106 research outputs found

    Real-time myocardial landmark tracking for MRI-guided cardiac radio-ablation using Gaussian Processes

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    The high speed of cardiorespiratory motion introduces a unique challenge for cardiac stereotactic radio-ablation (STAR) treatments with the MR-linac. Such treatments require tracking myocardial landmarks with a maximum latency of 100 ms, which includes the acquisition of the required data. The aim of this study is to present a new method that allows to track myocardial landmarks from few readouts of MRI data, thereby achieving a latency sufficient for STAR treatments. We present a tracking framework that requires only few readouts of k-space data as input, which can be acquired at least an order of magnitude faster than MR-images. Combined with the real-time tracking speed of a probabilistic machine learning framework called Gaussian Processes, this allows to track myocardial landmarks with a sufficiently low latency for cardiac STAR guidance, including both the acquisition of required data, and the tracking inference. The framework is demonstrated in 2D on a motion phantom, and in vivo on volunteers and a ventricular tachycardia (arrhythmia) patient. Moreover, the feasibility of an extension to 3D was demonstrated by in silico 3D experiments with a digital motion phantom. The framework was compared with template matching - a reference, image-based, method - and linear regression methods. Results indicate an order of magnitude lower total latency (<10 ms) for the proposed framework in comparison with alternative methods. The root-mean-square-distances and mean end-point-distance with the reference tracking method was less than 0.8 mm for all experiments, showing excellent (sub-voxel) agreement. The high accuracy in combination with a total latency of less than 10 ms - including data acquisition and processing - make the proposed method a suitable candidate for tracking during STAR treatments

    AI for Everyone? Critical Perspectives

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    We are entering a new era of technological determinism and solutionism in which governments and business actors are seeking data-driven change, assuming that Artificial Intelligence is now inevitable and ubiquitous. But we have not even started asking the right questions, let alone developed an understanding of the consequences. Urgently needed is debate that asks and answers fundamental questions about power. This book brings together critical interrogations of what constitutes AI, its impact and its inequalities in order to offer an analysis of what it means for AI to deliver benefits for everyone. The book is structured in three parts: Part 1, AI: Humans vs. Machines, presents critical perspectives on human-machine dualism. Part 2, Discourses and Myths About AI, excavates metaphors and policies to ask normative questions about what is ‘desirable’ AI and what conditions make this possible. Part 3, AI Power and Inequalities, discusses how the implementation of AI creates important challenges that urgently need to be addressed. Bringing together scholars from diverse disciplinary backgrounds and regional contexts, this book offers a vital intervention on one of the most hyped concepts of our times

    Structure and photophysics of indigoids for singlet fission: Cibalackrot

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    We report an investigation of structure and photophysics of thin layers of cibalackrot, a sturdy dye derived from indigo by double annulation at the central double bond. Evaporated layers contain up to three phases, two crystalline and one amorphous. Relative amounts of all three have been determined by a combination of X-ray diffraction and FT-IR reflectance spectroscopy. Initially, excited singlet state rapidly produces a high yield of a transient intermediate whose spectral properties are compatible with charge-transfer nature. This intermediate more slowly converts to a significant yield of triplet, which, however, does not exceed 100% and may well be produced by intersystem crossing rather than singlet fission. The yields were determined by transient absorption spectroscopy and corrected for effects of partial sample alignment by a simple generally applicable procedure. Formation of excimers was also observed. In order to obtain guidance for improving molecular packing by a minor structural modification, calculations by a simplified frontier orbital method were used to find all local maxima of singlet fission rate as a function of geometry of a molecular pair. The method was tested at 48 maxima by comparison with the ab initio Frenkel-Davydov exciton model. Published under license by AIP Publishing

    Alumoxane/ferroxane nanoparticles for the removal of viral pathogens: the importance of surface functionality to nanoparticle activity

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    A bi-functional nano-composite coating has been created on a porous Nomex fabric support as a trap for aspirated virus contaminated water. Nomex fabric was successively dip-coated in solutions containing cysteic acid functionalized alumina (alumoxane) nanoparticles and cysteic acid functionalized iron oxide (ferroxane) nanoparticles to form a nanoparticle coated Nomex (NPN) fabric. From SEM and EDX the nanoparticle coating of the Nomex fibers is uniform, continuous, and conformal. The NPN was used as a filter for aspirated bacteriophage MS2 viruses using end-on filtration. All measurements were repeated to give statistical reliability. The NPN fabrics show a large decrease as compared to Nomex alone or alumoxane coated Nomex . An increase in the ferroxane content results in an equivalent increase in virus retention. This suggests that it is the ferroxane that has an active role in deactivating and/or binding the virus. Heating the NPN to 160 C results in the loss of cysteic acid functional groups (without loss of the iron nanoparticleメs core structure) and the resulting fabric behaves similar to that of untreated Nomex , showing that the surface functionalization of the nanoparticles is vital for the surface collapse of aspirated water droplets and the absorption and immobilization of the MS2 viruses. Thus, for virus immobilization, it is not sufficient to have iron oxide nanoparticles per se, but the surface functionality of a nanoparticle is vitally important in ensuring efficacy

