evolution from Low to High Redshifts

Establishing the morphological history of ordinary galaxies was one of the original goals for the Hubble Space Telescope, and remarkable progress toward achieving this this goal has been made. How much of this progress has been at the expense of the Hubble sequence? As we probe further out in redshift space, it seems time to re-examine the underlying significance of Hubble's tuning fork in light of the the spectacular and often bizarre morphological characteristics of high redshift galaxies. The aim of this review is to build a morphological bridge between high-redshift and low-redshift galaxy populations, by using quantitative morphological measures to determine the maximum redshift for which the Hubble sequence provides a meaningful description of the galaxy population. I will outline the various techniques used to quantify high-redshift galaxy morphology, highlight the aspects of the Hubble sequence being probed by these techniques, and indicate what is getting left behind. I will argue that at higher redshifts new techniques (and new ideas) that place less emphasis on classical morphology and more emphasis on the link between morphology and resolved stellar populations are needed in order to probe the evolutionary history of high-redshift galaxies

Receptor-Mediated Enhancement of Beta Adrenergic Drug Activity by Ascorbate In Vitro and In Vivo

RATIONALE: Previous in vitro research demonstrated that ascorbate enhances potency and duration of activity of agonists binding to alpha 1 adrenergic and histamine receptors. OBJECTIVES: Extending this work to beta 2 adrenergic systems in vitro and in vivo. METHODS: Ultraviolet spectroscopy was used to study ascorbate binding to adrenergic receptor preparations and peptides. Force transduction studies on acetylcholine-contracted trachealis preparations from pigs and guinea pigs measured the effect of ascorbate on relaxation due to submaximal doses of beta adrenergic agonists. The effect of inhaled albuterol with and without ascorbate was tested on horses with heaves and sheep with carbachol-induced bronchoconstriction. MEASUREMENTS: Binding constants for ascorbate binding to beta adrenergic receptor were derived from concentration-dependent spectral shifts. Dose- dependence curves were obtained for the relaxation of pre-contracted trachealis preparations due to beta agonists in the presence and absence of varied ascorbate. Tachyphylaxis and fade were also measured. Dose response curves were determined for the effect of albuterol plus-and-minus ascorbate on airway resistance in horses and sheep. MAIN RESULTS: Ascorbate binds to the beta 2 adrenergic receptor at physiological concentrations. The receptor recycles dehydroascorbate. Physiological and supra-physiological concentrations of ascorbate enhance submaximal epinephrine and isoproterenol relaxation of trachealis, producing a 3-10-fold increase in sensitivity, preventing tachyphylaxis, and reversing fade. In vivo, ascorbate improves albuterol's effect on heaves and produces a 10-fold enhancement of albuterol activity in "asthmatic" sheep. CONCLUSIONS: Ascorbate enhances beta-adrenergic activity via a novel receptor-mediated mechanism; increases potency and duration of beta adrenergic agonists effective in asthma and COPD; prevents tachyphylaxis; and reverses fade. These novel effects are probably caused by a novel mechanism involving phosphorylation of aminergic receptors and have clinical and drug-development applications

Ants Constructing Rule-Based Classifiers

Book series: Studies in Computational Intelligencestatus: publishe

Complications of biliary-enteric anastomoses

INTRODUCTION Biliary-enteric anastomoses are performed for a range of indications and may result in early and late complications. The aim of this study was to assess the risk factors and management of anastomotic leak and stricture following biliary-enteric anastomosis. METHODS A retrospective analysis of the medical records of patients who underwent biliary-enteric anastomoses in a tertiary referral centre between 2000 and 2010 was performed. RESULTS Four hundred and sixty-two biliary-enteric anastomoses were performed. Of these, 347 (75%) were performed for malignant disease. Roux-en-Y hepaticojejunostomy or choledocho-jejunostomy were performed in 440 (95%) patients. Perioperative 30-day mortality was 6.5% (n=30). Seventeen patients had early bile leaks (3.7%) and 17 had late strictures (3.7%) at a median of 12 months. On univariable logistic regression analysis, younger age was a significant risk factor for biliary anastomotic leak. However, on multivariable analysis only biliary reconstruction following biliary injury (odds ratio [OR]=6.84; p=0.002) and anastomosis above the biliary confluence (OR=4.62; p=0.03) were significant. Younger age and biliary reconstruction following injury appeared to be significant risk factors for biliary strictures but multivariable analysis showed that only younger age was significant. CONCLUSIONS Biliary-enteric anastomoses have a low incidence of early and late complications. Biliary reconstruction following injury and a high anastomosis (above the confluence) are significant risk factors for anastomotic leak. Younger patients are significantly more likely to develop an anastomotic stricture over the longer term