Transforming growth factor-beta promotes rhinovirus replication in bronchial epithelial cells by suppressing the innate immune response

Rhinovirus (RV) infection is a major cause of asthma exacerbations which may be due to a deficient innate immune response in the bronchial epithelium. We hypothesized that the pleiotropic cytokine, TGF-?, influences interferon (IFN) production by primary bronchial epithelial cells (PBECs) following RV infection. Exogenous TGF-?(2) increased RV replication and decreased IFN protein secretion in response to RV or double-stranded RNA (dsRNA). Conversely, neutralizing TGF-? antibodies decreased RV replication and increased IFN expression in response to RV or dsRNA. Endogenous TGF-?(2) levels were higher in conditioned media of PBECs from asthmatic donors and the suppressive effect of anti-TGF-? on RV replication was significantly greater in these cells. Basal SMAD-2 activation was reduced when asthmatic PBECs were treated with anti-TGF-? and this was accompanied by suppression of SOCS-1 and SOCS-3 expression. Our results suggest that endogenous TGF-? contributes to a suppressed IFN response to RV infection possibly via SOCS-1 and SOCS-3

(E)-Benzo­yl[1-(2-hydroxy­ethyl)imidazolidin-2-yl­idene]acetonitrile

In the title compound, C14H15N3O2, the C=C(H)—C=O grouping and the imidazolidine ring are coplanar as a result of an intra­molecular N—H⋯O hydrogen bond and extended electronic conjugation. Inter­molecular N—H⋯O and O—H⋯N hydrogen bonds help to establish the packing

Combining multiple classifications of chemical structures using consensus clustering

Consensus clustering involves combining multiple clusterings of the same set of objects to achieve a single clustering that will, hopefully, provide a better picture of the groupings that are present in a dataset. This Letter reports the use of consensus clustering methods on sets of chemical compounds represented by 2D fingerprints. Experiments with DUD, IDAlert, MDDR and MUV data suggests that consensus methods are unlikely to result in significant improvements in clustering effectiveness as compared to the use of a single clustering method. (C) 2012 Elsevier Ltd. All rights reserved

Comparison of Test Your Memory and Montreal Cognitive Assessment Measures in Parkinson’s Disease

Background. MoCA is widely used in Parkinson’s disease (PD) to assess cognition. The Test Your Memory (TYM) test is a cognitive screening tool that is self-administered. Objectives. We sought to determine (a) the optimal value of TYM to discriminate between PD patients with and without cognitive deficits on MoCA testing, (b) equivalent MoCA and TYM scores, and (c) interrater reliability in TYM testing. Methods. We assessed the discriminant ability of TYM and the equivalence between TYM and MoCA scores and measured the interrater reliability between three raters. Results. Of the 135 subjects that completed both tests, 55% had cognitive impairment according to MoCA. A MoCA score of 25 was equivalent to a TYM score of 43-44. The area under the receiver operator characteristic (ROC) curve for TYM to differentiate between PD-normal and PD-cognitive impairment was 0.82 (95% CI 0.75 to 0.89). The optimal cutoff to distinguish PD-cognitive impairment from PD-normal was ≤45 (sensitivity 90.5%, specificity 59%) thereby correctly classifying 76.3% of patients with PD-cognitive impairment. Interrater agreement was high (0.97) and TYM was completed in under 7 minutes (interquartile range 5.33 to 8.52 minutes). Conclusions. The TYM test is a useful and less resource intensive screening test for cognitive deficits in PD

On the Geometric Interpretation of the Nonnegative Rank

The nonnegative rank of a nonnegative matrix is the minimum number of nonnegative rank-one factors needed to reconstruct it exactly. The problem of determining this rank and computing the corresponding nonnegative factors is difficult; however it has many potential applications, e.g., in data mining, graph theory and computational geometry. In particular, it can be used to characterize the minimal size of any extended reformulation of a given combinatorial optimization program. In this paper, we introduce and study a related quantity, called the restricted nonnegative rank. We show that computing this quantity is equivalent to a problem in polyhedral combinatorics, and fully characterize its computational complexity. This in turn sheds new light on the nonnegative rank problem, and in particular allows us to provide new improved lower bounds based on its geometric interpretation. We apply these results to slack matrices and linear Euclidean distance matrices and obtain counter-examples to two conjectures of Beasly and Laffey, namely we show that the nonnegative rank of linear Euclidean distance matrices is not necessarily equal to their dimension, and that the rank of a matrix is not always greater than the nonnegative rank of its square

T-duality with H-flux: non-commutativity, T-folds and G x G structure

Various approaches to T-duality with NSNS three-form flux are reconciled. Non-commutative torus fibrations are shown to be the open-string version of T-folds. The non-geometric T-dual of a three-torus with uniform flux is embedded into a generalized complex six-torus, and the non-geometry is probed by D0-branes regarded as generalized complex submanifolds. The non-commutativity scale, which is present in these compactifications, is given by a holomorphic Poisson bivector that also encodes the variation of the dimension of the world-volume of D-branes under monodromy. This bivector is shown to exist in SU(3) x SU(3) structure compactifications, which have been proposed as mirrors to NSNS-flux backgrounds. The two SU(3)-invariant spinors are generically not parallel, thereby giving rise to a non-trivial Poisson bivector. Furthermore we show that for non-geometric T-duals, the Poisson bivector may not be decomposable into the tensor product of vectors.Comment: 25 pages, LaTeX; v2: typos corrected, references adde