A commonly carried genetic variant in the delta opioid receptor gene, OPRD1, is associated with smaller regional brain volumes: Replication in elderly and young populations

Delta opioid receptors are implicated in a variety of psychiatric and neurological disorders. These receptors play a key role in the reinforcing properties of drugs of abuse, and polymorphisms in OPRD1 (the gene encoding delta opioid receptors) are associated with drug addiction. Delta opioid receptors are also involved in protecting neurons against hypoxic and ischemic stress. Here, we first examined a large sample of 738 elderly participants with neuroimaging and genetic data from the Alzheimer's Disease Neuroimaging Initiative. We hypothesized that common variants in OPRD1 would be associated with differences in brain structure, particularly in regions relevant to addictive and neurodegenerative disorders. One very common variant (rs678849) predicted differences in regional brain volumes. We replicated the association of this single-nucleotide polymorphism with regional tissue volumes in a large sample of young participants in the Queensland Twin Imaging study. Although the same allele was associated with reduced volumes in both cohorts, the brain regions affected differed between the two samples. In healthy elderly, exploratory analyses suggested that the genotype associated with reduced brain volumes in both cohorts may also predict cerebrospinal fluid levels of neurodegenerative biomarkers, but this requires confirmation. If opiate receptor genetic variants are related to individual differences in brain structure, genotyping of these variants may be helpful when designing clinical trials targeting delta opioid receptors to treat neurological disorders.

Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group

The pattern of structural brain alterations associated with major depressive disorder (MDD) remains unresolved. This is in part due to small sample sizes of neuroimaging studies resulting in limited statistical power, disease heterogeneity and the complex interactions between clinical characteristics and brain morphology. To address this, we meta-analyzed three-dimensional brain magnetic resonance imaging data from 1728 MDD patients and 7199 controls from 15 research samples worldwide, to identify subcortical brain volumes that robustly discriminate MDD patients from healthy controls. Relative to controls, patients had significantly lower hippocampal volumes (Cohen’s d=−0.14, % difference=−1.24). This effect was driven by patients with recurrent MDD (Cohen’s d=−0.17, % difference=−1.44), and we detected no differences between first episode patients and controls. Age of onset ⩽21 was associated with a smaller hippocampus (Cohen’s d=−0.20, % difference=−1.85) and a trend toward smaller amygdala (Cohen’s d=−0.11, % difference=−1.23) and larger lateral ventricles (Cohen’s d=0.12, % difference=5.11). Symptom severity at study inclusion was not associated with any regional brain volumes. Sample characteristics such as mean age, proportion of antidepressant users and proportion of remitted patients, and methodological characteristics did not significantly moderate alterations in brain volumes in MDD. Samples with a higher proportion of antipsychotic medication users showed larger caudate volumes in MDD patients compared with controls. This currently largest worldwide effort to identify subcortical brain alterations showed robust smaller hippocampal volumes in MDD patients, moderated by age of onset and first episode versus recurrent episode status.

Investigating brain connectivity heritability in a twin study using diffusion imaging data

Heritability of brain anatomical connectivity has been studied with diffusion-weighted imaging (DWI) mainly by modeling each voxel's diffusion pattern as a tensor (e.g., to compute fractional anisotropy), but this method cannot accurately represent the many crossing connections present in the brain. We hypothesized that different brain networks (i.e., their component fibers) might have different heritability and we investigated brain connectivity using High Angular Resolution Diffusion Imaging (HARDI) in a cohort of twins comprising 328 subjects that included 70 pairs of monozygotic and 91 pairs of dizygotic twins. Water diffusion was modeled in each voxel with a Fiber Orientation Distribution (FOD) function to study heritability for multiple fiber orientations in each voxel. Precision was estimated in a test-retest experiment on a sub-cohort of 39 subjects. This was taken into account when computing heritability of FOD peaks using an ACE model on the monozygotic and dizygotic twins. Our results confirmed the overall heritability of the major white matter tracts but also identified differences in heritability between connectivity networks. Inter-hemispheric connections tended to be more heritable than intra-hemispheric and cortico-spinal connections. The highly heritable tracts were found to connect particular cortical regions, such as medial frontal cortices, postcentral, paracentral gyri, and the right hippocampus.

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.

MR image-based measurement of rates of change in volumes of brain structures. Part II: Application to a study of Alzheimer's disease and normal aging

We present global and regional rates of brain atrophy measured on serially acquired Tl-weighted brain MR images for a group of Alzheimer's disease (AD) patients and age-matched normal control (NC) subjects using the analysis procedure described in Part I. Three rates of brain atrophy: the rate of atrophy in the cerebrum, the rate of lateral ventricular enlargement and the rate of atrophy in the region of temporal lobes, were evaluated for 14 AD patients and 14 age-matched NC subjects. All three rates showed significant differences between the two groups. However, the greatest separation of the two groups was obtained when the regional rates were combined. This application has demonstrated that rates of brain atrophy, especially in specific regions of the brain, based on MR images can provide sensitive measures for evaluating the progression of AD. These measures will be useful for the evaluation of therapeutic effects of novel therapies for AD.

