Bayesian latent variable models for median regression on multiple outcomes

Often a response of interest cannot be measured directly and it is necessary to rely on multiple surrogates, which can be assumed to be conditionally independent given the latent response and observed covariates. Latent response models typically assume that residual densities are Gaussian. This article proposes a Bayesian median regression modeling approach, which avoids parametric assumptions about residual densities by relying on an approximation based on quantiles. To accommodate within-subject dependency, the quantile response categories of the surrogate outcomes are related to underlying normal variables, which depend on a latent normal response. This underlying Gaussian covariance structure simplifies interpretation and model fitting, without restricting the marginal densities of the surrogate outcomes. A Markov chain Monte Carlo algorithm is proposed for posterior computation, and the methods are applied to single-cell electrophoresis (comet assay) data from a genetic toxicology study.     

Detection of bird schistosomes in lakes by PCR and filter-hybridization

Many lakes around the world are contaminated with bird schistosome cercariae, which penetrate into human skin, causing an itching dermatitis called "swimmers' itch." Bathers could be forewarned from exposure to the larvae and ecological examinations could be performed, when a sensitive method to detect the parasites in aquatic systems, where lots of organisms hinder microscopic examinations, would be available. For this purpose we cloned, sequenced, and analyzed a 396 bp tandem repeated DNA sequence from Trichobilharzia ocellata (ToSau3A), and employed it for developing molecular detection assays. It hybridized with less than 100 pg DNA from different Trichobilharzia species (T. ocellata, Trichobilharzia franki, and Trichobilharzia regenti), but not with 10 ng DNA from other related or sympatric trematodes. A PCR assay, amplifying this sequence with the same specificity, detected 100 fg T. ocellata DNA, 1 cercaria in 0.5 g plankton, and 2 cercariae in 0.5 g host snail tissues.     

Generalized character process models: estimating the genetic basis of traits that cannot be observed and that change with age or environmental conditions

The genetic analysis of characters that change as a function of some independent and continuous variable has received increasing attention in the biological and statistical literature. Previous work in this area has focused on the analysis of normally distributed characters that are directly observed. We propose a framework for the development and specification of models for a quantitative genetic analysis of function-valued characters that are not directly observed, such as genetic variation in age-specific mortality rates or complex threshold characters. We employ a hybrid Markov chain Monte Carlo algorithm involving a Monte Carlo EM algorithm coupled with a Markov chain approximation to the likelihood, which is quite robust and provides accurate estimates of the parameters in our models. The methods are investigated using simulated data and are applied to a large data set measuring mortality rates in the fruit fly, Drosophila melanogaster.     

Generalized linear mixture models for handling nonignorable dropouts in longitudinal studies

This paper presents a method for analysing longitudinal data when there are dropouts. In particular, we develop a simple method based on generalized linear mixture models for handling nonignorable dropouts for a variety of discrete and continuous outcomes. Statistical inference for the model parameters is based on a generalized estimating equations (GEE) approach (Liang and Zeger, 1986). The proposed method yields estimates of the model parameters that are valid when nonresponse is nonignorable under a variety of assumptions concerning the dropout process. Furthermore, the proposed method can be implemented using widely available statistical software. Finally, an example using data from a clinical trial of contracepting women is used to illustrate the methodology.     

A Novel Technique for the Effective Production of Short Peptide Analogs from Concatameric Short Peptide Multimers

We designed a basic unit of the modified chicken gonadotropin releasing hormone II (cGnRH-II) peptide containing a trypsin cleavable linker peptide at both ends of the original peptide. We made a synthetic DNA coding for the modified cGnRH-II peptide with asymmetric and complementary cohesive ends of linker nucleotides. A tandemly repeated DNA cassette for the expression of concatameric short peptide multimers was constructed by ligating the basic units. The expressed peptide multimers were purified and subject to amino-terminal sequence analysis, which displayed the amino acid sequences expected from the designed nucleotides of the expression cassette. The monomeric cGnRH-II peptide analogs were generated after trypsin digestion. The present results showed that the technique developed for the production of the concatameric peptide multimers with cleavable linker peptides can be generally applicable to the production of short peptide analogs.     

