9,630 research outputs found

    Patient's breath controls comfort devices

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    Patient assist system for totally disabled persons was developed which permits a person, so paralyzed as to be unable to move, to activate by breathing, a call system to summon assistance, turn the page of a book, ajust his bed, or do any one of a number of other things. System consists of patient assist control and breath actuated switch

    Longitudinal multivariate tensor- and searchlight-based morphometry using permutation testing

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    Tensor based morphometry [1] was used to detect statistically significant regions of neuroanatomical change over time in a comparison between 36 probable Alzheimer's Disease patients and 20 age- and sexmatched controls. Baseline and twelve-month repeat Magnetic Resonance images underwent tied spatial normalisation [10] and longitudinal high-dimensional warps were then estimated. Analyses involved univariate and multivariate data derived from the longitudinal deformation fields. The most prominent findings were expansion of the fluid spaces, and contraction of the hippocampus and temporal region. Multivariate measures were notably more powerful, and have the potential to identify patterns of morphometric difference that would be overlooked by conventional mass-univariate analysis

    Supporting the active learning of collaborative database browsing techniques

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    We describe the implications of a study of database browsing behaviour for the development of a system to support more effective browsing. In particular we consider the importance of collaborative working, both in learning browsing skills and in co‐operating on a shared information‐retrieval task. From our study, we believe that an interface to support collaboration should promote the awareness of the activities of others, better visualization of the information data structures being browsed, and effective communication of the browsing process

    Bayesian log-Gaussian Cox process regression: applications to meta-analysis of neuroimaging working memory studies

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    Working memory (WM) was one of the first cognitive processes studied with functional magnetic resonance imaging. With now over 20 years of studies on WM, each study with tiny sample sizes, there is a need for meta-analysis to identify the brain regions that are consistently activated by WM tasks, and to understand the interstudy variation in those activations. However, current methods in the field cannot fully account for the spatial nature of neuroimaging meta-analysis data or the heterogeneity observed among WM studies. In this work, we propose a fully Bayesian random-effects metaregression model based on log-Gaussian Cox processes, which can be used for meta-analysis of neuroimaging studies. An efficient Markov chain Monte Carlo scheme for posterior simulations is presented which makes use of some recent advances in parallel computing using graphics processing units. Application of the proposed model to a real data set provides valuable insights regarding the function of the WM

    Reevaluación crítica del holotipo de Beothukis mistakensis, único organismo rangeomorfo excepcionalmente preservado en Mistaken Point, Terranova, Canadá

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    The holotype of Beothukis mistakensis in Mistaken Point, Newfoundland, is the only currently known specimen that can be definitely placed within the species. Morphological differences between the holotype of B. mistakensis and the well-constrained species plumosa suggest that the two are not congeneric and Culmofrons plumosa should be retained as a valid taxon as originally established.El holotipo de Beothukis mistakensis en Mistaken Point, Terranova, es el único ejemplar actualmente conocido que puede ser colocado definitivamente dentro de la especie. Las diferencias morfológicas entre el holotipo de B. mistakensis y la especie plumosa sugieren que ambas no son congéneres y que Culmofrons plumosa debería conservarse como un taxón válido tal como se estableció originalmente

    Towards structured sharing of raw and derived neuroimaging data across existing resources

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    Data sharing efforts increasingly contribute to the acceleration of scientific discovery. Neuroimaging data is accumulating in distributed domain-specific databases and there is currently no integrated access mechanism nor an accepted format for the critically important meta-data that is necessary for making use of the combined, available neuroimaging data. In this manuscript, we present work from the Derived Data Working Group, an open-access group sponsored by the Biomedical Informatics Research Network (BIRN) and the International Neuroimaging Coordinating Facility (INCF) focused on practical tools for distributed access to neuroimaging data. The working group develops models and tools facilitating the structured interchange of neuroimaging meta-data and is making progress towards a unified set of tools for such data and meta-data exchange. We report on the key components required for integrated access to raw and derived neuroimaging data as well as associated meta-data and provenance across neuroimaging resources. The components include (1) a structured terminology that provides semantic context to data, (2) a formal data model for neuroimaging with robust tracking of data provenance, (3) a web service-based application programming interface (API) that provides a consistent mechanism to access and query the data model, and (4) a provenance library that can be used for the extraction of provenance data by image analysts and imaging software developers. We believe that the framework and set of tools outlined in this manuscript have great potential for solving many of the issues the neuroimaging community faces when sharing raw and derived neuroimaging data across the various existing database systems for the purpose of accelerating scientific discovery

    Romidepsin inhibits Ras-dependent growth transformation of NIH 3T3 fibroblasts and RIE-1 epithelial cells independently of Ras signaling inhibition

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    Abstract Background Despite intensive effort, currently no effective anti-Ras therapies have successfully reached clinical application. Previous studies suggest that the histone deacetylatse (HDAC) inhibitor romidepsin, which is currently in clinical trials for the treatment of multiple malignancies, can block Ras-dependent signaling and growth transformation. These studies suggest that mutational activation of Ras may be a useful biomarker for sensitivity to romidepsin and that the anti-tumor activity of this HDAC inhibitor may involve inhibition of Ras effector-mediated signaling. Results To rigorously assess romidepsin as an antagonist of Ras, we utilized two well-characterized cell models for Ras transformation. We found that romidepsin blocked the anchorage-dependent and -independent growth of NIH 3T3 fibroblasts and RIE-1 epithelial cells transformed by all three Ras isoforms. However, romidepsin treatment also blocked growth transformation caused by other oncoproteins (B-Raf and ErbB2/Neu), suggesting that romidepsin is not selective for Ras. We also observed striking differences in romidepsin-mediated growth inhibition between transformed NIH 3T3 fibroblasts compared to RIE-1 epithelial cells, suggesting that the mechanism by which romidepsin blocks transformation is dependent on cellular context. Finally, we found that romidepsin did not inhibit Ras activation of the ERK and AKT effector pathways in NIH 3T3 and RIE-1 cells, suggesting that romidepsin does not directly antagonize Ras. Conclusion Taken together, our results suggest that romidepsin is not selective for Ras-transformed cells and that the anti-tumor activity of romidepsin is not due to direct inhibition of Ras function
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