A reproducible method for automated extraction of brain volumes from 3D human head MR images

An automated method for extracting brain volumes from three commonly acquired three-dimensional (3D) MR images (proton density, T1 weighted, and T2-weighted) of the human head is described. The procedure is divided into four levels: preprocessing, segmentation, scalp removal, and postprocessing. A user-provided reference point is the sole operator-dependent input required. The method's parameters were first optimized and then fixed and applied to 30 repeat data sets from 15 normal older adult subjects to investigate its reproducibility. Percent differences between total brain volumes (TBVs) for the subjects' repeated data sets ranged from .5% to 2.2%. We conclude that the method is both robust and reproducible and has the potential for wide application.

Brain network efficiency and topology depend on the fiber tracking method: 11 tractography algorithms compared in 536 subjects

As connectivity analyses become more popular, claims are often made about how the brain's anatomical networks depend on age, sex, or disease. It is unclear how results depend on tractography methods used to compute fiber networks. We applied 11 tractography methods to high angular resolution diffusion images of the brain (4-Tesla 105-gradient HARDI) from 536 healthy young adults. We parcellated 70 cortical regions, yielding 70×70 connectivity matrices, encoding fiber density. We computed popular graph theory metrics, including network efficiency, and characteristic path lengths. Both metrics were robust to the number of spherical harmonics used to model diffusion (4th-8th order). Age effects were detected only for networks computed with the probabilistic Hough transform method, which excludes smaller fibers. Sex and total brain volume affected networks measured with deterministic, tensor-based fiber tracking but not with the Hough method. Each tractography method includes different fibers, which affects inferences made about the reconstructed networks.

Multiple stages classification of Alzheimer’s disease based on structural brain networks using generalized low rank approximations (GLRAM)

To classify each stage for a progressing disease such as Alzheimer’s disease is a key issue for the disease prevention and treatment. In this study, we derived structural brain networks from diffusion-weighted MRI using whole-brain tractography since there is growing interest in relating connectivity measures to clinical, cognitive, and genetic data. Relatively little work has usedmachine learning to make inferences about variations in brain networks in the progression of the Alzheimer’s disease. Here we developed a framework to utilize generalized low rank approximations of matrices (GLRAM) and modified linear discrimination analysis for unsupervised feature learning and classification of connectivity matrices. We apply the methods to brain networks derived from DWI scans of 41 people with Alzheimer’s disease, 73 people with EMCI, 38 people with LMCI, 47 elderly healthy controls and 221 young healthy controls. Our results show that this new framework can significantly improve classification accuracy when combining multiple datasets; this suggests the value of using data beyond the classification task at hand to model variations in brain connectivity.

Letter: Brain natriuretic peptide is a potentially useful screening tool for the detection of cardiovascular disease in patients with rheumatoid arthritis

Patients with rheumatoid arthritis (RA) have a significantly higher risk of coronary heart disease, despite being less likely to report symptoms of angina, and are more likely to experience unrecognised myocardial infarction and sudden cardiac death than non-RA controls.1 Furthermore, left ventricular diastolic dysfunction has been described in up to 40% of patients with RA.2...

Low temperature solar cooling system with absorption chiller and desiccant wheel

Nowadays Solar Cooling systems are becoming popular to reduce the carbon footprint of air conditioning. The use of an absorption chiller connected to solar thermal panels is increasing, but little study has been carried out to assess the advantage of join together an absorption chiller and a desiccant wheel to remove the sensible heat and the latent heat in different ways than the current design adopted in the industry. In this work I assess the possibility of implement a desiccant wheel in a conventional solar cooling system and the possibility of recovering the heat rejected by the absorption chiller which is then used for the regeneration of the desiccant wheel. The implementation of a desiccant wheel and the recovery of the heat rejected could provide a significant energy saving when compared to traditional solar cooling system. The results assist in the practical development of a solar cooling system which simultaneously uses absorption and adsorption technology.

Advanced CUBIC protocols for whole-brain and whole-body clearing and imaging

Here we describe a protocol for advanced CUBIC (Clear, Unobstructed Brain/Body Imaging Cocktails and Computational analysis). The CUBIC protocol enables simple and efficient organ clearing, rapid imaging by light-sheet microscopy and quantitative imaging analysis of multiple samples. The organ or body is cleared by immersion for 1–14 d, with the exact time required dependent on the sample type and the experimental purposes. A single imaging set can be completed in 30–60 min. Image processing and analysis can take <1 d, but it is dependent on the number of samples in the data set. The CUBIC clearing protocol can process multiple samples simultaneously. We previously used CUBIC to image whole-brain neural activities at single-cell resolution using Arc-dVenus transgenic (Tg) mice. CUBIC informatics calculated the Venus signal subtraction, comparing different brains at a whole-organ scale. These protocols provide a platform for organism-level systems biology by comprehensively detecting cells in a whole organ or body.

