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Cardamonin, the chalcone class, is one of the natural components from the spicy herbaceous plant (Alpinia conchigera Griff) and has anticancer activities in many human cancer cell lines. There is, however, no information to show that cardamonin induces cell apoptosis and alters apoptosis associated gene expressions in mouse leukemia cells. Thus, we investigated the effects of cardamonin on the apoptotic cell death and associated gene expression in mouse leukemia WEHI-3 cells in vitro. Results indicated that cardamonin decreased total viable cell number via induced cell morphological changes and apoptotic cell death in WEHI-3 cells that were assay by contrast-phase microscopy and flow cytometry examinations, respectively. The flow cytometry assay indicated that cardamonin increased reactive oxygen species (ROS) and Ca${}^{2+}$ production, decreased the levels of mitochondrial membrane potential ($\mathrm{\Delta }{\mathrm{\Psi }}_m)$ and increased caspase-3, -8 and -9 activities in WEHI-3 cells. Western blotting was performed to analyze expression of relevant pro- and anti-apoptotic proteins and results showed that cardamonin decreased anti-apoptotic protein of Bcl-2 but increased pro-apoptotic protein of Bax in WEHI-3 cells. Furthermore, cardamonin increased cytochrome c, AIF and Endo G release, increased GRP78, caspase-12 that were associated with ER stress and increased Fas, Fas-Ligand and FADD expression. Furthermore, cardamonin increased the gene expressions of DAP (death-associated protein), TMBIM4 transmembrane (BAX inhibitor motif containing 4), ATG5 (autophagy related 5) but decreased the gene expression of DDIT3 (DNA-damage inducible transcript 3), DDIT4 (DNA-damage-inducible transcript 4), BAG6 (BCL2-associated athanogene 6), BCL2L13 [BCL2-like 13 (apoptosis facilitator)] and BRAT1 (BRCA1-associated ATM activator 1) that are associated with apoptosis pathways. Based on those findings, we may suggest cardamonin induced apoptotic cell death through Fas and Fas-Ligand-, caspase- and mitochondria-dependently pathways and also affects the apoptotic gene expression in WEHI-3 cells in vitro.

The article is about the Rice Genome Microarray Project, DNA probes for the microarray analysis and the rice full-length cDNA project and the activities of the microarray center.

The article is a summary of the research done in GIS. It touches on the focus on systems and integrative biology and GIS's efforts in collaborating with international organizations.

In the process of making full-length cDNA, predicting protein coding regions helps both in the preliminary analysis of genes and in any succeeding process. However, unfinished cDNA contains artifacts including many sequencing errors, which hinder the correct evaluation of coding sequences. Especially, predictions of short sequences are difficult because they provide little information for evaluating coding potential. In this paper, we describe ANGLE, a new program for predicting coding sequences in low quality cDNA. To achieve error-tolerant prediction, ANGLE uses a machine-learning approach, which makes better expression of coding sequence maximizing the use of limited information from input sequences. Our method utilizes not only codon usage, but also protein structure information which is difficult to be used for stochastic model-based algorithms, and optimizes limited information from a short segment when deciding coding potential, with the result that predictive accuracy does not depend on the length of an input sequence. The performance of ANGLE is compared with ESTSCAN on four dataset each of them having a different error rate (one frame-shift error or one substitution error per 200–500 nucleotides) and on one dataset which has no error. ANGLE outperforms ESTSCAN by 9.26% in average Matthews's correlation coefficient on short sequence dataset (< 1000 bases). On long sequence dataset, ANGLE achieves comparable performance.