1,637 research outputs found

    Does stimulant therapy help adult ADHD?

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    Central nervous system stimulants improve symptoms of attention deficit-hyperactivity disorder (ADHD) in adults (strength of recommendation: B, based on an older, inconclusive systematic review, a lesser-quality systematic review, and several newer small randomized controlled trials). Although not the focus of this question, nonstimulant medications (including buproprion, modafinil, and guanfacine) have also been studied in the treatment of ADHD in adults. Recently, atomoxetine became the only nonstimulant medication to receive approval by the US Food and Drug Administration for the treatment of ADHD

    A curvature-enhanced random walker segmentation method for detailed capture of 3D cell surface Membranes

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    High-resolution 3D microscopy is a fast advancing field and requires new techniques in image analysis to handle these new datasets. In this work, we focus on detailed 3D segmentation of Dictyostelium cells undergoing macropinocytosis captured on an iSPIM microscope. We propose a novel random walker-based method with a curvature-based enhancement term, with the aim of capturing fine protrusions, such as filopodia and deep invaginations, such as macropinocytotic cups, on the cell surface. We tested our method on both real and synthetic 3D image volumes, demonstrating that the inclusion of the curvature enhancement term can improve the segmentation of the aforementioned features. We show that our method performs better than other state of the art segmentation methods in 3D images of Dictyostelium cells, and performs competitively against CNN-based methods in two Cell Tracking Challenge datasets, demonstrating the ability to obtain accurate segmentations without the requirement of large training datasets. We also present an automated seeding method for microscopy data, which, combined with the curvature-enhanced random walker method, enables the segmentation of large time series with minimal input from the experimenter

    Artificial Darwinism: an overview

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    Genetic algorithms, genetic programming, evolution strategies, and what is now called evolutionary algorithms, are stochastic optimisation techniques inspired by Darwin’s theory. We present here an overview of these techniques, while stressing on the extreme versatility of the artificial evolution concept. Their applicative framework is very large and is not limited to pure optimisation. Artifical evolution implementations are however computationally expensive: an efficient tuning of the components and parameter of these algorithms should be based on a clear comprehension of the evolutionary mechanisms. Moreover, it is noticeable that the killer-applications of the domain are for the most part based on hybridisation with other optimisation techniques. As a consequence, evolutionary algorithms are not to be considered in competition but rather in complement to the “classical ” optimisation techniques.Les algorithmes génétiques, la programmation génétique, les stratégies d’évolution, et ce que l’on appelle maintenant en général les algorithmes évolutionnaires, sont des techniques d’optimisation stochastiques inspirées de la théorie de l’évolution selon Darwin. Nous donnons ici une vision globale de ces techniques, en insistant sur l’extrême flexibilité du concept d’évolution artificielle. Cet outil a un champ très vaste d’applications, qui ne se limite pas à l’optimisation pure. Leur mise en oeuvre se fait cependant au prix d’un coût calculatoire important, d’où la nécessité de bien comprendre ces mécanismes d’évolution pour adapter et régler efficacement les différentes composantes de ces algorithmes. Par ailleurs, on note que les applications-phares de ce domaine sont assez souvent fondées sur une hybridation avec d’autres techniques d’optimisation. Les algorithmes évolutionnaires ne sont donc pas à considérer comme une méthode d’optimisation concurrente des méthodes d’optimisation classiques, mais plutôt comme une approche complémentaire

    Generative adversarial networks for augmenting training data of microscopic cell images

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    Generative adversarial networks (GANs) have recently been successfully used to create realistic synthetic microscopy cell images in 2D and predict intermediate cell stages. In the current paper we highlight that GANs can not only be used for creating synthetic cell images optimized for different fluorescent molecular labels, but that by using GANs for augmentation of training data involving scaling or other transformations the inherent length scale of biological structures is retained. In addition, GANs make it possible to create synthetic cells with specific shape features, which can be used, for example, to validate different methods for feature extraction. Here, we apply GANs to create 2D distributions of fluorescent markers for F-actin in the cell cortex of Dictyostelium cells (ABD), a membrane receptor (cAR1), and a cortex-membrane linker protein (TalA). The recent more widespread use of 3D lightsheet microscopy, where obtaining sufficient training data is considerably more difficult than in 2D, creates significant demand for novel approaches to data augmentation. We show that it is possible to directly generate synthetic 3D cell images using GANs, but limitations are excessive training times, dependence on high-quality segmentations of 3D images, and that the number of z-slices cannot be freely adjusted without retraining the network. We demonstrate that in the case of molecular labels that are highly correlated with cell shape, like F-actin in our example, 2D GANs can be used efficiently to create pseudo-3D synthetic cell data from individually generated 2D slices. Because high quality segmented 2D cell data are more readily available, this is an attractive alternative to using less efficient 3D networks

    What are effective treatments for oppositional and defiant behaviors in preadolescents?

