3,467 research outputs found
Review of presentations at the 6th European Lupus Meeting 3-5 March 2005.
The 6th European Lupus Meeting was held at the Royal College of Physicians of London and was attended by 450 delegates. The conference brought together leading speakers from Europe and North America who reviewed current knowledge and exciting new developments in both clinical and basic science aspects of systemic lupus erythematosus. This review summarizes the major points covered in each session
Annus Mirabilis - a guide to the 6th European Lupus meeting 3-5 March 2005
This article has no abstract
Arginine mutation alters binding of a human monoclonal antibody to antigens linked to systemic lupus erythematosus and the antiphospholipid syndrome
Objective: Previous studies have shown the importance of somatic mutations and arginine residues in the complementarity-determining regions (CDRs) of pathogenic anti-double-stranded DNA (anti-dsDNA) antibodies in human and murine lupus, and in studies of murine antibodies, a role of mutations at position 53 in VH CDR2 has been demonstrated. We previously demonstrated in vitro expression and mutagenesis of the human IgG1 monoclonal antibody B3. The present study was undertaken to investigate, using this expression system, the importance of the arginine residue at position 53 (R53) in B3 VH.
Methods: R53 was altered, by site-directed mutagenesis, to serine, asparagine, or lysine, to create 3 expressed variants of VH. In addition, the germline sequence of the VH3-23 gene (from which B3 VH is derived) was expressed either with or without arginine at position 53. These 5 new heavy chains, as well as wild-type B3 VH, were expressed with 4 different light chains, and the resulting antibodies were assessed for their ability to bind to nucleosomes, -actinin, cardiolipin, ovalbumin, 2-glycoprotein I (2GPI), and the N-terminal domain of 2GPI (domain I), using direct binding assays.
Results: The presence of R53 was essential but not sufficient for binding to dsDNA and nucleosomes. Conversely, the presence of R53 reduced binding to -actinin, ovalbumin, 2GPI, and domain I of 2GPI. The combination B3 (R53S) VH/B3 VL bound human, but not bovine, 2GPI.
Conclusion: The fact that the R53S substitution significantly alters binding of B3 to different clinically relevant antigens, but that the alteration is in opposite directions depending on the antigen, implies that this arginine residue plays a critical role in the affinity maturation of antibody B3
Deep roots: Improving CNN efficiency with hierarchical filter groups
We propose a new method for creating computationally efficient and compact
convolutional neural networks (CNNs) using a novel sparse connection structure
that resembles a tree root. This allows a significant reduction in
computational cost and number of parameters compared to state-of-the-art deep
CNNs, without compromising accuracy, by exploiting the sparsity of inter-layer
filter dependencies. We validate our approach by using it to train more
efficient variants of state-of-the-art CNN architectures, evaluated on the
CIFAR10 and ILSVRC datasets. Our results show similar or higher accuracy than
the baseline architectures with much less computation, as measured by CPU and
GPU timings. For example, for ResNet 50, our model has 40% fewer parameters,
45% fewer floating point operations, and is 31% (12%) faster on a CPU (GPU).
For the deeper ResNet 200 our model has 25% fewer floating point operations and
44% fewer parameters, while maintaining state-of-the-art accuracy. For
GoogLeNet, our model has 7% fewer parameters and is 21% (16%) faster on a CPU
(GPU).Microsoft Research PhD Scholarshi
Scanning Electron Microscopy - Electron Beam Induced Current and Deep Level Transient Spectroscopy Studies of GaAs(In) Layers grown by Molecular Beam Epitaxy
Electrically active defects in indium-doped (0.6%) GaAs layers grown by Molecular Beam Epitaxy (MBE) on Si-doped (≈1x1018 cm-3) GaAs substrates have been studied by the combination of two techniques: Scanning Electron Microscope - Electron Beam Induced Current (SEM-EBIC) technique, and Deep Level Transient Spectroscopy (DLTS). The epilayers studied were three microns thick. No electrically active defects were revealed by the EBIC micrographs in the top one micron of the epilayers, whereas a large number of non-propagating misfit dislocations were observed at the epilayer/substrate interface. DLTS measurements made in the dislocation free top region of the epilayer showed the presence of three well known traps, which had previously been observed to also exist near the interface. It is concluded that these traps are not related to misfit dislocations
Refining Architectures of Deep Convolutional Neural Networks
© 2016 IEEE. Deep Convolutional Neural Networks (CNNs) have recently evinced immense success for various image recognition tasks [11, 27]. However, a question of paramount importance is somewhat unanswered in deep learning research - is the selected CNN optimal for the dataset in terms of accuracy and model size? In this paper, we intend to answer this question and introduce a novel strategy that alters the architecture of a given CNN for a specified dataset, to potentially enhance the original accuracy while possibly reducing the model size. We use two operations for architecture refinement, viz. stretching and symmetrical splitting. Stretching increases the number of hidden units (nodes) in a given CNN layer, while a symmetrical split of say K between two layers separates the input and output channels into K equal groups, and connects only the corresponding input-output channel groups. Our procedure starts with a pre-trained CNN for a given dataset, and optimally decides the stretch and split factors across the network to refine the architecture. We empirically demonstrate the necessity of the two operations. We evaluate our approach on two natural scenes attributes datasets, SUN Attributes [16] and CAMIT-NSAD [20], with architectures of GoogleNet and VGG-11, that are quite contrasting in their construction. We justify our choice of datasets, and show that they are interestingly distinct from each other, and together pose a challenge to our architectural refinement algorithm. Our results substantiate the usefulness of the proposed method
IgG anti-apolipoprotein A-1 antibodies in patients with systemic lupus erythematosus are associated with disease activity and corticosteroid therapy: an observational study.
