Radiological skeletal survey or computed tomography are currently applied to assess bone diseases in patients with monoclonal plasma cell disorders. Whole-body magnetic resonance imaging (whole-body MRI) allows detecting the infiltration of clonal cells in nearly the whole bone marrow compartment even before bone destruction has occurred. Those MRI results (i.e., patterns of bone marrow infiltration) have been demonstrated to be of prognostic significance in patients with symptomatic as well as asymptomatic multiple myeloma. We have therefore analyzed the findings of whole-body MRI in 137 consecutive individuals with monoclonal gammopathy of undetermined significance (MGUS). A focal infiltration pattern was detected in 23.4% of patients. Presence and number of focal lesions as well as value of M-Protein were of independent prognostic significance for progression into a symptomatic disease requiring systemic treatment (P=0.02; P<0.0001 and P=0.0005, respectively). Lower homogeneous signal intensities in T1-weighted images were related to a physiologically higher bone marrow cellularity in younger individuals (P=0.002). We conclude that whole-body MRI identifies patients with focal accumulations of presumably monoclonal cells in bone marrow with prognostic impact concerning the risk of progression into symptomatic disease.

Our goal is to learn control policies for robots that provably generalize well to novel environments given a dataset of example environments. The key technical idea behind our approach is to leverage tools from generalization theory in machine learning by exploiting a precise analogy (which we present in the form of a reduction) between generalization of control policies to novel environments and generalization of hypotheses in the supervised learning setting. In particular, we utilize the probably approximately correct (PAC)-Bayes framework, which allows us to obtain upper bounds that hold with high probability on the expected cost of (stochastic) control policies across novel environments. We propose policy learning algorithms that explicitly seek to minimize this upper bound. The corresponding optimization problem can be solved using convex optimization (relative entropy programming in particular) in the setting where we are optimizing over a finite policy space. In the more general setting of continuously parameterized policies (e.g., neural network policies), we minimize this upper bound using stochastic gradient descent. We present simulated results of our approach applied to learning (1) reactive obstacle avoidance policies and (2) neural network-based grasping policies. We also present hardware results for the Parrot Swing drone navigating through different obstacle environments. Our examples demonstrate the potential of our approach to provide strong generalization guarantees for robotic systems with continuous state and action spaces, complicated (e.g., nonlinear) dynamics, rich sensory inputs (e.g., depth images), and neural network-based policies.

SUMMARY-Patients coinfected with hepatitis C virus (HCV) and the trematode, Schistosoma mansoni, have an increased incidence of viral persistence and accelerated fibrosis. To investigate immunological mechanisms responsible for this more aggressive natural history of HCV, the core HCV-specific T-cell responses were analysed in 44 donated blood units rejected because they had antibodies to HCV (anti-HCV). Half also had anti-S. mansoni antibodies, evidence of past or active infection. HCV-specific ELISPOT responses were examined using pools of 180 overlapping

Replacing sucrose with non-caloric sweeteners is an approach to avoid overweight and diabetes development. Non-caloric sweeteners are classified into either artificial as sucralose or natural as stevia. Both of them have been approved by FDA, but the effects of their chronic consumption are controversial. The present study aimed to evaluate the effects of these two sweeteners, in male and female albino mice, on different blood biochemical parameters, enzymes activities and immunological parameters after 8 and 16 weeks of sweeteners administration. 40.5 mg/ml of sucrose, 5.2 mg/ml of sucralose and 4.2 mg/ml of stevia were dissolved individually in distilled water. Mice were administrated by sweetener's solution for 5 h daily. Male and female mice showed a preference for water consumption with sucralose or stevia. Both of the two sweeteners significantly reduced the hemoglobin level, HCT%, RBCs and WBCs count. After 18 weeks, significant elevations in liver and kidney function enzymes were observed in male and female mice administrated with both non-caloric sweeteners. Histopathological examination in sucralose and stevia administrated groups confirmed the biochemical results; where it revealed a severe damage in liver and kidney sections. While, sucrose administration elevated, only, the levels of ALT, AST and cholesterol in male mice. A vigorous elevation in levels of different immunoglobulin (IgG, IgE and IgA) and pro-inflammatory cytokines (IL-6 and -8), that was accompanied by a significant reduction in level of anti-inflammatory cytokine IL-10, was observed in male and female mice groups administrated with sucralose or stevia. On the other hand, sucrose administration led to an elevation in IgA and reduction in IL-10 levels.

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