A gene fusion event in the evolution of aminoacyl-tRNA synthetases

The genes of glutamyl- and prolyl-tRNA synthetases (GluRS and ProRS) are organized differently in the three kingdoms of the tree of life. In bacteria and archaea, distinct genes encode the two proteins. In several organisms from the eukaryotic phylum of coelomate metazoans, the two polypeptides are carried by a single polypeptide chain to form a bifunctional protein. The linker region is made of imperfectly repeated units also recovered as singular or plural elements connected as N-terminal or C-terminal polypeptide extensions in various eukaryotic aminoacyl-tRNA synthetases. Phylogenetic analysis points to the monophyletic origin of this polypeptide motif appended to six different members of the synthetase family, belonging to either of the two classes of aminoacyl-tRNA synthetases. In particular, the monospecific GluRS and ProRS from Caenorhabditis elegans, an acoelomate metazoan, exhibit this recurrent motif as a C-terminal or N-terminal appendage, respectively. Our analysis of the extant motifs suggests a possible series of events responsible for a gene fusion that gave rise to the bifunctional glutamyl-prolyl-tRNA synthetase through recombination between genomic sequences encoding the repeated units.     

Mathematical modeling of citric acid production by repeated batch culture

A mathematical model has been created for the process of citric acid biosynthesis by yeast (mutant strain Yarrowia lipolytica) cultivated by the repeated batch (RB) method on ethanol under conditions of nitrogen limitation. The model accounts for cell growth as a function of nitrogen concentration in the culture liquid; nitrogen uptake by growing cells; citric acid production; pH control in the fermentor by means of NaOH addition; and changes in system volume. The model represents a system of five nonlinear differential equations. Experimental measurements of cell concentration, citric acid concentration, and cultivation broth volume were used with the least squares method to determine the values of eight model parameters. The parameter values obtained were consistent with literature data and general concepts of cell growth and citric acid biosynthesis. The model has been used to predict optimum RB culture conditions.     

Bayesian analysis for nonlinear regression model under skewed errors,with application in growth curves

We have considered a Bayesian approach for the nonlinear regression model by replacing the normal distribution on the error term by some skewed distributions, which account for both skewness and heavy tails or skewness alone. The type of data considered in this paper concerns repeated measurements taken in time on a set of individuals. Such multiple observations on the same individual generally produce serially correlated outcomes. Thus, additionally, our model does allow for a correlation between observations made from the same individual. We have illustrated the procedure using a data set to study the growth curves of a clinic measurement of a group of pregnant women from an obstetrics clinic in Santiago, Chile. Parameter estimation and prediction were carried out using appropriate posterior simulation schemes based in Markov Chain Monte Carlo methods. Besides the deviance information criterion (DIC) and the conditional predictive ordinate (CPO), we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. For our data set, all these criteria chose the skew‐t model as the best model for the errors. These DIC and CPO criteria are also validated, for the model proposed here, through a simulation study. As a conclusion of this study, the DIC criterion is not trustful for this kind of complex model.     

多次采血对Wistar大鼠脏器系数的影响

目的研究不同时间间隔经眼眶静脉丛多次采血后,对雄性Wistar大鼠重要脏器系数的影响。方法实验组分别间隔3 d、7 d、10 d,经眼眶静脉丛采血,每次采血1 mL,共采3次。对照组于实验组最后一次采血时采血一次,采血1 mL。每次采血前称量体重,于最后一次采血后将大鼠处死,取心脏、肝脏、肾脏、脾脏、胸腺,称量脏器重量,计算脏器系数。结果间隔3 d多次采血,大鼠的肝、肾系数差异具有显著性（P〈0.05）,间隔7 d、10 d多次采血,大鼠的各脏器系数差异无显著性。结论间隔3 d多次采血对大鼠的肝、肾系数有影响,间隔7 d、10 d多次采血对各脏器系数均无影响。