The Saccharomyces cerevisiae RNA-binding protein Rbp29 functions in cytoplasmic mRNA metabolism

Here we report that the Saccharomyces cerevisiae RBP29 (SGN1, YIR001C) gene encodes a 29-kDa cytoplasmic protein that binds to mRNA in vivo. Rbp29p can be co-immunoprecipitated with the poly(A) tail-binding protein Pab1p from crude yeast extracts in a dosageand RNA-dependent manner. In addition, recombinant Rbp29p binds preferentially to poly(A) with nanomolar binding affinity in vitro. Although RBP29 is not essential for cell viability, its deletion exacerbates the slow growth phenotype of yeast strains harboring mutations in the eIF4G genes TIF4631 and TIF4632. Furthermore, overexpression of RBP29 suppresses the temperaturesensitive growth phenotype of specific tif4631, tif4632, and pab1 alleles. These data suggest that Rbp29p is an mRNA-binding protein that plays a role in modulating the expression of cytoplasmic mRNA.

Independent functions of yeast Pcf11p in pre-mRNA 3' end processing and in transcription termination

Pcf11p, an essential subunit of the yeast cleavage factor IA, is required for pre‐mRNA 3′ end processing, binds to the C‐terminal domain (CTD) of the largest subunit of RNA polymerase II (RNAP II) and is involved in transcription termination. We show that the conserved CTD interaction domain (CID) of Pcf11p is essential for cell viability. Interestingly, the CTD binding and 3′ end processing activities of Pcf11p can be functionally uncoupled from each other and provided by distinct Pcf11p fragments in trans. Impaired CTD binding did not affect the 3′ end processing activity of Pcf11p and a deficiency of Pcf11p in 3′ end processing did not prevent CTD binding. Transcriptional run‐on analysis with the CYC1 gene revealed that loss of cleavage activity did not correlate with a defect in transcription termination, whereas loss of CTD binding did. We conclude that Pcf11p is a bifunctional protein and that transcript cleavage is not an obligatory step prior to RNAP II termination.

Role of the N-terminal region in G protein-coupled receptor functions : negative modulation revealed by 5-HT2B receptor polymorphisms

The putative role of the N-terminal region of rhodopsin-like 7 transmembrane biogenic amine receptors in agonist-induced signaling has not yet been clarified despite recent advances in 7 transmembrane receptor structural biology. Given the existence of N-terminal nonsynonymous polymorphisms (R6G;E42G) within the HTR2B gene in a drug-abusing population, we assessed whether these polymorphisms affect 5-hydroxytryptamine 2B (5-HT2B) receptor in vitro pharmacologic and coupling properties in transfected COS-7 cells. Modification of the 5-HT2B receptor N terminus by the R6G;E42G polymorphisms increases such agonist signaling pathways as inositol phosphate accumulation as assessed by either classic or operational models. The N-terminal R6G;E42G mutations of the 5-HT2B receptor also increase cell proliferation and slow its desensitization kinetics compared with the wild-type receptor, further supporting a role for the N terminus in transduction efficacy. Furthermore, by coexpressing a tethered wild-type 5-HT2B receptor N terminus with a 5-HT2B receptor bearing a N-terminal deletion, we were able to restore original coupling. This reversion to normal activity of a truncated 5-HT2B receptor by coexpression of the membrane-tethered wild-type 5-HT2B receptor N terminus was not observed using a membrane-tethered 5-HT2B receptor R6G;E42G N terminus. These data suggest that the N terminus exerts a negative control over basal as well as agonist-stimulated receptor activity that is lost in the R6G;E42G mutant. Our findings reveal a new and unanticipated role of the 5-HT2B receptor N terminus as a negative modulator, affecting both constitutive and agonist-stimulated activity. Moreover, our data caution against excluding the N terminus and extracellular loops in structural studies of this 7 transmembrane receptor family

World emissions and economic growth: Application of non-parametric methods

The Environmental Kuznets Curve (EKC) hypothesises an inverse U-shaped relationship between a measure of environmental pollution and per capita income levels. In this study, we apply non-parametric estimation of local polynomial regression (local quadratic fitting) to allow more flexibility in local estimation. This study uses a larger and globally representative sample of many local and global pollutants and natural resources including Biological Oxygen Demand (BOD) emission, CO2 emission, CO2 damage, energy use, energy depletion, mineral depletion, improved water source, PM10, particulate emission damage, forest area and net forest depletion. Copyright © 2009 Inderscience Enterprises Ltd.

