Objective. To evaluate the efficacy and safety of rituximab in a randomized, double-blind, placebocontrolled phase III trial in patients with lupus nephritis treated concomitantly with mycophenolate mofetil (MMF) and corticosteroids.Methods. Patients (n ‫؍‬ 144) with class III or class IV lupus nephritis were randomized 1:1 to receive rituximab (1,000 mg) or placebo on days 1, 15, 168, and 182. The primary end point was renal response status at week 52.Results. Rituximab depleted peripheral CD19؉ B cells in 71 of 72 patients. The overall (complete and partial) renal response rates were 45.8% among the 72 patients receiving placebo and 56.9% among the 72 patients receiving rituximab (P ‫؍‬ 0.18); partial responses accounted for most of the difference. The primary end point (superior response rate with rituximab) was not achieved. Eight placebo-treated patients and no rituximab-treated patients required cyclophosphamide rescue therapy through week 52. Statistically significant improvements in serum complement C3, C4, and antidouble-stranded DNA (anti-dsDNA) levels were observed among patients treated with rituximab. In both treatment groups, a reduction in anti-dsDNA levels greater than the median reduction was associated with reduced proteinuria. The rates of serious adverse events, including infections, were similar in both groups. Neutropenia, leukopenia, and hypotension occurred more frequently in the rituximab group.Conclusion. Although rituximab therapy led to more responders and greater reductions in anti-dsDNA and C3/C4 levels, it did not improve clinical outcomes after 1 year of treatment. The combination of rituximab with MMF and corticosteroids did not result in any new or unexpected safety signals.Lupus nephritis (LN) may be observed in up to 50% of patients with systemic lupus erythematosus (SLE) and is associated with a poor prognosis (1). Although renal response rates among patients receiving standard treatment of proliferative LN may approach ClinicalTrials.gov identifier: NCT00282347.

Objective B cells are likely to contribute to the pathogenesis of systemic lupus erythematosus (SLE), and rituximab induces depletion of B cells. The Exploratory Phase II/III SLE Evaluation of Rituximab (EXPLORER) trial tested the efficacy and safety of rituximab versus placebo in patients with moderately-to-severely active extrarenal SLE. Methods Patients entered with ≥1 British Isles Lupus Assessment Group (BILAG) A score or ≥2 BILAG B scores despite background immunosuppressant therapy, which was continued during the trial. Prednisone was added and subsequently tapered. Patients were randomized at a ratio of 2:1 to receive rituximab (1,000 mg) or placebo on days 1, 15, 168, and 182. Results In the intent-to-treat analysis of 257 patients, background treatment was evenly distributed among azathioprine, mycophenolate mofetil, and methotrexate. Fifty-three percent of the patients had ≥1 BILAG A score at entry, and 57% of the patients were categorized as being steroid dependent. No differences were observed between placebo and rituximab in the primary and secondary efficacy end points, including the BILAG-defined response, in terms of both area under the curve and landmark analyses. A beneficial effect of rituximab on the primary end point was observed in the African American and Hispanic subgroups. Safety and tolerability were similar in patients receiving placebo and those receiving rituximab. Conclusion The EXPLORER trial enrolled patients with moderately-to-severely active SLE and used aggressive background treatment and sensitive cutoffs for nonresponse. No differences were noted between placebo and rituximab in the primary and secondary end points. Further evaluation of patient subsets, biomarkers, and exploratory outcome models may improve the design of future SLE clinical trials.

DNA N(6)-methyladenine (6mA) modification is commonly found in microbial genomes and plays important functions in regulating numerous biological processes in bacteria. However, whether 6mA occurs and what its potential roles are in higher-eukaryote cells remain unknown. Here, we show that 6mA is present in Drosophila genome and that the 6mA modification is dynamic and is regulated by the Drosophila Tet homolog, DNA 6mA demethylase (DMAD), during embryogenesis. Importantly, our biochemical assays demonstrate that DMAD directly catalyzes 6mA demethylation in vitro. Further genetic and sequencing analyses reveal that DMAD is essential for development and that DMAD removes 6mA primarily from transposon regions, which correlates with transposon suppression in Drosophila ovary. Collectively, we uncover a DNA modification in Drosophila and describe a potential role of the DMAD-6mA regulatory axis in controlling development in higher eukaryotes.

Sparse representation based classification has led to interesting image recognition results, while the dictionary used for sparse coding plays a key role in it. This paper presents a novel dictionary learning (DL) method to improve the pattern classification performance. Based on the Fisher discrimination criterion, a structured dictionary, whose dictionary atoms have correspondence to the class labels, is learned so that the reconstruction error after sparse coding can be used for pattern classification. Meanwhile, the Fisher discrimination criterion is imposed on the coding coefficients so that they have small within-class scatter but big between-class scatter. A new classification scheme associated with the proposed Fisher discrimination DL (FDDL) method is then presented by IntroductionThe past several years have witnessed the rapid development of the theory and algorithms of sparse representation (or coding) [30] and its successful applications in image restoration [1][2][3] and compressed sensing [4]. Recently sparse representation techniques have also led to promising results in image classification, e.g. face recognition (FR) [5-7, 10, 31], digit and texture classification [8][9][11][12], etc. The success of sparse representation based classification owes to the fact that a high-dimensional image can be represented or coded by a few representative samples from the same class in a low-dimensional manifold, and the recent progress of l 0 -norm and l 1 -norm minimization techniques [28].In sparse representation based classification, there are two phases: coding and classification. First, the query signal/image is collaboratively coded over a dictionary of atoms with some sparsity constraint, and then classification is performed based on the coding coefficients and the dictionary. The dictionary for sparse coding could be predefined. For example, Wright et al. [5] directly used the training samples of all classes as the dictionary to code the query face image, and classified the query face image by evaluating which class leads to the minimal reconstruction error. Although this so called sparse representation based classification (SRC) scheme shows interesting FR results, the dictionary used in it may not be effective enough to represent the query images due to the uncertain and noisy information in the original training images. The number of atoms of such a dictionary can also be very big, which increases the coding complexity. In addition, using the original training samples as the dictionary could not fully exploit the discriminative information hidden in the training samples. On the other hand, using analytically designed off-the-shelf bases as dictionary (e.g., [8] uses Haar wavelets and Gabor wavelets as the dictionary) might be universal to all types of images but will not be effective enough for specific type of images such as face, digit and texture images. In fact, all the above mentioned problems of predefined dictionary can be addressed, at least to some extent, by learning properly a non...