Baseline Objective Inflammation by Magnetic Resonance Imaging as a Predictor of Therapeutic Benefit in Early Rheumatoid Arthritis With Poor Prognosis

Objective: High magnetic resonance imaging (MRI )–detected inflammation is associated with greater progression and poorer outcomes in rheumatoid arthritis (RA ). This analysis aimed to determine if baseline MRI inflammation was related to clinical response and remission in the Assessing Very Early Rheumatoid arthritis Treatment (AVERT ) study. Methods: AVERT was a phase III b, randomized, controlled trial with a 12‐month, double‐blind treatment period enrolling patients with early (≤2 years' duration), anti‐citrullinated peptide–positive methotrexate (MTX )‐naive RA . In this post hoc analysis, patients in the abatacept plus MTX (n = 114) and MTX (n = 111) arms with available MRI results were stratified into low and high baseline MRI inflammation groups based on previously developed cutoffs of synovitis and osteitis on unilateral hand–wrist contrast‐enhanced MRI . Simplified Disease Activity Index (SDAI ) remission (≤3.3), Clinical Disease Activity Index (CDAI ) remission (≤2.8), Boolean remission, and Disease Activity Score in 28 joints using the C‐reactive protein level (<2.6) were assessed. Results: Overall, 100 of 225 patients (44.4%) had high baseline MRI inflammation. In patients with high baseline MRI inflammation, a significantly greater proportion achieved remission at 12 months with abatacept plus MTX versus MTX across SDAI (45.1% versus 16.3%; P = 0.0022), CDAI (47.1% versus 20.4%; P = 0.0065), and Boolean indices (39.2% versus 16.3%; P = 0.0156). In patients with low baseline MRI inflammation, remission rates were not significantly different with abatacept plus MTX versus MTX (SDAI : 39.7% versus 32.3%; P = 0.4961). Conclusion: In seropositive, MTX ‐naive patients with early RA and presence of objectively measured high inflammation by MRI , indicating poor prognosis, remission rates were higher with abatacept plus MTX treatment versus MTX

Solving ill-posed bilevel programs

This paper deals with ill-posed bilevel programs, i.e., problems admitting multiple lower-level solutions for some upper-level parameters. Many publications have been devoted to the standard optimistic case of this problem, where the difficulty is essentially moved from the objective function to the feasible set. This new problem is simpler but there is no guaranty to obtain local optimal solutions for the original optimistic problem by this process. Considering the intrinsic non-convexity of bilevel programs, computing local optimal solutions is the best one can hope to get in most cases. To achieve this goal, we start by establishing an equivalence between the original optimistic problem an a certain set-valued optimization problem. Next, we develop optimality conditions for the latter problem and show that they generalize all the results currently known in the literature on optimistic bilevel optimization. Our approach is then extended to multiobjective bilevel optimization, and completely new results are derived for problems with vector-valued upper- and lower-level objective functions. Numerical implementations of the results of this paper are provided on some examples, in order to demonstrate how the original optimistic problem can be solved in practice, by means of a special set-valued optimization problem

An assessment of the statistical distribution of Random Telegraph Noise Time Constants

As transistor sizes are downscaled, a single trapped charge has a larger impact on smaller devices and the Random Telegraph Noise (RTN) becomes increasingly important. To optimize circuit design, one needs assessing the impact of RTN on the circuit and this can only be accomplished if there is an accurate statistical model of RTN. The dynamic Monte Carlo modelling requires the statistical distribution functions of both the amplitude and the capture/emission time (CET) of traps. Early works were focused on the amplitude distribution and the experimental data of CETs were typically too limited to establish their statistical distribution reliably. In particular, the time window used has been often small, e.g. 10 sec or less, so that there are few data on slow traps. It is not known whether the CET distribution extracted from such a limited time window can be used to predict the RTN beyond the test time window. The objectives of this work are three fold: to provide the long term RTN data and use them to test the CET distributions proposed by early works; to propose a methodology for characterizing the CET distribution for a fabrication process efficiently; and, for the first time, to verify the long term prediction capability of a CET distribution beyond the time window used for its extraction

Bifidobacterium longum 1714 as a translational psychobiotic: modulation of stress, electrophysiology and neurocognition in healthy volunteers

The emerging concept of psychobiotics—live microorganisms with a potential mental health benefit—represents a novel approach for the management of stress-related conditions. The majority of studies have focused on animal models. Recent preclinical studies have identified the B. longum 1714 strain as a putative psychobiotic with an impact on stress-related behaviors, physiology and cognitive performance. Whether such preclinical effects could be translated to healthy human volunteers remains unknown. We tested whether psychobiotic consumption could affect the stress response, cognition and brain activity patterns. In a within-participants design, healthy volunteers (N=22) completed cognitive assessments, resting electroencephalography and were exposed to a socially evaluated cold pressor test at baseline, post-placebo and post-psychobiotic. Increases in cortisol output and subjective anxiety in response to the socially evaluated cold pressor test were attenuated. Furthermore, daily reported stress was reduced by psychobiotic consumption. We also observed subtle improvements in hippocampus-dependent visuospatial memory performance, as well as enhanced frontal midline electroencephalographic mobility following psychobiotic consumption. These subtle but clear benefits are in line with the predicted impact from preclinical screening platforms. Our results indicate that consumption of B. longum 1714 is associated with reduced stress and improved memory. Further studies are warranted to evaluate the benefits of this putative psychobiotic in relevant stress-related conditions and to unravel the mechanisms underlying such effects

