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

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

Change in gene expression of mouse embryonic stem cells derived from parthenogenetic activation

BACKGROUND We previously established parthenogenetic mouse embryonic stem cells (ESCs) and this study was subsequently conducted for elucidating the influence of oocyte parthenogenesis on gene expression profile of ESCs. METHODS Gene expression of parthenogenetic ESC (pESC)-1 or pESC-2 was separately compared with that of two normally fertilized ESC (nfESC) lines (B6D2F1 and R1 strains), and quantification of mRNA expression was conducted for validating microarray data. RESULTS In two sets of comparison, reaction of 11 347 and 15 454 gene probes were altered by parthenogenesis, while strain difference changed the expression of 15 750 and 14 944 probes. Level of correlation coefficient was higher in the comparisons between normal fertilization and parthenogenesis (0.974-0.985) than in the comparisons between strains of nfESCs (0.97-0.971). Overall, the expression of 3276-3329 genes was changed after parthenogenesis, and 88% (96/109) of major functional genes differentially (P < 0.01) expressed in one comparison set showed the same change in the other. When we monitored imprinted genes, expression of nine paternal and eight maternal genes were altered after parthenogenesis and 88% (14/16) of these was confirmed by mRNA quantification. CONCLUSIONS The change in gene expression after parthenogenesis was similar to, or less than, the change induced by a strain difference under a certain genetic background. These results may suggest the clinical feasibility of parthenogenesis-derived, pluripotent cell

A set of stage-specific gene transcripts identified in EK stage X and HH stage 3 chick embryos

<p>Abstract</p> <p>Background</p> <p>The embryonic developmental process in avian species is quite different from that in mammals. The first cleavage begins 4 h after fertilization, but the first differentiation does not occur until laying of the egg (Eyal-Giladi and Kochav (EK) stage X). After 12 to 13 h of incubation (Hamburger and Hamilton (HH) stage 3), the three germ layers form and germ cell segregation in the early chick embryo are completed. Thus, to identify genes associated with early embryonic development, we compared transcript expression patterns between undifferentiated (stage X) and differentiated (HH stage 3) embryos.</p> <p>Results</p> <p>Microarray analysis primarily showed 40 genes indicating the significant changes in expression levels between stage X and HH stage 3, and 80% of the genes (32/40) were differentially expressed with more than a twofold change. Among those, 72% (23/32) were relatively up-regulated at stage X compared to HH stage 3, while 28% (9/32) were relatively up-regulated at HH stage 3 compared to stage X. Verification and gene expression profiling of these GeneChip expression data were performed using quantitative RT-PCR for 32 genes at developmental four points; stage X (0 h), HH stage 3 (12 h), HH stage 6 (24 h), and HH stage 9 (30 h). Additionally, we further analyzed four genes with less than twofold expression increase at HH stage 3. As a result, we identified a set of stage-specific genes during the early chick embryo development; 21 genes were relatively up-regulated in the stage X embryo and 12 genes were relatively up-regulated in the HH stage 3 embryo based on both results of microarray and quantitative RT-PCR.</p> <p>Conclusion</p> <p>We identified a set of genes with stage-specific expression from microarray Genechip and quantitative RT-PCR. Discovering stage-specific genes will aid in uncovering the molecular mechanisms involved the formation of the three germ layers and germ cell segregation in the early chick embryos.</p

The Occurrence and Speed of CMEs Related to Two Characteristic Evolution Patterns of Helicity Injection in Their Solar Source Regions

Long-term (a few days) variation of magnetic helicity injection was calculated for 28 solar active regions which produced 47 CMEs to find its relationships with the CME occurrence and speed using SOHO/MDI line-of-sight magnetograms. As a result, we found that the 47 CMEs can be categorized into two different groups by two characteristic evolution patterns of helicity injection in their source active regions which appeared for about 0.5-4.5 days before their occurrence: (1) a monotonically increasing pattern with one sign of helicity (Group A; 30 CMEs in 23 active regions) and (2) a pattern of significant helicity injection followed by its sign reversal (Group B; 17 CMEs in 5 active regions). We also found that CME speed has a correlation with average helicity injection rate with linear correlation coefficients of 0.85 and 0.63 for Group A and Group B, respectively. In addition, these two CME groups show different characteristics as follows: (1) the average CME speed of Group B (1330km/s) is much faster than that of Group A (870km/s), (2) the CMEs in Group A tend to be single events, whereas those in Group B mainly consist of successive events, and (3) flares related to the CMEs in Group B are relatively more energetic and impulsive than those in Group A. Our findings therefore suggest that the two CME groups have different pre-CME conditions in their source active regions and different CME characteristics.Comment: 25 pages, 7 figures, accepted for publication in Ap