Presence of novel N-CAM glycoforms in the rat olfactory system

The functional activity of the neural cell adhesion molecule N-CAM can be modulated by posttranslational modifications such as glycosylation. For instance, the long polysialic acid side chains of N-CAM alter the adhesion properties of the protein backbone. In the present study, we identified two novel carbohydrates present on N-CAM, NOC-3 and NOC-4. Both carbohydrates were detected on N-CAM glycoforms expressed by subpopulations of primary sensory olfactory neurons in the rat olfactory system. Based on the expression of NOC-3 and NOC-4 and the olfactory marker protein (OMP), four independent subpopulations of primary sensory olfactory neurons were characterized. These neurons expressed: both NOC-3 and NOC-4 but not OMP; both NOC-4 and OMP but not NOC-3; NOC-3, NOC-4, and OMP together; and OMP alone. The NOC-3- and NOC-4-expressing neurons were widely dispersed in the olfactory neuroepithelium lining the nasal cavity. The axons of NOC-4 expressing neurons innervated all glomeruli in the olfactory bulb, whereas the NOC-3 expressing axons terminated in a discrete subset of glomeruli scattered throughout the whole olfactory bulb. We propose that both NOC-3 and NOC-4 are part of a chemical code of olfactory neurons which is used in establishing the topography of connections between the olfactory neuroepithelium and the olfactory bulb. (C) 1997 John Wiley & Sons, Inc.

The formal representation of process system modelling assumptions and their implications

In order to analyse the effect of modelling assumptions in a formal, rigorous way, a syntax of modelling assumptions has been defined. The syntax of modelling assumptions enables us to represent modelling assumptions as transformations acting on the set of model equations. The notion of syntactical correctness and semantical consistency of sets of modelling assumptions is defined and methods for checking them are described. It is shown on a simple example how different modelling assumptions act on the model equations and their effect on the differential index of the resulted model is also indicated.

Egr transcription factors in the nervous system

The Egr proteins, Egr-1, Egr-2, Egr-3 and Egr-4, are closely related members of a subclass of immediate early gene-encoded, inducible transcription factors. They share a highly homologous DNA-binding domain which recognises an identical DNA response element. In addition, they have several less-well conserved structural features in common. As immediate early proteins, the Egr transcription factors are rapidly induced by diverse extracellular stimuli within the nervous system in a discretely controlled manner. The basal expression of the Egr proteins in the developing and adult rat brain and the induction of Egr proteins by neurotransmitter analogue stimulation, physiological mimetic and brain injury paradigms is reviewed. We review evidence indicating that Egr proteins are subject to tight differential control through diverse mechanisms at several levels of regulation. These include transcriptional, translational and posttranslational (including glycosylation, phosphorylation and redox) mechanisms and protein-protein interaction. Ultimately the differentially co-ordinated Egr response may lead to discrete effects on target gene expression. Some of the known target genes of Egr proteins and functions of the Egr proteins in different cell types are also highlighted. Future directions for research into the control and function of the different Egr proteins are also explored. (C) 1997 Elsevier Science Ltd.

A stochastic frontier production function with flexible risk properties

This paper considers a stochastic frontier production function which has additive, heteroscedastic error structure. The model allows for negative or positive marginal production risks of inputs, as originally proposed by Just and Pope (1978). The technical efficiencies of individual firms in the sample are a function of the levels of the input variables in the stochastic frontier, in addition to the technical inefficiency effects. These are two features of the model which are not exhibited by the commonly used stochastic frontiers with multiplicative error structures, An empirical application is presented using cross-sectional data on Ethiopian peasant farmers. The null hypothesis of no technical inefficiencies of production among these farmers is accepted. Further, the flexible risk models do not fit the data on peasant farmers as well as the traditional stochastic frontier model with multiplicative error structure.