    Genome-wide association study identifies variants in the MHC class I, IL10, and IL23R-IL12RB2 regions associated with Behcet's disease

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    Behcet's disease is a genetically complex disease of unknown etiology characterized by recurrent inflammatory attacks affecting the orogenital mucosa, eyes and skin. We performed a genome-wide association study with 311,459 SNPs in 1,215 individuals with Behcet's disease (cases) and 1,278 healthy controls from Turkey. We confirmed the known association of Behcet's disease with HLA-B*51 and identified a second, independent association within the MHC Class I region. We also identified an association at IL10 (rs1518111, P = 1.88 x 10(-8)). Using a meta-analysis with an additional five cohorts from Turkey, the Middle East, Europe and Asia, comprising a total of 2,430 cases and 2,660 controls, we identified associations at IL10 (rs1518111, P = 3.54 x 10(-18), odds ratio = 1.45, 95% CI 1.34-1.58) and the IL23R-IL12RB2 locus (rs924080, P = 6.69 x 10(-9), OR = 1.28, 95% CI 1.18-1.39). The disease-associated IL10 variant (the rs1518111 A allele) was associated with diminished mRNA expression and low protein production

    Effect of gut microbiome modulation on muscle function and cognition: the PROMOTe randomised controlled trial

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    Studies suggest that inducing gut microbiota changes may alter both muscle physiology and cognitive behaviour. Gut microbiota may play a role in both anabolic resistance of older muscle, and cognition. In this placebo controlled double blinded randomised controlled trial of 36 twin pairs (72 individuals), aged ≥60, each twin pair are block randomised to receive either placebo or prebiotic daily for 12 weeks. Resistance exercise and branched chain amino acid (BCAA) supplementation is prescribed to all participants. Outcomes are physical function and cognition. The trial is carried out remotely using video visits, online questionnaires and cognitive testing, and posting of equipment and biological samples. The prebiotic supplement is well tolerated and results in a changed gut microbiome [e.g., increased relative Bifidobacterium abundance]. There is no significant difference between prebiotic and placebo for the primary outcome of chair rise time (β = 0.579; 95% CI −1.080-2.239 p = 0.494). The prebiotic improves cognition (factor score versus placebo (β = −0.482; 95% CI,−0.813, −0.141; p = 0.014)). Our results demonstrate that cheap and readily available gut microbiome interventions may improve cognition in our ageing population. We illustrate the feasibility of remotely delivered trials for older people, which could reduce under-representation of older people in clinical trials. ClinicalTrials.gov registration: NCT04309292

    Clinical Use and Therapeutic Potential of IVIG/SCIG, Plasma-Derived IgA or IgM, and Other Alternative Immunoglobulin Preparations

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    Intravenous and subcutaneous immunoglobulin preparations, consisting of IgG class antibodies, are increasingly used to treat a broad range of pathological conditions, including humoral immune deficiencies, as well as acute and chronic inflammatory or autoimmune disorders. A plethora of Fab- or Fc-mediated immune regulatory mechanisms has been described that might act separately or in concert, depending on pathogenesis or stage of clinical condition. Attempts have been undertaken to improve the efficacy of polyclonal IgG preparations, including the identification of relevant subfractions, mild chemical modification of molecules, or modification of carbohydrate side chains. Furthermore, plasma-derived IgA or IgM preparations may exhibit characteristics that might be exploited therapeutically. The need for improved treatment strategies without increase in plasma demand is a goal and might be achieved by more optimal use of plasma-derived proteins, including the IgA and the IgM fractions. This article provides an overview on the current knowledge and future strategies to improve the efficacy of regular IgG preparations and discusses the potential of human plasma-derived IgA, IgM, and preparations composed of mixtures of IgG, IgA, and IgM

    Artificial neural network (ANN) approach for modelling of pile settlement of open-ended steel piles subjected to compression load

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    This study was devoted to examine pile bearing capacity and to provide a reliable model to simulate pile load-settlement behaviour using a new artificial neural network (ANN) method. To achieve the planned aim, experimental pile load test were carried out on model open-ended steel piles, with pile aspect ratios of 12, 17, and 25. An optimised second-order Levenberg-Marquardt (LM) training algorithm has been used in this process. The piles were driven in three sand densities; dense, medium, and loose. A statistical analysis test was conducted to explore the relative importance and the statistical contribution (Beta and Sig) values of the independent variables on the model output. Pile effective length, pile flexural rigidity, applied load, sand-pile friction angle and pile aspect ratio have been identified to be the most effective parameters on model output. To demonstrate the effectiveness of the proposed algorithm, a graphical comparison was performed between the implemented algorithm and the most conventional pile capacity design approaches. The proficiency metric indicators demonstrated an outstanding agreement between the measured and predicted pile-load settlement, thus yielding a correlation coefficient (R) and root mean square error (RMSE) of 0.99, 0.043 respectively, with a relatively insignificant mean square error level (MSE) of 0.0019. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group
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