Processing of somatostatin precursors: evidence for enzymatic cleavage by hypothalamic extract

The action of enzymes extracted from rat hypothalamus on the previously characterized high molecular weight forms of hypothalamic somatostatin-like immunoreactivity (4 K SLI and 25 K SLI) has been investigated in vitro in order to further define the role of these molecules as possible precursors for tetradecapeptide somatostatin (SRIF). Studies of the degradation of endogenous SLI and of synthetic SRIF by hypothalamic enzymes showed that the time course of breakdown of endogenous SLI is markedly slower than that of synthetic SRIF due to the relative stability of 25 K SLI as well as the generation of at least two new immunoreactive molecules. Incubation of purified 25 K SLI with SLI-free hypothalamic extract showed after 10 to 30 min newly formed immunoreactive material of an intermediate size between 25 K SLI and 4 K SLI and after 60 min the emergence of material coeluting with SRIF. These data show that the hypothalamus contains the enzymes necessary for degrading endogenous SLI and for processing the 25 K SLI molecule to SRIF providing further evidence that 25 K SLI might be a biosynthetic precursor for SRIF.     

A critique of the collaborative cytogenetics study to measure and minimize interlaboratory variation.

A statistical reanalysis was performed on the data fecently reported on a 6-laboratory, collaborative cytogenetic study to measure and minimize interlaboratory variation. Three of the laboratories had mean values significantly different from the others on most of the 6 indexes of chemically-induced aberration; one laboratory with values higher and two with values lower. Furthermore, relative variability of the values around the means was consistently lower in one of the 6 participating laborabories. The results of the reanalysis of this collaborative study demonstrates that significant interlaboratory differences exist and that these should be adjusted or diminished before rat cytogenetic analysis can be an effective test system for evaluation of a compound for mutagenic potential.     

On Testing for Equicorrelation in Random Coefficient Models

Recently BHATTI (1993) considered an efficient estimation of random coefficient model based on survey data. The main objective of this paper is to construct one sided test for testing equicorrelation coefficient in presence of random coefficients using optimal testing procedure. The test statistic is a ratio of quadratic forms in normal variables which is most powerful and point optimal invariant.     

Stabilization Coefficient of Random Variable

Coefficient of variation, standard deviation divided by mean, has some essential defects. Its density, expectation and variance are too complex to make the statistical inference for such a coefficient. The definition of stabilization coefficient is just the reciprocal of variation coefficient, mean divided by standard deviation. Such a coefficient has a simple expectation and a simple variance, and is an asymptotically unbiased estimator and a consistent estimator of its true value. Furthermore, coefficient of stabilization has an asymptotic normality. Due to its statistical advantages, coefficient of stabilization is easy to be tested statistically. In some applied fields, usually, there is an increasing standard deviation accompanying an increasing mean. Coefficient of stabilization can be practically used for some comparison studies in such fields. Illustrations about comparing microorganism strains are given in this paper. The robustness of stabilization coefficient is satisfactory.     

A Formula for the Gini Coefficient and its Decomposition

This paper is concerned with the Gini coefficient as a concentration measure of the distribution. The proposed formula for the computation of the Gini coefficient allows its decomposition according to different sub-groups of the initial population, either exactly or approximately.     

Rank of Correlation Coefficient as a Comparable Measure for Biological Significance of Gene Coexpression

Information regarding gene coexpression is useful to predict gene function. Several databases have been constructed for gene coexpression in model organisms based on a large amount of publicly available gene expression data measured by GeneChip platforms. In these databases, Pearson''s correlation coefficients (PCCs) of gene expression patterns are widely used as a measure of gene coexpression. Although the coexpression measure or GeneChip summarization method affects the performance of the gene coexpression database, previous studies for these calculation procedures were tested with only a small number of samples and a particular species. To evaluate the effectiveness of coexpression measures, assessments with large-scale microarray data are required. We first examined characteristics of PCC and found that the optimal PCC threshold to retrieve functionally related genes was affected by the method of gene expression database construction and the target gene function. In addition, we found that this problem could be overcome when we used correlation ranks instead of correlation values. This observation was evaluated by large-scale gene expression data for four species: Arabidopsis, human, mouse and rat.     