Metamodel-assisted design optimization of piezoelectric flex transducer for maximal bio-kinetic energy conversion

Energy Harvesting Devices (EHD) have been widely used to generate electrical power from the bio-kinetic energy of human body movement. A novel Piezoelectric Flex Transducer (PFT) based on the Cymbal device has been proposed by Daniels et al. (2013) for the purpose of energy harvesting. To further improve the efficiency of the device, optimal design of the PFT for maximum output power subject to stress and displacement constraints is carried out in this paper. Sequential Quadratic Programming (SQP) on metamodels generated with Genetic Programming from a 140-point optimal Latin hypercube design of experiments is used in the optimization. Finally, the optimal design is validated by finite element simulations. The simulations show that the magnitude of the electrical power generated from this optimal PFT harvesting device can be up to 6.5 mw when a safety design factor of 2.0 is applied

Determining MRI Inflammation Targets When Considering a Rheumatoid Arthritis Treat-to-Target Strategy: Results of a Randomized, Placebo-Controlled Trial

Introduction Magnetic resonance imaging (MRI) is increasingly used in patients with rheumatoid arthritis (RA) to determine residual inflammation after treatment and as a predictor of structural damage progression. Establishing an optimal threshold of inflammatory activity that predicts lower risk of structural damage progression may inform treatment decisions. This post hoc analysis investigated whether patients with RA at low risk of structural damage progression can be identified based on MRI inflammation thresholds. Methods Hand and wrist MRI was performed at baseline, and at months 6 and 12 in a phase 3b, randomized, active-controlled, double-blind trial of abatacept in early RA (AVERT). Pathologies were scored using the OMERACT RA MRI Score. Data were stratified into two risk subgroups (less and more severe inflammation) for structural damage progression (erosion change > 0.5) based on baseline inflammation. In this post hoc analysis, log odds ratios of probability of progression {adjusted for baseline Disease Activity Score in 28 joints [C-reactive protein; DAS28 (CRP)]} were compared between subgroups to test the performance of inflammation thresholds. Results There were 351 randomized and treated patients with baseline MRIs, of whom 276 (78.6%) and 235 (67.0%) had MRIs available at months 6 and 12, respectively. The DAS28 (CRP)-adjusted probabilities of progression from baseline to month 12 based on scores at baseline, and from months 6 to 12 based on month 6 scores, were significantly lower among patients with less inflammation (P < 0.0001–0.0459), independent of clinical disease activity. Predefined thresholds of synovitis ≤ 3 (total score 21), osteitis ≤ 3 (total score 69) and total inflammation score (osteitis double-weighted) ≤ 9 were associated with a lower likelihood of structural damage progression in unadjusted analyses. Conclusion Levels of MRI-determined inflammatory activity below defined thresholds were independently associated with a lower risk of structural damage progression in early RA, providing a potential trial endpoint for levels of inflammation not associated with progression. Trial Registration ClinicalTrials.gov identifier, NCT01142726. Funding Bristol-Myers Squibb

Long-distance quantum communication with atomic ensembles and linear optics

Quantum communication holds a promise for absolutely secure transmission of secret messages and faithful transfer of unknown quantum states. Photonic channels appear to be very attractive for physical implementation of quantum communication. However, due to losses and decoherence in the channel, the communication fidelity decreases exponentially with the channel length. We describe a scheme that allows to implement robust quantum communication over long lossy channels. The scheme involves laser manipulation of atomic ensembles, beam splitters, and single-photon detectors with moderate efficiencies, and therefore well fits the status of the current experimental technology. We show that the communication efficiency scale polynomially with the channel length thereby facilitating scalability to very long distances.Comment: 2 tex files (Main text + Supplement), 4 figure

Maximum energy conversion from human motion using piezoelectric flex transducer: A multi-level surrogate modeling strategy

Conventional engineering design optimization requires a large amount of expensive experimental tests from prototypes or computer simulations, which may result in an inefficient and unaffordable design process. In order to overcome these disadvantages, a surrogate model may be used to replace the prototype tests. To construct a surrogate model of sufficient accuracy from limited number of tests/simulations, a multi-level surrogate modeling strategy is introduced in this article. First, a chosen number of points determined by optimal Latin Hypercube Design of Experiments are used to generate global-level surrogate models with genetic programming and the fitness landscape can be explored by genetic algorithms for near-optimal solutions. Local-level surrogate models are constructed then from the extended-optimal Latin Hypercube samples in the vicinity of global optimum on the basis of a much smaller number of chosen points. As a result, an improved optimal design is achieved. The efficiency of this strategy is demonstrated by the parametric optimization design of a piezoelectric flex transducer energy harvester. The optimal design is verified by finite element simulations and the results show that the proposed multi-level surrogate modeling strategy has the advantages of faster convergence and more efficiency in comparison with the conventional single-single level surrogate modeling technique

Theory of disk accretion onto supermassive black holes

Accretion onto supermassive black holes produces both the dramatic phenomena associated with active galactic nuclei and the underwhelming displays seen in the Galactic Center and most other nearby galaxies. I review selected aspects of the current theoretical understanding of black hole accretion, emphasizing the role of magnetohydrodynamic turbulence and gravitational instabilities in driving the actual accretion and the importance of the efficacy of cooling in determining the structure and observational appearance of the accretion flow. Ongoing investigations into the dynamics of the plunging region, the origin of variability in the accretion process, and the evolution of warped, twisted, or eccentric disks are summarized.Comment: Mostly introductory review, to appear in "Supermassive black holes in the distant Universe", ed. A.J. Barger, Kluwer Academic Publishers, in pres