Small RNA-Dependent Gene Silencing in the Green Alga \u3ci\u3eChlamydomonas reinhardtii\u3c/i\u3e: Functions and Mechanisms

Small RNAs (sRNAs), ~20-30 nucleotides in length, are non-coding RNAs that play essential roles in the regulation of gene expression in eukaryotes. They lead to inactivation of cognate sequences at the post-transcriptional level via a variety of mechanisms involved in translation inhibition and/or RNA degradation. In the Chlorophyta Chlamydomonas reinhardtii, however, the molecular machinery responsible for sRNA-mediated translational repression remains unclear. To address the mechanisms of translation inhibition by sRNA, we have isolated an RNAi defective mutant (Mut26), which contains a deletion of the gene encoding the homolog of CCR4 in Chlamydomonas. We investigated the expression of both an exogenous siRNA target and endogenous miRNA target. Additionally, the pattern of poly(A) tailing in diagnostic mRNAs was examined with the G/I tailing assay and CCR4 partner proteins were identified through affinity purification. Our overall results are consistent with the role of CCR4 in sRNA-dependent translational repression without target mRNA degradation in Chlamydomonas. The biological function(s) of miRNAs in responses to nutrient deprivation in Chlamydomonas reinhardtii were also explored. Transcriptome analysis using cells grown under various trophic conditions revealed that several miRNAs were differentially expressed, but their predicted targets showed no changes in transcript abundance. Collective evidence suggests that miRNAs may not play an essential role in endogenous gene regulation in Chlamydomonas. Advisor: Heriberto Cerutt

Finding branch-decompositions of matroids, hypergraphs, and more

Given $n$ subspaces of a finite-dimensional vector space over a fixed finite field $\mathcal F$, we wish to find a "branch-decomposition" of these subspaces of width at most $k$, that is a subcubic tree $T$ with $n$ leaves mapped bijectively to the subspaces such that for every edge $e$ of $T$, the sum of subspaces associated with leaves in one component of $T-e$ and the sum of subspaces associated with leaves in the other component have the intersection of dimension at most $k$. This problem includes the problems of computing branch-width of $\mathcal F$-represented matroids, rank-width of graphs, branch-width of hypergraphs, and carving-width of graphs. We present a fixed-parameter algorithm to construct such a branch-decomposition of width at most $k$, if it exists, for input subspaces of a finite-dimensional vector space over $\mathcal F$. Our algorithm is analogous to the algorithm of Bodlaender and Kloks (1996) on tree-width of graphs. To extend their framework to branch-decompositions of vector spaces, we developed highly generic tools for branch-decompositions on vector spaces. The only known previous fixed-parameter algorithm for branch-width of $\mathcal F$-represented matroids was due to Hlin\v{e}n\'y and Oum (2008) that runs in time $O(n^3)$ where $n$ is the number of elements of the input $\mathcal F$-represented matroid. But their method is highly indirect. Their algorithm uses the non-trivial fact by Geelen et al. (2003) that the number of forbidden minors is finite and uses the algorithm of Hlin\v{e}n\'y (2005) on checking monadic second-order formulas on $\mathcal F$-represented matroids of small branch-width. Our result does not depend on such a fact and is completely self-contained, and yet matches their asymptotic running time for each fixed $k$.Comment: 73 pages, 10 figure

Topology of Luminous Red Galaxies from the Sloan Digital Sky Survey

We present measurements of the genus topology of luminous red galaxies (LRGs) from the Sloan Digital Sky Survey (SDSS) Data Release 7 catalog, with unprecedented statistical significance. To estimate the uncertainties in the measured genus, we construct 81 mock SDSS LRG surveys along the past light cone from the Horizon Run 3, one of the largest N-body simulations to date that evolved 7210^3 particles in a 10815 Mpc/h size box. After carefully modeling and removing all known systematic effects due to finite pixel size, survey boundary, radial and angular selection functions, shot noise and galaxy biasing, we find the observed genus amplitude to reach 272 at 22 Mpc/h smoothing scale with an uncertainty of 4.2%; the estimated error fully incorporates cosmic variance. This is the most accurate constraint of the genus amplitude to date, which significantly improves on our previous results. In particular, the shape of the genus curve agrees very well with the mean topology of the SDSS LRG mock surveys in the LCDM universe. However, comparison with simulations also shows small deviations of the observed genus curve from the theoretical expectation for Gaussian initial conditions. While these discrepancies are mainly driven by known systematic effects such as those of shot noise and redshift-space distortions, they do contain important cosmological information on the physical effects connected with galaxy formation, gravitational evolution and primordial non-Gaussianity. We address here the key role played by systematics on the genus curve, and show how to accurately correct for their effects to recover the topology of the underlying matter. In a forthcoming paper, we provide an interpretation of those deviations in the context of the local model of non-Gaussianity.Comment: 23 pages, 18 figures. APJ Supplement Series 201

Apigenin Induces Apoptosis through a Mitochondria/Caspase-Pathway in Human Breast Cancer MDA-MB-453 Cells

In this study, we investigated the mechanistic role of the caspase cascade in extrinsic and intrinsic apoptosis induced by apigenin, which has been targeted as a candidate in the development of noncytotoxic anticancer medicines. Treatment with apigenin (1–100 µM) significantly inhibited the proliferation of MDA-MB-453 human breast cancer cells in a dose- and time-dependent manner with IC50 values of 59.44 and 35.15 µM at 24 and 72 h, respectively. This inhibition resulted in the induction of apoptosis and the release of cytochrome c in cells exposed to apigenin at its 72 h IC50. Subsequently, caspase-9, which acts in mitochondria-mediated apoptosis, was cleaved by apigenin. In addition, apigenin activated caspase-3, which functions downstream of caspase-9. The apigenin-induced activation of caspase-3 was accompanied by the cleavage of capases-6, -7, and -8. These results are supported by evidence showing that the activity patterns of caspases-3, -8, and -9 were similar. The present study supports the hypothesis that apigenin-induced apoptosis involves the activation of both the intrinsic and extrinsic apoptotic pathways

OPTIMAL REGRESSION MODEL FOR PREDICTING THE WINNING GAME AND CONTRIBUTING FACTORS IN ICE HOCKEY WORLD CHAMPIONSHIP

The purpose of this study was to present the statistical model to predict the winning of ice hockey game and determine the contributing factors for win in the world ice hockey championship. In order to find the optimal regression model for ice hockey, we compared two regression model (logistic and linear model) with the database of all games and the separate databases of top/bottom teams. The logistic regression model using the separate database was most accurately predicted the actual outcome of games. This model and database further revealed that goalkeeping and scoring efficiencies and the number of shots on goal were significantly contributing factors to win. In addition, the results for prediction analysis of winning rate for each team indicated that offensive skills were more important factors than defense power to increase winning rate for teams