IgG anti-apolipoprotein A-1 (IgG anti-apoA-1) antibodies are present in patients with systemic lupus erythematosus (SLE) and may link inflammatory disease activity and the increased risk of developing atherosclerosis and cardiovascular disease (CVD) in these patients. We carried out a rigorous analysis of the associations between IgG anti-apoA-1 levels and disease activity, drug therapy, serology, damage, mortality and CVD events in a large British SLE cohort
Simultaneous Quantification of Bone Edema/Adiposity and Structure in Inflamed Bone Using Chemical Shift-Encoded MRI in Spondyloarthritis
PURPOSE: To evaluate proton density fat fraction (PDFF) and R2* as markers of bone marrow composition and structure in inflamed bone in patients with spondyloarthritis. METHODS: Phantoms containing fat, water, and trabecular bone were constructed with proton density fat fraction (PDFF) and bone mineral density (BMD) values matching those expected in healthy bone marrow and disease states, and scanned using chemical shift-encoded MRI (CSE-MRI) at 3T. Measured PDFF and R2* values in phantoms were compared with reference FF and BMD values. Eight spondyloarthritis patients and 10 controls underwent CSE-MRI of the sacroiliac joints. PDFF and R2* in areas of inflamed bone and fat metaplasia in patients were compared with normal bone marrow in controls. RESULTS: In phantoms, PDFF measurements were accurate over the full range of PDFF and BMD values. R2* measurements were positively associated with BMD but also were influenced by variations in PDFF. In patients, PDFF was reduced in areas of inflammation and increased in fat metaplasia compared to normal marrow. R2* measurements were significantly reduced in areas of fat metaplasia. CONCLUSION: PDFF measurements reflect changes in marrow composition in areas of active inflammation and structural damage and could be used for disease monitoring in spondyloarthritis. R2* measurements may provide additional information bone mineral density but also are influenced by fat content
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Measuring neural net robustness with constraints
Despite having high accuracy, neural nets have been shown to be susceptible
to adversarial examples, where a small perturbation to an input can cause it to
become mislabeled. We propose metrics for measuring the robustness of a neural
net and devise a novel algorithm for approximating these metrics based on an
encoding of robustness as a linear program. We show how our metrics can be used
to evaluate the robustness of deep neural nets with experiments on the MNIST
and CIFAR-10 datasets. Our algorithm generates more informative estimates of
robustness metrics compared to estimates based on existing algorithms.
Furthermore, we show how existing approaches to improving robustness "overfit"
to adversarial examples generated using a specific algorithm. Finally, we show
that our techniques can be used to additionally improve neural net robustness
both according to the metrics that we propose, but also according to previously
proposed metrics
Improved algorithm for quantum separability and entanglement detection
Determining whether a quantum state is separable or entangled is a problem of
fundamental importance in quantum information science. It has recently been
shown that this problem is NP-hard. There is a highly inefficient `basic
algorithm' for solving the quantum separability problem which follows from the
definition of a separable state. By exploiting specific properties of the set
of separable states, we introduce a new classical algorithm that solves the
problem significantly faster than the `basic algorithm', allowing a feasible
separability test where none previously existed e.g. in 3-by-3-dimensional
systems. Our algorithm also provides a novel tool in the experimental detection
of entanglement.Comment: 4 pages, revtex4, no figure
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