Mapping cortical change in Alzheimer's disease, brain development, and schizophrenia

This paper describes algorithms that can identify patterns of brain structure and function associated with Alzheimer's disease, schizophrenia, normal aging, and abnormal brain development based on imaging data collected in large human populations. Extraordinary information can be discovered with these techniques: dynamic brain maps reveal how the brain grows in childhood, how it changes in disease, and how it responds to medication. Genetic brain maps can reveal genetic influences on brain structure, shedding light on the nature-nurture debate, and the mechanisms underlying inherited neurobehavioral disorders. Recently, we created time-lapse movies of brain structure for a variety of diseases. These identify complex, shifting patterns of brain structural deficits, revealing where, and at what rate, the path of brain deterioration in illness deviates from normal. Statistical criteria can then identify situations in which these changes are abnormally accelerated, or when medication or other interventions slow them. In this paper, we focus on describing our approaches to map structural changes in the cortex. These methods have already been used to reveal the profile of brain anomalies in studies of dementia, epilepsy, depression, childhood and adult-onset schizophrenia, bipolar disorder, attention-deficit/ hyperactivity disorder, fetal alcohol syndrome, Tourette syndrome, Williams syndrome, and in methamphetamine abusers. Specifically, we describe an image analysis pipeline known as cortical pattern matching that helps compare and pool cortical data over time and across subjects. Statistics are then defined to identify brain structural differences between groups, including localized alterations in cortical thickness, gray matter density (GMD), and asymmetries in cortical organization. Subtle features, not seen in individual brain scans, often emerge when population-based brain data are averaged in this way. Illustrative examples are presented to show the profound effects of development and various diseases on the human cortex. Dynamically spreading waves of gray matter loss are tracked in dementia and schizophrenia, and these sequences are related to normally occurring changes in healthy subjects of various ages. (C) 2004 Published by Elsevier Inc.

Association of tumor necrosis factor-alpha polymorphisms and ozone-induced change in lung function

Ozone is a major air pollutant with adverse health effects which exhibit marked inter-individual variability. In mice, regions of genetic linkage with ozone-induced lung injury include the tumor necrosis factor-alpha (TNF), lymphotoxin-alpha (LTA), Toll-like receptor 4 (TLR4), superoxide dismutase (SOD2), and glutathione peroxidase (GPX1) genes. We genotyped polymorphisms in these genes in 51 individuals who had undergone ozone challenge. Mean change in FEV1 with ozone challenge, as a percentage of baseline, was -3% in TNF -308G/A or A/A individuals, compared with -9% in G/G individuals (p = 0.024). When considering TNF haplotypes, the smallest change in FEV1 with ozone exposure was associated with the TNF haplotype comprising LTA +252G/TNF -1031T/TNF -308A/TNF -238G. This association remained statistically significant after correction for age, sex, disease, and ozone concentration (p = 0.047). SOD2 or GPX1 genotypes were not associated with lung function, and the TLR4 polymorphism was too infrequent to analyze. The results of this study support TNF as a genetic factor for susceptibility to ozone-induced changes in lung function in humans, and has potential implications for stratifying health risks of air pollution.

Employee group memberships and organisational communication during organisational change

The preset study adopted an intergroup approach to information sharing and communication in three organisational samples during change. In Study 1, employees from a public hospital (N = 142) completed a survey measuring perceptions of organisational communication and strength of identification with the work unit and the organisation as a whole. Consistent with predictions, team members rated communication from double ingroup members (same work unit/same occupational group) more favourably than communication from partial group members (same work unit/different occupational group). Also as predicted, work unit identification was related to favourable ratings of work unit communication across occupational groups, whereas occupational identification was related to favourable ratings of work unit communication within occupational groups. In Study 2, strength of identification with three organisational groups was associated with positive ratings of communication among employees from the same public hospital (N = 189) and a military organisation (N = 2119). Based on these results, intergroup strategies for the management of information sharing and organisational communication during change are discussed.