Mutations in Mtr4 Structural Domains Reveal Their Important Role in Regulating tRNA\u3csub\u3ei\u3c/sub\u3e \u3csup\u3eMet\u3c/sup\u3e Turnover in \u3cem\u3eSaccharomyces cerevisiae\u3c/em\u3e and Mtr4p Enzymatic Activities \u3cem\u3eIn Vitro\u3c/em\u3e

RNA processing and turnover play important roles in the maturation, metabolism and quality control of a large variety of RNAs thereby contributing to gene expression and cellular health. The TRAMP complex, composed of Air2p, Trf4p and Mtr4p, stimulates nuclear exosome-dependent RNA processing and degradation in Saccharomyces cerevisiae. The Mtr4 protein structure is composed of a helicase core and a novel so-called arch domain, which protrudes from the core. The helicase core contains highly conserved helicase domains RecA-1 and 2, and two structural domains of unclear functions, winged helix domain (WH) and ratchet domain. How the structural domains (arch, WH and ratchet domain) coordinate with the helicase domains and what roles they are playing in regulating Mtr4p helicase activity are unknown. We created a library of Mtr4p structural domain mutants for the first time and screened for those defective in the turnover of TRAMP and exosome substrate, hypomodified tRNAiMet. We found these domains regulate Mtr4p enzymatic activities differently through characterizing the arch domain mutants K700N and P731S, WH mutant K904N, and ratchet domain mutant R1030G. Arch domain mutants greatly reduced Mtr4p RNA binding, which surprisingly did not lead to significant defects on either in vivo tRNAiMet turnover, or in vitro unwinding activities. WH mutant K904N and Ratchet domain mutant R1030G showed decreased tRNAiMet turnover in vivo, as well as reduced RNA binding, ATPase and unwinding activities of Mtr4p in vitro. Particularly, K904 was found to be very important for steady protein levels in vivo. Overall, we conclude that arch domain plays a role in RNA binding but is largely dispensable for Mtr4p enzymatic activities, however the structural domains in the helicase core significantly contribute to Mtr4p ATPase and unwinding activities

Estimation of Models in a Rasch Family for Polytomous Items and Multiple Latent Variables

The Rasch family of models considered in this paper includes models for polytomous items and multiple correlated latent traits, as well as for dichotomous items and a single latent variable. An R package is described that computes estimates of parameters and robust standard errors of a class of log-linear-by-linear association (LLLA) models, which are derived from a Rasch family of models. The LLLA models are special cases of log-linear models with bivariate interactions. Maximum likelihood estimation of LLLA models in this form is limited to relatively small problems; however, pseudo-likelihood estimation overcomes this limitation. Maximizing the pseudo-likelihood function is achieved by maximizing the likelihood of a single conditional multinomial logistic regression model. The parameter estimates are asymptotically normal and consistent. Based on our simulation studies, the pseudo-likelihood and maximum likelihood estimates of the parameters of LLLA models are nearly identical and the loss of efficiency is negligible. Recovery of parameters of Rasch models fit to simulated data is excellent.

Cascade production in heavy-ion collisions at SIS energies

Production of the doubly strange $\Xi$ baryon in heavy-ion collisions at \textrm{SIS} energies is studied in a relativistic transport model that includes perturbatively the strangeness-exchange reactions $\bar{K}\Lambda \to \pi \Xi$ and $\bar{K}\Sigma \to \pi \Xi$. Taking the cross sections for these reactions from the predictions of a hadronic model, we find that the $\Xi$ yield is about $10^{-4}$ in central collisions of $$Ni + $^{58}$Ni at $E/A=1.93$ \textrm{GeV}. The $\Xi$ yield is further found to be more sensitive to the magnitude of the cross sections for strangeness-exchange reactions than to the medium effects due to modified kaon properties. We have also made predictions for $\Xi$ production in Au+Au collisions at energies from 1 to 2 GeV/nucleon.Comment: 13 pages, 5 figures, typos fixed and discussions added, to appear in PL

Targeted antimicrobial therapy against Streptococcus mutans establishes protective non-cariogenic oral biofilms and reduces subsequent infection.

AimDental biofilms are complex communities composed largely of harmless bacteria. Certain pathogenic species including Streptococcus mutans (S. mutans) can become predominant when host factors such as dietary sucrose intake imbalance the biofilm ecology. Current approaches to control S. mutans infection are not pathogen-specific and eliminate the entire oral community along with any protective benefits provided. Here, we tested the hypothesis that removal of S. mutans from the oral community through targeted antimicrobial therapy achieves protection against subsequent S. mutans colonization.MethodologyControlled amounts of S. mutans were mixed with S. mutans-free saliva, grown into biofilms and visualized by antibody staining and cfu quantization. Two specifically-targeted antimicrobial peptides (STAMPs) against S. mutans were tested for their ability to reduce S. mutans biofilm incorporation upon treatment of the inocula. The resulting biofilms were also evaluated for their ability to resist subsequent exogenous S. mutans colonization.ResultsS. mutans colonization was considerably reduced ( +/- 0.4 fold reduction, P=0.01) when the surface was preoccupied with saliva-derived biofilms. Furthermore, treatment with S. mutans-specific STAMPs yielded S. mutans-deficient biofilms with significant protection against further S. mutans colonization (5 minutes treatment: 38 +/- 13 fold reduction P=0.01; 16 hours treatment: 96 +/- 28 fold reduction P=0.07).ConclusionS. mutans infection is reduced by the presence of existing biofilms. Thus maintaining a healthy or "normal" biofilm through targeted antimicrobial therapy (such as the STAMPs) could represent an effective strategy for the treatment and prevention of S. mutans colonization in the oral cavity and caries progression

Statistical description of turbulent transport for flux driven toroidal plasmas

A novel methodology to analyze non-Gaussian probability distribution functions (PDFs) of intermittent turbulent transport in global full-f gyrokinetic simulations is presented. In this work, the Auto-Regressive Integrated Moving Average (ARIMA) model is applied to time series data of intermittent turbulent heat transport to separate noise and oscillatory trends, allowing for the extraction of non-Gaussian features of the PDFs. It was shown that non-Gaussian tails of the PDFs from first principles based gyrokinetic simulations agree with an analytical estimation based on a two fluid model.Comment: arXiv admin note: text overlap with arXiv:1008.321