Dictionary Learning and Sparse Coding-based Denoising for High-Resolution Task Functional Connectivity MRI Analysis

We propose a novel denoising framework for task functional Magnetic Resonance Imaging (tfMRI) data to delineate the high-resolution spatial pattern of the brain functional connectivity via dictionary learning and sparse coding (DLSC). In order to address the limitations of the unsupervised DLSC-based fMRI studies, we utilize the prior knowledge of task paradigm in the learning step to train a data-driven dictionary and to model the sparse representation. We apply the proposed DLSC-based method to Human Connectome Project (HCP) motor tfMRI dataset. Studies on the functional connectivity of cerebrocerebellar circuits in somatomotor networks show that the DLSC-based denoising framework can significantly improve the prominent connectivity patterns, in comparison to the temporal non-local means (tNLM)-based denoising method as well as the case without denoising, which is consistent and neuroscientifically meaningful within motor area. The promising results show that the proposed method can provide an important foundation for the high-resolution functional connectivity analysis, and provide a better approach for fMRI preprocessing.Comment: 8 pages, 3 figures, MLMI201

Deep Modeling of Growth Trajectories for Longitudinal Prediction of Missing Infant Cortical Surfaces

Charting cortical growth trajectories is of paramount importance for understanding brain development. However, such analysis necessitates the collection of longitudinal data, which can be challenging due to subject dropouts and failed scans. In this paper, we will introduce a method for longitudinal prediction of cortical surfaces using a spatial graph convolutional neural network (GCNN), which extends conventional CNNs from Euclidean to curved manifolds. The proposed method is designed to model the cortical growth trajectories and jointly predict inner and outer cortical surfaces at multiple time points. Adopting a binary flag in loss calculation to deal with missing data, we fully utilize all available cortical surfaces for training our deep learning model, without requiring a complete collection of longitudinal data. Predicting the surfaces directly allows cortical attributes such as cortical thickness, curvature, and convexity to be computed for subsequent analysis. We will demonstrate with experimental results that our method is capable of capturing the nonlinearity of spatiotemporal cortical growth patterns and can predict cortical surfaces with improved accuracy.Comment: Accepted as oral presentation at IPMI 201

Appetite suppressants and valvular heart disease - a systematic review

Background Although appetite suppressants have been implicated in the development of valvular heart disease, the exact level of risk is still uncertain. Initial studies suggested that as many as 1 in 3 exposed patients were affected, but subsequent research has yielded substantially different figures. Our objective was to systematically assess the risk of valvular heart disease with appetite suppressants. Methods We accepted studies involving obese patients treated with any of the following appetite suppressants: fenfluramine, dexfenfluramine, and phentermine. Three types of studies were reviewed: controlled and uncontrolled observational studies, and randomized controlled trials. Outcomes of interest were echocardiographically detectable aortic regurgitation of mild or greater severity, or mitral regurgitation of moderate or greater severity. Results Of the 1279 patients evaluated in seven uncontrolled cohort studies, 236 (18%) and 60 (5%) were found to have aortic and mitral regurgitation, respectively. Pooled data from six controlled cohort studies yielded, for aortic regurgitation, a relative risk ratio of 2.32 (95% confidence intervals 1.79 to 3.01, p < 0.00001) and an attributable rate of 4.9%, and for mitral regurgitation, a relative risk ratio of 1.55 (95% confidence intervals 1.06 to 2.25, p = 0.02) with an attributable rate of 1.0%. Only one case of valvular heart disease was detected in 57 randomized controlled trials, but this was judged unrelated to drug therapy. Conclusions The risk of valvular heart disease is significantly increased by the appetite suppressants reviewed here. Nevertheless, when considering all the evidence, valvulopathy is much less common than suggested by the initial, less methodologically rigorous studies

Establishing bioinformatics research in the Asia Pacific

In 1998, the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation was set up to champion the advancement of bioinformatics in the Asia Pacific. By 2002, APBioNet was able to gain sufficient critical mass to initiate the first International Conference on Bioinformatics (InCoB) bringing together scientists working in the field of bioinformatics in the region. This year, the InCoB2006 Conference was organized as the 5(th )annual conference of the Asia-Pacific Bioinformatics Network, on Dec. 18–20, 2006 in New Delhi, India, following a series of successful events in Bangkok (Thailand), Penang (Malaysia), Auckland (New Zealand) and Busan (South Korea). This Introduction provides a brief overview of the peer-reviewed manuscripts accepted for publication in this Supplement. It exemplifies a typical snapshot of the growing research excellence in bioinformatics of the region as we embark on a trajectory of establishing a solid bioinformatics research culture in the Asia Pacific that is able to contribute fully to the global bioinformatics community

A new class of pluripotent stem cell cytotoxic small molecules

10.1371/journal.pone.0085039PLoS ONE93-POLN

Risk of valvular heart disease associated with use of fenfluramine

BACKGROUND: Estimates of excess risk of valvular heart disease among prior users of fenfluramine and dexfenfluramine have varied widely. Two major forms of bias appear to contribute to this variability and also result in a systematic under-estimation of risk. The first, a form of nondifferential misclassification, is the result of including background, prevalent cases among both exposed and unexposed persons in calculations of risk. The second bias results from not considering the relatively short duration of exposure to drugs. METHODS: We examined data from all available echocardiographic studies reporting the prevalence of aortic regurgitation (AR) and mitral regurgitation (MR) among persons exposed to fenfluramine or dexfenfluramine and a suitable control group. We also included one study in which previously existing AR or MR had been excluded. We corrected for background prevalent cases, estimated incidence rates in unexposed persons, and performed a person-years analysis of apparent incidence rates based on exposure time to provide an unbiased estimate of relative risk. RESULTS: Appearance of new AR was strongly related to duration of exposure (R(2 )= 0.75, p < 0.0001). The summary relative risk for mild or greater AR was 19.6 (95% CI 16.3 – 23.5, p < 0.00001); for moderate or greater MR it was 5.9 (95% CI 4.0 – 8.6, p < 0.00001). CONCLUSION: These findings provide strong support for the view that fenfluramine and dexfenfluramine are potent causal factors in the development of both aortic and mitral valvular heart disease

A clinical diagnostic model for predicting influenza among young adult military personnel with febrile respiratory illness in Singapore

10.1371/journal.pone.0017468PLoS ONE63

CSN-mediated deneddylation differentially modulates Ci155 proteolysis to promote Hedgehog signalling responses

The Hedgehog (Hh) morphogen directs distinct cell responses according to its distinct signalling levels. Hh signalling stabilizes transcription factor cubitus interruptus (Ci) by prohibiting SCFSlimb-dependent ubiquitylation and proteolysis of Ci. How graded Hh signalling confers differential SCFSlimb-mediated Ci proteolysis in responding cells remains unclear. Here, we show that in COP9 signalosome (CSN) mutants, in which deneddylation of SCFSlimb is inactivated, Ci is destabilized in low-to-intermediate Hh signalling cells. As a consequence, expression of the low-threshold Hh target gene dpp is disrupted, highlighting the critical role of CSN deneddylation on low-to-intermediate Hh signalling response. The status of Ci phosphorylation and the level of E1 ubiquitin-activating enzyme are tightly coupled to this CSN regulation. We propose that the affinity of substrate–E3 interaction, ligase activity and E1 activity are three major determinants for substrate ubiquitylation and thereby substrate degradation in vivo