Not lesser but Greater fractional anisotropy in adolescents with alcohol use disorders

AbstractObjectiveThe objective of this study is to examine white matter microstructure using diffusion tensor imaging (DTI) in a sample of adolescents with alcohol use disorders (AUD) and no psychiatric or substance co-morbidity.MethodsFifty adolescents with AUD and fifty non-alcohol abusing controls matched on gender and age were studied with DTI, neurocognitive testing, and a clinical assessment that included measures of alcohol use and childhood trauma. Maps of fractional anisotropy (FA) and mean diffusivity (MD) were computed, registered to a common template, and voxel-wise statistical analysis used to assess group differences. Associations between regions of altered WM microstructure and clinical or neurocognitive measures were also assessed.ResultsCompared with controls, adolescent drinkers without co-morbid substance abuse or externalizing disorder, showed 1) no regions of significantly lower FA, 2) increased FA in WM tracts of the limbic system; 3) no MD differences; and 4) within the region of higher FA in AUD, there were no associations between FA and alcohol use, cognition, or trauma.DiscussionThe most important observation of this study is our failure to observe significantly smaller FA in this relatively large alcohol abuse/dependent adolescent sample. Greater FA in the limbic regions observed in this study may index a risk for adolescent AUD instead of a consequence of drinking. Drinking behavior may be reinforced in those with higher FA and perhaps greater myelination in these brain regions involved in reward and reinforcement

The Irish potato famine pathogen Phytophthora infestans originated in central Mexico rather than the Andes

Phytophthora infestans is a destructive plant pathogen best known for causing the disease that triggered the Irish potato famine and remains the most costly potato pathogen to manage worldwide. Identification of P. infestan’s elusive center of origin is critical to understanding the mechanisms of repeated global emergence of this pathogen. There are two competing theories, placing the origin in either South America or in central Mexico, both of which are centers of diversity of Solanum host plants. To test these competing hypotheses, we conducted detailed phylogeographic and approximate Bayesian computation analyses, which are suitable approaches to unraveling complex demographic histories. Our analyses used microsatellite markers and sequences of four nuclear genes sampled from populations in the Andes, Mexico, and elsewhere. To infer the ancestral state, we included the closest known relatives Phytophthora phaseoli, Phytophthora mirabilis, and Phytophthora ipomoeae, as well as the interspecific hybrid Phytophthora andina. We did not find support for an Andean origin of P. infestans; rather, the sequence data suggest a Mexican origin. Our findings support the hypothesis that populations found in the Andes are descendants of the Mexican populations and reconcile previous findings of ancestral variation in the Andes. Although centers of origin are well documented as centers of evolution and diversity for numerous crop plants, the number of plant pathogens with a known geographic origin are limited. This work has important implications for our understanding of the coevolution of hosts and pathogens, as well as the harnessing of plant disease resistance to manage late blight.Keywords: coalescent analysis, biological invasion, oomycete, population genetics, stramenopil

EEG coherence related to fMRI resting state synchrony in long-term abstinent alcoholics

Recent work suggests that faulty co-activation or synchrony of multiple brain regions comprising “networks,” or an imbalance between opposing brain networks, is important in alcoholism. Previous studies showed higher fMRI resting state synchrony (RSS) within the executive control (inhibitory control and emotion regulation) networks and lower RSS within the appetitive drive network in long-term (multi-year) abstinent alcoholics (LTAA) vs. non substance abusing controls (NSAC). Our goal was to identify EEG networks that are correlated with the appetitive drive and executive function networks identified with fMRI in our previous alcohol studies. We used parallel ICA for multimodal data fusion for the 20 LTAA and 21 NSAC that had both usable fMRI and 64-channel EEG data. Our major result was that parallel ICA identified a pair of components that significantly separated NSAC from LTAA and were correlated with each other. Examination of the resting-state fMRI seed-correlation map component showed higher bilateral nucleus accumbens seed-correlation in the dorsolateral prefrontal cortex bilaterally and lower seed-correlation in the thalamus. This single component thus encompassed both the executive control and appetitive drive networks, consistent with our previous work. The correlated EEG coherence component showed mostly higher theta and alpha coherence in LTAA compared to NSAC, and lower gamma coherence in LTAA compared to NSAC. The EEG theta and alpha coherence results suggest enhanced top-down control in LTAA and the gamma coherence results suggest impaired appetitive drive in LTAA. Our results support the notion that fMRI RSS is reflected in spontaneous EEG, even when the EEG and fMRI are not obtained simultaneously. Keywords: Independent components analysis, Resting state, EEG, fMRI, Network

Reliability of tissue volumes and their spatial distribution for segmented magnetic resonance images

Abstract Before using MRI tissue segmentation in clinical studies as a dependent variable or as a means to correct functional data for differential tissue contribution, we must first establish the volume reliability and spatial distribution reproducibility of the segmentation method. Although several reports of volume reliability can be found in the literature, there are no articles assessing the reproducibility of the spatial distribution of tissue. In this report, we examine the validity, volume reliability, and spatial distribution reproducibility for our K-means cluster segmentation. Validation was examined by classifying gray matter, white matter, and CSF on images constructed using an MRI simulator and digital brain phantom, with percentage volume differences of less than 5% and spatial distribution overlaps greater than 0.94 (1.0 is perfect). We also segmented repeat scan MRIs from 10 healthy subjects, with intraclass correlation coefficients greater than 0.92 for cortical gray matter, white matter, sulcal CSF, and ventricular CSF. The original scans were also coregistered to the repeat scan of the same subject, and the spatial overlap for each tissue was then computed. Our overlaps ranged from 0.75 to 0.86 for these tissues. Our results support the use of K-means cluster segmentation, and the use of segmented structural MRIs to guide the analysis of functional and other images. 0 2001 Elsevier Science Ireland Ltd. All rights reserved

Voxel‐Wise Co‐analysis of Macro‐ and Microstructural Brain Alteration in Mild Cognitive Impairment and Alzheimer's Disease Using Anatomical and Diffusion MRI

Background and purposeTo determine if a voxel-wise "co-analysis" of structural and diffusion tensor magnetic resonance imaging (MRI) together reveals additional brain regions affected in mild cognitive impairment (MCI) and Alzheimer's disease (AD) than voxel-wise analysis of the individual MRI modalities alone.MethodsTwenty-one patients with MCI, 21 patients with AD, and 21 cognitively normal healthy elderly were studied with MRI. Maps of deformation and fractional anisotropy (FA) were computed and used as dependent variables in univariate and multivariate statistical models.ResultsUnivariate voxel-wise analysis of macrostructural changes in MCI showed atrophy in the right anterior temporal lobe, left posterior parietal/precuneus region, WM adjacent to the cingulate gyrus, and dorsolateral prefrontal regions, consistent with prior research. Univariate voxel-wise analysis of microstructural changes in MCI showed reduced FA in the left posterior parietal region extending into the corpus callosum, consistent with previous work. The multivariate analysis, which provides more information than univariate tests when structural and FA measures are correlated, revealed additional MCI-related changes in corpus callosum and temporal lobe.ConclusionThese results suggest that in corpus callosum and temporal regions macro- and microstructural variations in MCI can be congruent, providing potentially new insight into the mechanisms of brain tissue degeneration