Bayesian hierarchical models for analysing spatial point-based data at a grid level: A comparison of approaches

Spatial data are now prevalent in a wide range of fields including environmental and health science. This has led to the development of a range of approaches for analysing patterns in these data. In this paper, we compare several Bayesian hierarchical models for analysing point-based data based on the discretization of the study region, resulting in grid-based spatial data. The approaches considered include two parametric models and a semiparametric model. We highlight the methodology and computation for each approach. Two simulation studies are undertaken to compare the performance of these models for various structures of simulated point-based data which resemble environmental data. A case study of a real dataset is also conducted to demonstrate a practical application of the modelling approaches. Goodness-of-fit statistics are computed to compare estimates of the intensity functions. The deviance information criterion is also considered as an alternative model evaluation criterion. The results suggest that the adaptive Gaussian Markov random field model performs well for highly sparse point-based data where there are large variations or clustering across the space; whereas the discretized log Gaussian Cox process produces good fit in dense and clustered point-based data. One should generally consider the nature and structure of the point-based data in order to choose the appropriate method in modelling a discretized spatial point-based data.

Fire performance of LSF wall panels using numerical parametric studies

Light Gauge Steel Framing (LSF) walls made of cold-formed and thin-walled steel lipped channel studs with plasterboard linings on both sides are commonly used in commercial, industrial and residential buildings. However, there is limited data about their structural and thermal performances under fire conditions. Recent research at the Queensland University of Technology has investigated the structural and thermal behaviour of load bearing LSF wall systems. In this research a series of full scale fire tests was conducted first to evaluate the performance of LSF wall systems with eight different wall configurations under standard fire conditions. Finite element models of LSF walls were then developed, analysed under transient and steady state conditions, and validated using full scale fire tests. This paper presents the details of an investigation into the fire performance of LSF wall panels based on an extensive finite element analysis based parametric study. The LSF wall panels with eight different plasterboard-insulation configurations were considered under standard fire conditions. Effects of varying steel grades, steel thicknesses, screw spacing, plasterboard restraint, insulation materials and load ratio on the fire performance of LSF walls were investigated and the results of extensive fire performance data are presented in the form of load ratio versus time and critical hot flange (failure) temperature curves.

A frontier functions approach to optimal scales of sustainable production

This paper translates the concepts of sustainable production to three dimensions of economic, environmental and ecological sustainability to analyze optimal production scales by solving optimizing problems. Economic optimization seeks input-output combinations to maximize profits. Environmental optimization searches for input-output combinations that minimize the polluting effects of materials balance on the surrounding environment. Ecological optimization looks for input-output combinations that minimize the cumulative destruction of the entire ecosystem. Using an aggregate space, the framework illustrates that these optimal scales are often not identical because markets fail to account for all negative externalities. Profit-maximizing firms normally operate at the scales which are larger than optimal scales from the viewpoints of environmental and ecological sustainability; hence policy interventions are favoured. The framework offers a useful tool for efficiency studies and policy implication analysis. The paper provides an empirical investigation using a data set of rice farms in South Korea.

Frequency-motivated observer design for the prediction of parametric roll resonance control applications in marine systems

This work deals with estimators for predicting when parametric roll resonance is going to occur in surface vessels. The roll angle of the vessel is modeled as a second-order linear oscillatory system with unknown parameters. Several algorithms are used to estimate the parameters and eigenvalues of the system based on data gathered experimentally on a 1:45 scale model of a tanker. Based on the estimated eigenvalues, the system predicts whether or not parametric roll occurred. A prediction accuracy of 100% is achieved for regular waves, and up to 87.5% for irregular waves.