Interaction of enkephalin peptides with anionic model membranes

According to the model for passive transport across the membranes, the total flow of permeant molecules is related to the product of the water-membrane partition coefficient and the diffusion coefficient, and to the water-membrane interfacial barrier. The effect of membrane surface charge on the permeability and interaction of analgesic peptide ligands with model membranes was investigated. A mixture of zwitterionic phospholipids with cholesterol was used as a model membrane. The lipid membrane charge density was controlled by the addition of anionic 1-palmitoyl-2-oleoylphosphatidylserine. Two classes of highly potent analgesic peptides were studied, c[D-Pen²,D-Pen⁵]enkephalin (DPDPE) and biphalin, a dimeric analog of enkephalin. The effect of increased surface charge on the permeability of the zwitterionic DPDPE is a relatively modest decrease, that appears to be due to a diminished partition coefficient. On the other hand the binding of the dicationic biphalin ligands to membranes increases proportionally with increased negative surface charge. This effect translates into a significant reduction of biphalin permeability by reducing the diffusion of the peptide across the bilayer. These experiments show the importance of electrostatic effects on the peptide-membrane interactions and suggest that the negative charge naturally present in cell membranes may hamper the membrane transport of some peptide drugs, especially cationic ones, unless there are cationic transporters present.     

Accuracy Analysis with Special Reference to the Prediction of Grassland Yield

In this paper techniques are presented which allow the evaluation of accuracy of prediction methods, with special reference to the prediction of grassland yield. The more prominent methods of predicting grassland yield are discussed. Two coefficients, which are normalizations of the mean-squared-error, are proposed as measures of accuracy. It is shown that the mean-squared-error partitions into the sum of three meaningful components of error. The distribution of the components is discussed under the assumption that the actual and predicted yields have a bivariate normal distribution. The problem of accuracy analysis is addressed when one is only interested in ranking the yields of grassland areas. The ratio of the mean-squared-error for two competing prediction methods is investigated. Finally, a multiplicative model is studied which allows predicting ability to differ over time or over regions.     

The determination of desirable and nuisance plant levels in streams

To cope with luxuriant plant growth in the streams of southern Ontario, an approach to determine the desirable and nuisance plant levels was proposed.With a more intensive analysis of the assimilation efficiency of plant communities, which includes the fractionation of community respiration as well as compensation for the plant self-shading effect, the plant biomass of all species component expressed as chlorophyll a can be estimated from the modified growth equation, where B is the biomass, P_max is the photosynthetic growth rate at light saturation, A is the assimilation number and S is the plant shading coefficient. Once comparable biomass values are available, a desirable plant level relative to specified environmental standards can be determined.For instance, to meet the minimum dissolved oxygen criteria of 5 ppm, the desirable and the nuisance crop levels in the North Thames River, Ontario, were found to be 0.15 and 0.75 g chla/m² respectively.     

Monitoring habitat types by the mixed multinomial logit model using panel data

Habitats in the Wadden Sea, a world heritage area, are affected by land subsidence resulting from natural gas extraction and by sea level rise. Here we describe a method to monitor changes in habitat types by producing sequential maps based on point information followed by mapping using a multinomial logit regression model with abiotic variables of which maps are available as predictors.In a 70 ha study area a total of 904 vegetation samples has been collected in seven sampling rounds with an interval of 2–3 years. Half of the vegetation plots was permanent, violating the assumption of independent data in multinomial logistic regression. This paper shows how this dependency can be accounted for by adding a random effect to the multinomial logit (MLN) model, thus becoming a mixed multinomial logit (MMNL) model. In principle all regression coefficients can be taken as random, but in this study only the intercepts are treated as location-specific random variables (random intercepts model). With six habitat types we have five intercepts, so that the number of extra model parameters becomes 15, 5 variances and 10 covariances.The likelihood ratio test showed that the MMNL model fitted significantly better than the MNL model with the same fixed effects. McFadden-R² for the MMNL model was 0.467, versus 0.395 for the MNL model. The estimated coefficients of the MMNL and MNL model were comparable; those of altitude, the most important predictor, differed most. The MMNL model accounts for pseudo-replication at the permanent plots, which explains the larger standard errors of the MMNL coefficients. The habitat type at a given location-year combination was predicted by the habitat type with the largest predicted probability. The series of maps shows local trends in habitat types most likely driven by sea-level rise, soil subsidence, and a restoration project.We conclude that in environmental modeling of categorical variables using panel data, dependency of repeated observations at permanent plots should be accounted for. This will affect the estimated probabilities of the categories, and even stronger the standard errors of the regression coefficients.