30 research outputs found

    Microenvironmental acidosis in carcinogenesis and metastases: new strategies in prevention and therapy

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    Geometrically coupled monte carlo sampling

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    © 2018 Curran Associates Inc..All rights reserved. Monte Carlo sampling in high-dimensional, low-sample settings is important in many machine learning tasks. We improve current methods for sampling in Euclidean spaces by avoiding independence, and instead consider ways to couple samples. We show fundamental connections to optimal transport theory, leading to novel sampling algorithms, and providing new theoretical grounding for existing strategies. We compare our new strategies against prior methods for improving sample efficiency, including quasi-Monte Carlo, by studying discrepancy. We explore our findings empirically, and observe benefits of our sampling schemes for reinforcement learning and generative modelling

    The CX3C-Chemokine Fractalkine (CX3CL1) is Detectable in Serum of Patients Affected by the Inflammatory Diseases Allergic Rhinitis and/or Asthma

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    Fractalkine (FKN) is a chemokine able to mediate the initial capture, firm adhesion, and activation of circulating leukocytes. Many tissues express FKN mRNA and FKN expression is increased during inflammatory conditions. To assess a possible involvement in allergic airway disease, we detected serum levels of FKN in a group of patients affected by allergic rhinitis and/or asthma and found high serum levels of FKN in all patients and in only 26% of healthy donors at lower concentrations. The present results underscore the potential role that this chemokine may play in the pathogenesis of respiratory allergic diseases
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