Validation of a container ship model for parametric rolling

The objective of this work is to formulate a nonlinear, coupled model of a container ship during parametric roll resonance, and to validate the model using experimental data.

Functions and therapeutic roles of exosomes in cancer

The role of exosomes in cancer development has become the focus of much research, due to the many emerging roles possessed by exosomes. These micro-vesicles that are ubiquitously released in to the extracellular milieu, have been found to regulate immune system function, particularly in tumorigenesis, as well as conditioning future metastatic sites for the attachment and growth of tumor tissue. Through an interaction with a range of host tissue, exosomes are able to generate a pro-tumor environment that is essential for carcinogenesis. Herein, we discuss the contents of exosomes and their contribution to tumorigenesis, as well as their role in chemotherapeutic resistance and the development of novel cancer treatments and the identification of cancer biomarkers.

Critical linguistics in the early years : exploring functions of language through sophisticated picture books and process drama strategies

In this chapter we describe a critical fairytales unit taught to 4.5 to 5.5 year olds in a context of intensifying pressure to raise literacy achievement. The unit was infused with lessons on reinterpreted fairytales followed by process drama activities built around a sophisticated picture book, Beware of the Bears (MacDonald, 2004). The latter entailed a text analytic approach to critical literacy derived from systemic functional linguistics (Halliday, 1978; Halliday & Matthiessen, 2004). This approach provides a way of analysing how words and discourse are used to represent the world in a particular way and shape reader relations with the author in a particular field (Janks, 2010).

Examining the predictive value of combining the theory of planned behaviour and the volunteer functions inventory

The functions of the volunteer functions inventory were combined with the constructs of the theory of planned behaviour (i.e., attitudes, subjective norms, and perceived behavioural control) to establish whether a stronger, single explanatory model prevailed. Undertaken in the context of episodic, skilled volunteering by individuals who were retired or approaching retirement (N = 186), the research advances on prior studies which either examined the predictive capacity of each model independently or compared their explanatory value. Using hierarchical regression analysis, the functions of the volunteer functions inventory (when controlling for demographic variables) explained an additional 7.0% of variability in individuals’ willingness to volunteer over and above that accounted for by the theory of planned behaviour. Significant predictors in the final model included attitudes, subjective norms and perceived behavioural control from the theory of planned behaviour and the understanding function from the volunteer functions inventory. It is proposed that the items comprising the understanding function may represent a deeper psychological construct (e.g., self-actualisation) not accounted for by the theory of planned behaviour. The findings highlight the potential benefit of combining these two prominent models in terms of improving understanding of volunteerism and providing a single parsimonious model for raising rates of this important behaviour.

Understanding Uncertainties in Non-Linear Population Trajectories: A Bayesian Semi-Parametric Hierarchical Approach to Large-Scale Surveys of Coral Cover

Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making

Exact parametric confidence intervals for Bland-Altman limits of agreement

Purpose The previous literature on Bland-Altman analysis only describes approximate methods for calculating confidence intervals for 95% Limits of Agreement (LoAs). This paper describes exact methods for calculating such confidence intervals, based on the assumption that differences in measurement pairs are normally distributed. Methods Two basic situations are considered for calculating LoA confidence intervals: the first where LoAs are considered individually (i.e. using one-sided tolerance factors for a normal distribution); and the second, where LoAs are considered as a pair (i.e. using two-sided tolerance factors for a normal distribution). Equations underlying the calculation of exact confidence limits are briefly outlined. Results To assist in determining confidence intervals for LoAs (considered individually and as a pair) tables of coefficients have been included for degrees of freedom between 1 and 1000. Numerical examples, showing the use of the tables for calculating confidence limits for Bland-Altman LoAs, have been provided. Conclusions Exact confidence intervals for LoAs can differ considerably from Bland and Altman’s approximate method, especially for sample sizes that are not large. There are better, more precise methods for calculating confidence intervals for LoAs than Bland and Altman’s approximate method, although even an approximate calculation of confidence intervals for LoAs is likely to be better than none at all. Reporting confidence limits for LoAs considered as a pair is appropriate for most situations, however there may be circumstances where it is appropriate to report confidence limits for LoAs considered individually.