A structural MRI study in monozygotic twins concordant or discordant for attention/hyperactivity problems: Evidence for genetic and environmental heterogeneity in the developing brain.

Several structural brain abnormalities have been reported in patients with Attention Deficit Hyperactivity Disorder (ADHD). However, the etiology of these brain changes is still unclear. To investigate genetic and environmental influences on ADHD related neurobiological changes, we performed Voxel-Based Morphometry on MRI scans from monozygotic (MZ) twins selected from a large longitudinal population database to be highly concordant or highly discordant for ratings on the Child Behavior Checklist Attention Problem scale (CBCL-AP). Children scoring low on the CBCL-AP are at low risk for ADHD, whereas children scoring high on this scale are at high-risk for ADHD. Brain differences between concordant high-risk twin pairs and concordant low-risk twin pairs likely reflect the genetic risk for ADHD; brain differences between the low-risk and high-risk twins from discordant MZ twin pairs reflect the environmental risk for ADHD. A major difference between comparisons of high and low-risk twins from concordant pairs and high/low twins from discordant pairs was found for the prefrontal lobes. The concordant high-risk pairs showed volume loss in orbitofrontal subdivisions. High-risk members from the discordant twin pairs exhibited volume reduction in the right inferior dorsolateral prefontal cortex. In addition, the posterior corpus callosum was compromised in concordant high-risk pairs, only. Our findings indicate that inattention and hyperactivity symptoms are associated with anatomical abnormalities of a distributed action-attentional network. Different brain areas of this network appear to be affected in inattention/hyperactivity caused by genetic (i.e., high concordant MZ pairs) vs. environmental (i.e., high-low discordant MZ pairs) risk factors. These results provide clues that further our understanding of brain alterations in ADHD. © 2007 Elsevier Inc. All rights reserved

A hidden Markov model approach for determining vessel activity from vessel monitoring system data.

Many fisheries worldwide have adopted vessel monitoring systems (VMS) for compliance purposes. An added benefit of these systems is that they collect a large amount of data on vessel locations at very fine spatial and temporal scales. This data can provide a wealth of information for stock assessment, research, and management. However, since most VMS implementations record vessel location at set time intervals with no regard to vessel activity, some methodology is required to determine which data records correspond to fishing activity. This paper describes a probabilistic approach, based on hidden Markov models (HMMs), to determine vessel activity. A HMM provides a natural framework for the problem and, by definition, models the intrinsic temporal correlation of the data. The paper describes the general approach that was developed and presents an example of this approach applied to the Queensland trawl fishery off the coast of eastern Australia. Finally, a simulation experiment is presented that compares the misallocation rates of the HMM approach with other approaches

Comparison of relative fishing power between different sectors of the Queensland trawl fishery, Australia

The effects of improvements in fishing gear and technology on prawn and scallop catches from the Queensland trawl fishery were investigated. The species, the spatial distribution of the stocks, and the management regulations were used to partition the fishery into five main sectors: Torres Strait tiger prawns, north Queensland tiger prawns, shallow-water (50 fathoms) eastern king prawns and saucer scallops. For each sector, annual changes in average relative fishing power were calculated as a function of the fishing gear and technology parameters estimated in a generalised linear model and the average and/or percentage use of different gears and technologies in the sector. Over the 11 years from 1989 to 1999, fishing power for an average vessel increased at a low of 4% in the saucer scallop sector to a high of 27% in the shallow-water eastern king prawn sector. Fishing power in the shallow-water eastern king and tiger prawn sectors had the highest rates of increase and was largely attributed to vessels upgrading to larger engines. Increases in the number of vessels using global positioning systems and computer mapping software also contributed to increased fishing power in the two tiger prawn sectors. In the deep-water eastern king prawn sector, increased fishing power was associated with net head rope length, however, current management controls over engine size and head rope length are likely to limit this source of increase in fishing power. Fishing power in the scallop sector was associated with a relatively low average trawl speed of about 2.2 kn, which differed from the prawn sectors where higher catches were generally taken at trawl speeds of at least 3 kn. The results should be used to standardise fishing effort and be incorporated into stock assessments for each sector