Sugarcane Phosphoribosyl Pyrophosphate Synthetase: Molecular Characterization of a Phosphate-independent PRS

Phosphoribosyl pyrophosphate synthetase (PRS-EC:2.7.6.1) is an important enzyme present in several metabolic pathways, thus forming a complex family of isoenzymes. However, plant PRS enzymes have not been extensively investigated. In this study, a sugarcane prs gene has been characterized from the Sugar Cane Expressed Sequence Tag Genome Project. This gene contains a 984-bp open reading frame encoding a 328-amino acid protein. The predicted amino acid sequence has 77% and 78% amino acid sequence identity to Arabidopsis thaliana and Spinacia oleracea PRS4, respectively. The assignment of sugarcane PRS as a phosphate-independent PRS isoenzyme (Class II PRS) is verified following enzyme assay and phylogenetic reconstruction of PRS homologues. To gain further insight into the structural framework of the phosphate independence of sugarcane PRS, a molecular model is described. This model reveals the formation of two conserved domains elucidating the structural features involved in sugarcane PRS phosphate independence. The recombinant PRS retains secondary structure elements and a quaternary arrangement consistent with known PRS homologues, based on circular dichroism measurements.

Heteroscedastic controlled calibration model applied to analytical chemistry

In chemical analyses performed by laboratories, one faces the problem of determining the concentration of a chemical element in a sample. In practice, one deals with the problem using the so-called linear calibration model, which considers that the errors associated with the independent variables are negligible compared with the former variable. In this work, a new linear calibration model is proposed assuming that the independent variables are subject to heteroscedastic measurement errors. A simulation study is carried out in order to verify some properties of the estimators derived for the new model and it is also considered the usual calibration model to compare it with the new approach. Three applications are considered to verify the performance of the new approach. Copyright (C) 2010 John Wiley & Sons, Ltd.

Short-time behaviour of demand and price viewed through an exactly solvable model for heterogeneous interacting market agents

We introduce a stochastic heterogeneous interacting-agent model for the short-time non-equilibrium evolution of excess demand and price in a stylized asset market. We consider a combination of social interaction within peer groups and individually heterogeneous fundamentalist trading decisions which take into account the market price and the perceived fundamental value of the asset. The resulting excess demand is coupled to the market price. Rigorous analysis reveals that this feedback may lead to price oscillations, a single bounce, or monotonic price behaviour. The model is a rare example of an analytically tractable interacting-agent model which allows LIS to deduce in detail the origin of these different collective patterns. For a natural choice of initial distribution, the results are independent of the graph structure that models the peer network of agents whose decisions influence each other. (C) 2009 Elsevier B.V. All rights reserved.

A robust Bayesian approach to null intercept measurement error model with application to dental data

Measurement error models often arise in epidemiological and clinical research. Usually, in this set up it is assumed that the latent variable has a normal distribution. However, the normality assumption may not be always correct. Skew-normal/independent distribution is a class of asymmetric thick-tailed distributions which includes the Skew-normal distribution as a special case. In this paper, we explore the use of skew-normal/independent distribution as a robust alternative to null intercept measurement error model under a Bayesian paradigm. We assume that the random errors and the unobserved value of the covariate (latent variable) follows jointly a skew-normal/independent distribution, providing an appealing robust alternative to the routine use of symmetric normal distribution in this type of model. Specific distributions examined include univariate and multivariate versions of the skew-normal distribution, the skew-t distributions, the skew-slash distributions and the skew contaminated normal distributions. The methods developed is illustrated using a real data set from a dental clinical trial. (C) 2008 Elsevier B.V. All rights reserved.