Regulation of MBK-2/DYRK by CDK-1 and the Pseudophosphatases EGG-4 and EGG-5 during the Oocyte-to-Embryo Transition

SummaryDYRKs are kinases that self-activate in vitro by autophosphorylation of a YTY motif in the kinase domain, but their regulation in vivo is not well understood. In C. elegans zygotes, MBK-2/DYRK phosphorylates oocyte proteins at the end of the meiotic divisions to promote the oocyte-to-embryo transition. Here we demonstrate that MBK-2 is under both positive and negative regulation during the transition. MBK-2 is activated during oocyte maturation by CDK-1-dependent phosphorylation of serine 68, a residue outside of the kinase domain required for full activity in vivo. The pseudotyrosine phosphatases EGG-4 and EGG-5 sequester activated MBK-2 until the meiotic divisions by binding to the YTY motif and inhibiting MBK-2′s kinase activity directly, using a mixed-inhibition mechanism that does not involve tyrosine dephosphorylation. Our findings link cell-cycle progression to MBK-2/DYRK activation and the oocyte-to-embryo transition

Lowly Expressed Ribosomal Protein S19 in the Feces of Patients with Colorectal Cancer

Colorectal cancer (CRC) has become one of the most common fatal cancers. CRC tumorigenesis is a complex process involving multiple genetic changes to several sequential mutations or molecular alterations. P53 is one of the most significant genes; its mutations account for more than half of all CRC. Therefore, understanding the cellular genes that are directly or indirectly related to p53 is particularly crucial for investigating CRC tumorigenesis. In this study, a p53-related ribosomal protein, ribosomal protein S19 (RPS19), obtained from the feces of CRC patients is evaluated by using specifically quantitative real-time PCR and knocked down in the colonic cell line by gene silencing. This study found that CRC patients with higher expressions of RPS19 in their feces had a better prognosis and consistent expressions of RPS19 and BAX in their colonic cells. In conclusion, the potential mechanism of RPS19 in CRC possibly involves cellular apoptosis through the BAX/p53 pathway, and the levels of fecal RPS19 may function as a prognostic predictor for CRC patients

Evolution of electronic and magnetic properties of Sr2\mathbf{_2}IrO4\mathbf{_4} under strain

Motivated by properties-controlling potential of the strain, we investigate strain dependence of structure, electronic and magnetic properties of Sr$_2$IrO$_4$ using complementary theoretical tools: {\it ab-initio} calculations, analytical approaches (rigid octahedra picture, Slater-Koster integrals), and extended $t-{\mathcal{J}}$ model. We find that strain affects both Ir-Ir distance and Ir-O-Ir angle, and the rigid octahedra picture is not relevant. Second, we find fundamentally different behavior for compressive and tensile strain. One remarkable feature is the formation of two subsets of bond- and orbital- dependent carriers, a compass-like model, under compression. This originates from the strain-induced renormalization of the Ir-O-Ir superexchange and O on-site energy. We also show that under compressive (tensile) strain, Fermi surface becomes highly dispersive (relatively flat). Already at a tensile strain of $1.5\%$, we observe spectral weight redistribution, with the low-energy band acquiring almost purely singlet character. These results can be directly compared with future experiments.Comment: 28 pages, 6 figures, includes Supplemental Informatio

The heterojunction effects of TiO2 nanotubes fabricated by atomic layer deposition on photocarrier transportation direction

The heterojunction effects of TiO2 nanotubes on photoconductive characteristics were investigated. For ITO/TiO2/Si diodes, the photocurrent is controlled either by the TiO2/Si heterojunction (p-n junction) or the ITO-TiO2 heterojunction (Schottky contact). In the short circuit (approximately 0 V) condition, the TiO2-Si heterojunction dominates the photocarrier transportation direction due to its larger space-charge region and potential gradient. The detailed transition process of the photocarrier direction was investigated with a time-dependent photoresponse study. The results showed that the diode transitioned from TiO2-Si heterojunction-controlled to ITO-TiO2 heterojunction-controlled as we applied biases from approximately 0 to -1 V on the ITO electrode

Publisher Correction: Evolution of electronic and magnetic properties of Sr2IrO4 under strain

In the original version of this Article, all the figures (together with the captions) are inadvertently misplaced. Figures 1, 2, 3, 4, 5, 6 and 7 were wrongly placed in the positions of Figures 7, 1, 2, 3, 4, 5 and 6, respectively. This has been corrected in both the PDF and HTML versions of the Article

Mining association language patterns using a distributional semantic model for negative life event classification

AbstractPurposeNegative life events, such as the death of a family member, an argument with a spouse or the loss of a job, play an important role in triggering depressive episodes. Therefore, it is worthwhile to develop psychiatric services that can automatically identify such events. This study describes the use of association language patterns, i.e., meaningful combinations of words (e.g., <loss, job>), as features to classify sentences with negative life events into predefined categories (e.g., Family, Love, Work).MethodsThis study proposes a framework that combines a supervised data mining algorithm and an unsupervised distributional semantic model to discover association language patterns. The data mining algorithm, called association rule mining, was used to generate a set of seed patterns by incrementally associating frequently co-occurring words from a small corpus of sentences labeled with negative life events. The distributional semantic model was then used to discover more patterns similar to the seed patterns from a large, unlabeled web corpus.ResultsThe experimental results showed that association language patterns were significant features for negative life event classification. Additionally, the unsupervised distributional semantic model was not only able to improve the level of performance but also to reduce the reliance of the classification process on the availability of a large, labeled corpus