NOD2/RICK-dependent β-defensin 2 regulation is protective for nontypeable Haemophilus influenzae-induced middle ear infection.

Middle ear infection, otitis media (OM), is clinically important due to the high incidence in children and its impact on the development of language and motor coordination. Previously, we have demonstrated that the human middle ear epithelial cells up-regulate β-defensin 2, a model innate immune molecule, in response to nontypeable Haemophilus influenzae (NTHi), the most common OM pathogen, via TLR2 signaling. NTHi does internalize into the epithelial cells, but its intracellular trafficking and host responses to the internalized NTHi are poorly understood. Here we aimed to determine a role of cytoplasmic pathogen recognition receptors in NTHi-induced β-defensin 2 regulation and NTHi clearance from the middle ear. Notably, we observed that the internalized NTHi is able to exist freely in the cytoplasm of the human epithelial cells after rupturing the surrounding membrane. The human middle ear epithelial cells inhibited NTHi-induced β-defensin 2 production by NOD2 silencing but augmented it by NOD2 over-expression. NTHi-induced β-defensin 2 up-regulation was attenuated by cytochalasin D, an inhibitor of actin polymerization and was enhanced by α-hemolysin, a pore-forming toxin. NOD2 silencing was found to block α-hemolysin-mediated enhancement of NTHi-induced β-defensin 2 up-regulation. NOD2 deficiency appeared to reduce inflammatory reactions in response to intratympanic inoculation of NTHi and inhibit NTHi clearance from the middle ear. Taken together, our findings suggest that a cytoplasmic release of internalized NTHi is involved in the pathogenesis of NTHi infections, and NOD2-mediated β-defensin 2 regulation contributes to the protection against NTHi-induced otitis media

Physical characterization of amorphous In-Ga-Zn-O thin-film transistors with direct-contact asymmetric graphene electrode

High performance a-IGZO thin-film transistors (TFTs) are fabricated using an asymmetric graphene drain electrode structure. A-IGZO TFTs (channel length = 3 μm) were successfully demonstrated with a saturation field-effect mobility of 6.6 cm2/Vs without additional processes between the graphene and a-IGZO layer. The graphene/a-IGZO junction exhibits Schottky characteristics and the contact property is affected not only by the Schottky barrier but also by the parasitic resistance from the depletion region under the graphene electrode. Therefore, to utilize the graphene layer as S/D electrodes for a-IGZO TFTs, an asymmetric electrode is essential, which can be easily applied to the conventional pixel electrode structure. © 2014 Author(s).1

Geometrically Aligned Transfer Encoder for Inductive Transfer in Regression Tasks

Transfer learning is a crucial technique for handling a small amount of data that is potentially related to other abundant data. However, most of the existing methods are focused on classification tasks using images and language datasets. Therefore, in order to expand the transfer learning scheme to regression tasks, we propose a novel transfer technique based on differential geometry, namely the Geometrically Aligned Transfer Encoder (GATE). In this method, we interpret the latent vectors from the model to exist on a Riemannian curved manifold. We find a proper diffeomorphism between pairs of tasks to ensure that every arbitrary point maps to a locally flat coordinate in the overlapping region, allowing the transfer of knowledge from the source to the target data. This also serves as an effective regularizer for the model to behave in extrapolation regions. In this article, we demonstrate that GATE outperforms conventional methods and exhibits stable behavior in both the latent space and extrapolation regions for various molecular graph datasets.Comment: 12+11 pages, 6+1 figures, 0+7 table

The Distribution Strategy Of A Representative Fair Trade Organization In Korea: The Case Of Beautiful Coffee

This case study analyzes the distribution strategy of Beautiful Coffee, a leading fair trade organization in Korea. Because of their focus on matters of public interest, fair trade organizations often face financial difficulties, and such difficulties can limit their growth and force them to pursue differentiated distribution strategies. The results indicate that Beautiful Coffee can serve as a good role model for fair trade organizations and have important practical implications for firms pursuing sustainable growth as a social enterprise

Bioinspired reversible hydrogel adhesives for wet and underwater surfaces

Stable and reversible adhesion to wet surfaces is challenging owing to water molecules at the contact interface. In this study, we develop a hydrogel-based wet adhesive, which can exhibit strong and reversible adhesion to wet and underwater surfaces as well as to dry surfaces. The remarkable wet adhesion of the hydrogel adhesive is realized based on a synergetic integration of bioinspired microarchitectures and water-friendly and water-absorbing properties of the polymeric hydrogel. Under dry conditions, the microstructured hydrogel adhesive exhibits strong van der Waals interaction-based adhesion, while under underwater conditions, it can maximize capillary adhesion. Consequently, the hydrogel adhesive exhibits remarkable adhesion strengths for dry, moist, and submerged substrates. Maximum normal and shear adhesion strengths of 423 and 384, 492 and 340, and 253 and 21 kPa are achieved with the hydrogel adhesive for dry, moist, and submerged substrates, respectively. Our results demonstrate that strong wet and underwater adhesion can be achieved only with the hydrogel-based adhesive with simple microscale architecture

Grouping-matrix based Graph Pooling with Adaptive Number of Clusters

Graph pooling is a crucial operation for encoding hierarchical structures within graphs. Most existing graph pooling approaches formulate the problem as a node clustering task which effectively captures the graph topology. Conventional methods ask users to specify an appropriate number of clusters as a hyperparameter, then assume that all input graphs share the same number of clusters. In inductive settings where the number of clusters can vary, however, the model should be able to represent this variation in its pooling layers in order to learn suitable clusters. Thus we propose GMPool, a novel differentiable graph pooling architecture that automatically determines the appropriate number of clusters based on the input data. The main intuition involves a grouping matrix defined as a quadratic form of the pooling operator, which induces use of binary classification probabilities of pairwise combinations of nodes. GMPool obtains the pooling operator by first computing the grouping matrix, then decomposing it. Extensive evaluations on molecular property prediction tasks demonstrate that our method outperforms conventional methods.Comment: 10 pages, 3 figure

Flexible and Shape-Reconfigurable Hydrogel Interlocking Adhesives for High Adhesion in Wet Environments Based on Anisotropic Swelling of Hydrogel Microstructures

This study presents wet-responsive, shape-reconfigurable, and flexible hydrogel adhesives that exhibit strong adhesion under wet environments based on reversible interlocking between reconfigurable microhook arrays. The experimental investigation on the swelling behavior and structural characterization of the hydrogel microstructures reveal that the microhook arrays undergo anisotropic swelling and shape transformation upon contact with water. The adhesion between the interlocked microhook arrays is greatly enhanced under wet conditions because of the hydration-triggered shape reconfiguration of the hydrogel microstructures. Furthermore, wet adhesion monotonically increases with water-exposure time. A maximum adhesion force of 79.9 N cm-2 in the shear direction is obtained with the hydrogel microhook array after 20 h of swelling, which is 732.3% greater than that under dry conditions (i.e., 9.6 N cm-2). A simple theoretical model is developed to describe the measured adhesion forces. The results are in good agreement with the experimental data

Characteristics of the Korean stock market correlations

In this study, we establish a network structure of the Korean stock market, one of the emerging markets, with its minimum spanning tree through the correlation matrix. Base on this analysis, it is found that the Korean stock market doesn't form the clusters of the business sectors or of the industry categories. When the MSCI (Morgan Stanley Capital International Inc.) index is exploited, we found that the clusters of the Korean stock market is formed. This finding implicates that the Korean market, in this context, is characteristically different form the mature markets.Comment: 11 pages, 3 figures, revised on June 200