Functional magnetic resonance data acquired in a task-absent condition (“resting state”) require new data analysis techniques that do not depend on an activation model. In this work, we introduce an alternative assumption- and parameter-free method based on a particular form of node centrality called eigenvector centrality. Eigenvector centrality attributes a value to each voxel in the brain such that a voxel receives a large value if it is strongly correlated with many other nodes that are themselves central within the network. Google's PageRank algorithm is a variant of eigenvector centrality. Thus far, other centrality measures - in particular “betweenness centrality” - have been applied to fMRI data using a pre-selected set of nodes consisting of several hundred elements. Eigenvector centrality is computationally much more efficient than betweenness centrality and does not require thresholding of similarity values so that it can be applied to thousands of voxels in a region of interest covering the entire cerebrum which would have been infeasible using betweenness centrality. Eigenvector centrality can be used on a variety of different similarity metrics. Here, we present applications based on linear correlations and on spectral coherences between fMRI times series. This latter approach allows us to draw conclusions of connectivity patterns in different spectral bands. We apply this method to fMRI data in task-absent conditions where subjects were in states of hunger or satiety. We show that eigenvector centrality is modulated by the state that the subjects were in. Our analyses demonstrate that eigenvector centrality is a computationally efficient tool for capturing intrinsic neural architecture on a voxel-wise level.
The stability of ethyl glucuronide (EtG) under conditions of degradation was examined in urine samples of nine volunteers and in post-mortem tissue (liver, skeletal muscle) and blood taken from seven corpses at autopsies. Analysis was performed via LC-MS/MS. EtG concentrations in urine samples ranged from 2.5 to 296.5 mg/l. When stored at 4 degrees C in airtight test tubes, EtG concentrations remained relatively constant; when stored at room temperature (RT) for 5 weeks in ventilated vials, variations of EtG concentrations ranged from a 30% decrease to an 80% increase, with an average of 37.5% increase. Liver and skeletal muscle tissue of three corpses with positive blood alcohol concentrations (BAC; ranging from 0.106 to 0.183 g%) were stored for 4 weeks and analysed periodically. EtG concentrations decreased 27.7% on average in 4 weeks storage at RT but EtG was still detectable in all samples with initial EtG concentrations higher than 1 mug/g. Blood and liver samples of four corpses with negative BACs were stored at RT after addition of 0.1 g% ethanol, and no new formation of EtG was observed.
In recent years, knowledge about hormonal feedback from the gastrointestinal tract and adipose tissue has increased tremendously. Peptide hormones modulating hunger have been intensively studied, mostly in animals but increasingly also in humans. The first therapeutic agents, such as GLP-1 analogues, are in successful clinical use for T2D and may beneficially affect hunger and reduce weight. Data from in vitro studies and animals provide detailed insight into regulatory mechanisms leading to peptide secretion and receptor bindings, as well as to the distribution of receptors involved in different parts of the body. With neuroimaging techniques human brain structures have been identified that play a role in hunger, satiety and eating behaviour. These include the primary gustatory (insular) and olfactory (pyriform) cortex and regions with a highly permeable blood-brain barrier (hypothalamus, brain stem), which facilitates humoral input via gut peptides and leptin. In addition, cerebral networks involved in higher cognitive functions, especially those relevant to reward, pleasure and also addiction (ventral and dorsal striatum, amygdala, orbitofrontal cortex (OFC), prefrontal cortex (PFC)) were shown to be involved. First indications of direct influences of peptide hormones on these networks have become available from neuroimaging studies administrating synthetic PYY, ghrelin and leptin. Insulin also appears to play an important role as a central satiety hormone, and evidence indicating the possibility of central insulin resistance in obesity is available.
Obesity is associated with genetic and environmental factors but the underlying mechanisms remain poorly understood. Recent genome-wide association studies (GWAS) identified obesity- and type 2 diabetes-associated genetic variants located within or near genes that modulate brain activity and development. Among the top hits is rs17782313 near MC4R, encoding for the melanocortin-4-receptor, which is expressed in brain regions that regulate eating. Here, we hypothesized rs17782313-associated changes in human brain regions that regulate eating behavior. Therefore, we examined effects of common variants at rs17782313 near MC4R on brain structure and eating behavior. Only in female homozygous carriers of the risk allele we found significant increases of gray matter volume (GMV) in the right amygdala, a region known to influence eating behavior, and the right hippocampus, a structure crucial for memory formation and learning. Further, we found bilateral increases in medial orbitofrontal cortex, a multimodal brain structure encoding the subjective value of reinforcers, and bilateral prefrontal cortex, a higher order regulation area. There was no association between rs17782313 and brain structure in men. Moreover, among female subjects only, we observed a significant increase of ‘disinhibition’, and, more specifically, on ‘emotional eating’ scores of the Three Factor Eating Questionnaire in carriers of the variant rs17782313’s risk allele. These findings suggest that rs17782313’s effect on eating behavior is mediated by central mechanisms and that these effects are sex-specific.
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