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    Parent training is effective for treating oppositional and defiant behaviors (strength of recommendation [SOR]: A, based on systematic reviews). Parent training programs are standardized, short-term interventions that teach parents specialized strategies--including positive attending, ignoring, the effective use of rewards and punishments, token economies, and time out --to address clinically significant behavior problems. In addition to parent training, other psychosocial interventions are efficacious in treating oppositional and defiant behavior. To date, no studies have assessed the efficacy of medication in treating children with pure oppositional defiant disorder (ODD). However, studies have shown amphetamines to be effective for children with ODD and comorbid attention deficit/hyperactivity disorder (ADHD) (SOR: A, based on a meta-analysis)

    MiCellAnnGELo: Annotate microscopy time series of complex cell surfaces with 3D Virtual Reality

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    Summary: Advances in 3D live cell microscopy are enabling high-resolution capture of previously unobserved processes. Unleashing the power of modern machine learning methods to fully benefit from these technologies is, however, frustrated by the difficulty of manually annotating 3D training data. MiCellAnnGELo virtual reality software offers an immersive environment for viewing and interacting with 4D microscopy data, including efficient tools for annotation. We present tools for labelling cell surfaces with a wide range of applications, including cell motility, endocytosis, and transmembrane signalling. Availability and implementation: MiCellAnnGELo employs the cross platform (Mac/Unix/Windows) Unity game engine and is available under the MIT licence at https://github.com/CellDynamics/MiCellAnnGELo.git, together with sample data and demonstration movies. MiCellAnnGELo can be run in desktop mode on a 2D screen or in 3D using a standard VR headset with compatible GPU.Comment: For associated code and sample data, see https://github.com/CellDynamics/MiCellAnnGELo.gi

    Artificial Evolution, 5th International Conference, Evolution Artificielle, EA 200. Selected Papers

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    Digital capture of the histological microarchitecture in the myometrium and its implications for the propagation of electrophysiological excitation.

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    Coordination of uterine contractions during labour is critical for successful delivery. The mechanisms underlying this coordination are not fully understood. Propagation of contraction signals has previously been observed to occur through transmission of electrical excitation waves. This thesis aims to examine the histological microarchitecture of the muscular layer of the uterus (myometrium) and determine how this structure affects the propagation of excitation by means of in silico three-dimensional reconstruction of the myometrium and numerical simulations of a spatially structured excitation-relaxation model. A key aim of the in silico reconstruction of the smooth muscle architecture of the myometrium is to identify structural features that correspond to the control of excitation behaviour in the myometrium. This examination is aided by analysis of excitation patterns observed in multi-electrode array recordings. The reconstruction is subsequently used as a basis for simulating electrical activity in the myometrium. Novel structural features are identified here that are located at the initiation points of electrical activity and are proposed to be the pacemaker sites in rat myometrium. Furthermore, boundary of low connectivity across the mesometrial border was observed in the rat, which corresponds to the termination of excitation waves observed in multielectrode array recordings. In addition, bridges of smooth muscle cells connecting the inner and outer layers of the myometrium were observed in both rat and human myometrium. Taken together these three features suggest a novel mechanism for control of contraction in the rat myometrium; an analogous mechanism is proposed for the human myometrium. The results presented in this thesis could provide an explanation for the patterns of excitation propagation observed in human and rat uteri. Further refinements of the methods used here are outlined and expected to generate a more detailed visualisation of the structures underpinning these mechanisms

    Rapport final de la Collaboration CERN-CNRS pour la construction du LHC: Accord Technique d'Exécution No 2 Cryostats et assemblage des sections droites courtes (SSS) du LHC

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    Depuis 1995 et suite à la signature du protocole de Collaboration, le CERN, le CEA et le CNRS ont étroitement collaboré dans le cadre de la contribution exceptionnelle de la France à la construction du LHC. Pour le CNRS, l'Institut de Physique Nucléaire d'Orsay a pris en charge deux Accords Techniques d'Exécution. Le premier concerne la conception et l'assemblage des Sections Droites Courtes de la machine, et le deuxième, l'étalonnage des thermomètres cryogéniques du LHC. Dans le cadre de l'Accord Technique d'Exécution N°2, le Bureau d'Etudes de la Division Accélérateur de l'IPNO et le groupe AT-CRI du CERN ont travaillé de concert pour mener à bien la conception des SSS (Short Straight Section) et de tous les équipements nécessaires à l'assemblage. Ce rapport a donc pour objectif de dresser, en termes d'historique, d'organisation, de résultats quantitatifs et qualitatifs et de moyens mis en ?uvre, un tableau aussi complet que possible du déroulement de cette Collaboration entre le CERN et le CNRS

    3D Model based stereo reconstruction using coupled Markov random fields

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