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W e studied the short-and long-term effects of classroom separation in twins on behavior problems and academic performance. Short-term effects were studied at age 7 in twins separated at age 5 and long-term effects at age 12 in twins who had been separated or together most of the time at school. Behavior problems were rated by mothers (Child Behavior Checklist at ages 3, 7 and 12) and teachers (Teacher Report Form at ages 7 and 12). Academic achievement was measured at age 12 using a national academic achievement test (CITO). At age 7, twins from separated pairs had more internalizing and externalizing problems than nonseparated twins, as rated by both mothers and teachers. Only for the maternal ratings of internalizing problems, however, could these effects be attributed to the separation itself and not to preexisting problems (at age 3) between separated and nonseparated twins. Long-term effects of separation were significant for maternal and teacher ratings of internalizing and externalizing problems, but these effects could be explained by preexisting differences between separated and nonseparated groups. There were no differences in academic achievement between the separated and nonseparated group. These results suggest that the decision to separate twins when they go to school is based in part on the existing behavioral problems of the twins and that, in the long run, separation does not affect problem behavior or academic achievement. The findings were the same for monozygotic and dizygotic twins.In the Netherlands, the majority of children start primary school at the age of 4 (Statistics Netherlands, Centraal Bureau voor de Statistiek, n.d.) and this is when parents and teachers of twins decide whether or not to put the children into the same classroom. As there is hardly any research comparing the adjustment of twins who are separated versus those kept together at school, this decision is presently not evidence-based (Hay, 2004). The Dutch Society for Parents of Multiples (Nederlandse Vereniging voor Ouders van Meerlingen; NVOM) advises parents to base their decision whether or not to separate twins on what they think is best for their children, though generally NVOM believes separation to be best for the individualization of the twins (Geluk & Hol, 2001).Because of the importance of this question for parents of multiples, Tully et al. (2004) investigated the effects of classroom separation on twins' behavior, progress at school, and reading abilities. They studied a sample of 878 same-sex twin pairs from the United Kingdom (UK). The children were first assessed at the age of 5 years and were tested again approximately 18 months later. The assessment was done by the teacher and included externalizing and internalizing problems, prosocial behavior, Attention Deficit Hyperactivity Disorder symptoms, standard reading scores, how hard twins worked and how much they learned. The sample was divided into three groups: not separated (at both assessments twins were together in the same class, 552 pairs), separat...

Source/description: The melanocortin-4 receptor plays a central role in the regulation of energy balance. Activation of the receptor leads to decreased energy intake and increased energy expenditure. 1 Genetic variation at the melanocortin-4 receptor locus (mc4r) is associated with body measures in several species. [2][3][4] The purebred dog population is a collection of genetic isolates with highly diverging morphology. 5 Dog breeds also appear to differ in their tendency to gain weight. It would be interesting to study the role of mc4r variation in this phenotypic diversity. The objective of this study was to identify polymorphisms in mc4r in the Golden Retriever breed for future genetic association studies. Samples:We selected the 23 least related dogs (mean genetic relationship 0.0035) from a birth cohort of Golden Retrievers with known genealogy. Genomic DNA was isolated from blood using standard methodology.

Maximum likelihood estimation techniques are widely used in twin and family studies, but soon reach computational boundaries when applied to highly complex models (e.g., models including gene-by-environment interaction and gene–environment correlation, item response theory measurement models, repeated measures, longitudinal structures, extended pedigrees). Markov Chain Monte Carlo (MCMC) algorithms are very well suited to fit complex models with hierarchically structured data. This article introduces the key concepts of Bayesian inference and MCMC parameter estimation and provides a number of scripts describing relatively simple models to be estimated by the freely obtainable BUGS software. In addition, inference using BUGS is illustrated using a data set on follicle-stimulating hormone and luteinizing hormone levels with repeated measures. The examples provided can serve as stepping stones for more complicated models, tailored to the specific needs of the individual researcher.