No abstract

Aim: To determine the size of the growth deficit in Dutch monozygotic and dizygotic twins aged 0-2.5 years as compared to singletons and to construct reference growth charts for twins.Methods: Growth of twins was studied using longitudinal data on over 4000 twins aged 0-2.5 years of the Netherlands Twin Register. The LMS method was used to obtain growth references for length/height, weight, and body mass index (BMI) for twins.Results: During the first 2.5 years of age, differences in length/height and weight between twins and singletons decrease but do not disappear. BMI of twins deviates less than that of singletons.

Considerable recent attention has focused on the quantitative analysis of enzyme-altered foci in rodent hepatocarcinogenesis experiments. These foci are believed to represent clones of premalignant cells. A method is presented for the quantitative analysis of these foci that takes into account both the total number of focal transections observed in each liver cross-section and the size distribution of these transections. The method, which has a natural interpretation within the framework of a two-mutation model for carcinogenesis, yields estimates of rates of initiation and of growth rates of enzyme-altered foci as functions of dose of the agent under consideration. Definitions of initiation and promotion potencies are proposed. The method is illustrated by application to an experiment in which rats were administered N-nitrosomorpholine at various concentrations in their drinking water.

Neuronal signal integration and information processing in cortical networks critically depend on the organization of synaptic connectivity. During development, neurons can form synaptic connections when their axonal and dendritic arborizations come within close proximity of each other. Although many signaling cues are thought to be involved in guiding neuronal extensions, the extent to which accidental appositions between axons and dendrites can already account for synaptic connectivity remains unclear. To investigate this, we generated a local network of cortical L2/3 neurons that grew out independently of each other and that were not guided by any extracellular cues. Synapses were formed when axonal and dendritic branches came by chance within a threshold distance of each other. Despite the absence of guidance cues, we found that the emerging synaptic connectivity showed a good agreement with available experimental data on spatial locations of synapses on dendrites and axons, number of synapses by which neurons are connected, connection probability between neurons, distance between connected neurons, and pattern of synaptic connectivity. The connectivity pattern had a small-world topology but was not scale free. Together, our results suggest that baseline synaptic connectivity in local cortical circuits may largely result from accidentally overlapping axonal and dendritic branches of independently outgrowing neurons.

Type 1 diabetes is a T-cell-mediated chronic disease characterized by the autoimmune destruction of pancreatic insulin-producing beta cells and complete insulin deficiency. It is the result of a complex interrelation of genetic and environmental factors, most of which have yet to be identified. Simultaneous identification of these genetic factors, through use of unphased genotype data, has received increasing attention in the past few years. Several approaches have been described, such as the modified transmission/disequilibrium test procedure, the conditional extended transmission/disequilibrium test, and the stepwise logistic-regression procedure. These approaches are limited either by being restricted to family data or by ignoring so-called "haplotype interactions" between alleles. To overcome this limit, the present study provides a general method to identify, on the basis of unphased genotype data, the haplotype blocks that interact to define the risk for a complex disease. The principle underpinning the proposal is minimal entropy. The performance of our procedure is illustrated for both simulated and real data. In particular, for a set of Dutch type 1 diabetes data, our procedure suggests some novel evidence of the interactions between and within haplotype blocks that are across chromosomes 1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 15, 16, 17, 19, and 21. The results demonstrate that, by considering interactions between potential disease haplotype blocks, we may succeed in identifying disease-predisposing genetic variants that might otherwise have remained undetected.