Evaluating the potential use of direct evaporative cooling in Australia

Greenhouse gas emissions and associated global climate change are a significant and growing concern for the world community. In order to improve building energy efficiency, the use of evaporative cooling systems is attracting growing attention. Using a climate assessment tool, the potential use of direct evaporative coolers over different Australian climates is evaluated. It is found that overall, the potential use of direct evaporative cooling is very significant in Australian climates. Among all the eight capital cities across Australia, except for Darwin, the need of hybrid cooling for other cities is found to be insignificant,and is less than 5% if appropriate air circulation is provided on hot/warm days. It is also found that the potential use of evaporative cooling can be significantly influenced by a change in the applications or design parameters. In Brisbane, it is estimated that with an increase of sensible cooling load from 30 W/m2 to 40 W/m2 in the conditioned space, the requirement in hours of hybrid cooling can increase significantly, from 4.06% to 14.89%.

Performance analysis of solar desiccant-evaporative cooling for a commercial building under different Australian climates

This paper evaluates and compares the system performance of a solar desiccant-evaporative cooling (SDEC) system with a referenced conventional variable air volume (VAV) system for a typical office building in all 8 Australian capital cities. A simulation model of the building is developed using the whole building simulation software EnergyPlus. The performance indicators for the comparison are system coefficient of performance (COP), annual primary energy consumption, annual energy savings, and annual CO2 emissions reduction. The simulation results show that Darwin has the most apparent advantages for SDEC system applications with an annual energy savings of 557 GJ and CO2 emission reduction of 121 tonnes. The maximum system COP is 7. For other climate zones such as Canberra, Hobart and Melbourne, the SDEC system is not as energy efficient as the conventional VAV system.

Physical activity cost in children following an acquired brain injury : a comparative study

Background: Alterations in energy expenditure during activity post head injury has not been investigated due primarily to the difficulty of measurement. Objective: The aim of this study was to compare energy expenditure during activity and body composition of children following acquired brain injury (ABI) with data from a group of normal controls. Design: Energy expenditure was measured using the Cosmed K4b2 in a group of 15 children with ABI and a group of 67 normal children during rest and when walking and running. Mean number of steps taken per 3 min run was also recorded and body composition was measured. Results: The energy expended during walking was not significantly different between both groups. A significant difference was found between the two groups in the energy expended during running and also for the number of steps taken as children with ABI took significantly less steps than the normal controls during a 3 min run. Conclusions: Children with ABI exert more energy per activity than healthy controls when controlled for velocity or distance. However, they expend less energy to walk and run when they are free to choose their own desirable, comfortable pace than normal controls. © 2003 Elsevier Ltd. All rights reserved.

Doctor’s knowledge and practices of traumatic brain injury management in Chinese prehospital settings

Objectives: The incidence and mortality of traumatic brain injury (TBI) has increased rapidly in the last decade in China. Appropriate ambulance service can reduce case-fatality rates of TBI significantly. This study aimed to explore the factors (age, gender, education level, clinical experience, professional title, organization, specialty before prehospital care, and training frequency) that could influence prehospital doctors’ knowledge level and practices in TBI management in China, Hubei Province. Methods: A cross-sectional questionnaire survey was conducted in two cities in Hubei Province. The self-administered questionnaire consisted of demographic information and questions about prehospital TBI management. Independent samples t-test and one-way ANOVA were used to analyze group differences in the average scores in terms of demographic character. General linear regression was used to explore associated factors in prehospital TBI management. Results: A total of 56 questionnaires were handed out and 52 (93%) were returned. Participants received the lowest scores in TBI treatment (0.64; SD=0.08) and the highest scores in TBI assessment (0.80; SD=0.14). According to the regression model, the education level was associated positively with the score of TBI identification (P=.019); participants who worked in the emergency department (ED; P=.011) or formerly practiced internal medicine (P=.009) tended to get lower scores in TBI assessment; participants’ scores in TBI treatment were associated positively with the training frequency (P=.011); and no statistically significant associated factor was found in the overall TBI management. Conclusion: This study described the current situation of prehospital TBI management. The prehospital doctors’ knowledge level and practices in TBI management were quantified and the influential factors hidden underneath were explored. The results indicated that an appropriate continuing medical education (CME) program enables improvement of the quality of ambulance service in China.