α-Adducin Gly460Trp Gene Mutation and Essential Hypertension in a Chinese Population: A Meta-Analysis including 10960 Subjects

BACKGROUND: The α-adducin Gly460Trp (G460W) gene polymorphism may be associated with susceptibility to essential hypertension (EH), but this relationship remains controversial. In an attempt to resolve this issue, we conducted a meta-analysis. METHODS: Twenty-three separated studies involving 5939 EH patients and 5021 controls were retrieved and analyzed. Four ethnicities were included: Han, Kazakh, Mongolian, and She. Eighteen studies with 5087 EH patients and 4183 controls were included in the Han subgroup. Three studies with 636 EH patients and 462 controls were included in the Kazakh subgroup. The Mongolian subgroup was represented by only one study with 100 EH patients and 50 controls; similarly, only one study with 116 EH patients and 326 controls was available for the She subgroup. The pooled and ethnic group odds ratios (ORs) along with the corresponding 95% confidence intervals (95% CI) were assessed using a random effects model. RESULTS: There was a significant association between the α-adducin G460W gene polymorphism and EH in the pooled Chinese population under both an allelic genetic model (OR: 1.12, 95% CI: 1.04-1.20, P = 0.002) and a recessive genetic model (OR: 1.40, 95% CI: 1.16-1.70, P = 0.0005). In contrast, no significant association between the α-adducin G460W gene polymorphism and EH was observed in the dominant genetic model (OR: 0.88, 95% CI: 0.72-1.09, P = 0.24). In stratified analysis by ethnicity, significantly increased risk was detected in the Han subgroup under an allelic genetic model (OR: 1.13, 95% CI: 1.04-1.23, P = 0.003) and a recessive genetic model (OR: 1.43, 95% CI: 1.17-1.75, P = 0.0006). CONCLUSIONS: In a Chinese population of mixed ethnicity, the α-adducin G460W gene polymorphism was linked to EH susceptibility, most strongly in Han Chinese

Modeling the Impact of Lesions in the Human Brain

Lesions of anatomical brain networks result in functional disturbances of brain systems and behavior which depend sensitively, often unpredictably, on the lesion site. The availability of whole-brain maps of structural connections within the human cerebrum and our increased understanding of the physiology and large-scale dynamics of cortical networks allow us to investigate the functional consequences of focal brain lesions in a computational model. We simulate the dynamic effects of lesions placed in different regions of the cerebral cortex by recording changes in the pattern of endogenous (“resting-state”) neural activity. We find that lesions produce specific patterns of altered functional connectivity among distant regions of cortex, often affecting both cortical hemispheres. The magnitude of these dynamic effects depends on the lesion location and is partly predicted by structural network properties of the lesion site. In the model, lesions along the cortical midline and in the vicinity of the temporo-parietal junction result in large and widely distributed changes in functional connectivity, while lesions of primary sensory or motor regions remain more localized. The model suggests that dynamic lesion effects can be predicted on the basis of specific network measures of structural brain networks and that these effects may be related to known behavioral and cognitive consequences of brain lesions

Large-Scale Brain Networks in Board Game Experts: Insights from a Domain-Related Task and Task-Free Resting State

Cognitive performance relies on the coordination of large-scale networks of brain regions that are not only temporally correlated during different tasks, but also networks that show highly correlated spontaneous activity during a task-free state. Both task-related and task-free network activity has been associated with individual differences in cognitive performance. Therefore, we aimed to examine the influence of cognitive expertise on four networks associated with cognitive task performance: the default mode network (DMN) and three other cognitive networks (central-executive network, dorsal attention network, and salience network). During fMRI scanning, fifteen grandmaster and master level Chinese chess players (GM/M) and fifteen novice players carried out a Chinese chess task and a task-free resting state. Modulations of network activity during task were assessed, as well as resting-state functional connectivity of those networks. Relative to novices, GM/Ms showed a broader task-induced deactivation of DMN in the chess problem-solving task, and intrinsic functional connectivity of DMN was increased with a connectivity pattern associated with the caudate nucleus in GM/Ms. The three other cognitive networks did not exhibit any difference in task-evoked activation or intrinsic functional connectivity between the two groups. These findings demonstrate the effect of long-term learning and practice in cognitive expertise on large-scale brain networks, suggesting the important role of DMN deactivation in expert performance and enhanced functional integration of spontaneous activity within widely distributed DMN-caudate circuitry, which might better support high-level cognitive control of behavior

Altered Effective Connectivity Network of the Amygdala in Social Anxiety Disorder: A Resting-State fMRI Study

The amygdala is often found to be abnormally recruited in social anxiety disorder (SAD) patients. The question whether amygdala activation is primarily abnormal and affects other brain systems or whether it responds “normally” to an abnormal pattern of information conveyed by other brain structures remained unanswered. To address this question, we investigated a network of effective connectivity associated with the amygdala using Granger causality analysis on resting-state functional MRI data of 22 SAD patients and 21 healthy controls (HC). Implications of abnormal effective connectivity and clinical severity were investigated using the Liebowitz Social Anxiety Scale (LSAS). Decreased influence from inferior temporal gyrus (ITG) to amygdala was found in SAD, while bidirectional influences between amygdala and visual cortices were increased compared to HCs. Clinical relevance of decreased effective connectivity from ITG to amygdala was suggested by a negative correlation of LSAS avoidance scores and the value of Granger causality. Our study is the first to reveal a network of abnormal effective connectivity of core structures in SAD. This is in support of a disregulation in predescribed modules involved in affect control. The amygdala is placed in a central position of dysfunction characterized both by decreased regulatory influence of orbitofrontal cortex and increased crosstalk with visual cortex. The model which is proposed based on our results lends neurobiological support towards cognitive models considering disinhibition and an attentional bias towards negative stimuli as a core feature of the disorder

Driving and Driven Architectures of Directed Small-World Human Brain Functional Networks

Recently, increasing attention has been focused on the investigation of the human brain connectome that describes the patterns of structural and functional connectivity networks of the human brain. Many studies of the human connectome have demonstrated that the brain network follows a small-world topology with an intrinsically cohesive modular structure and includes several network hubs in the medial parietal regions. However, most of these studies have only focused on undirected connections between regions in which the directions of information flow are not taken into account. How the brain regions causally influence each other and how the directed network of human brain is topologically organized remain largely unknown. Here, we applied linear multivariate Granger causality analysis (GCA) and graph theoretical approaches to a resting-state functional MRI dataset with a large cohort of young healthy participants (n = 86) to explore connectivity patterns of the population-based whole-brain functional directed network. This directed brain network exhibited prominent small-world properties, which obviously improved previous results of functional MRI studies showing weak small-world properties in the directed brain networks in terms of a kernel-based GCA and individual analysis. This brain network also showed significant modular structures associated with 5 well known subsystems: fronto-parietal, visual, paralimbic/limbic, subcortical and primary systems. Importantly, we identified several driving hubs predominantly located in the components of the attentional network (e.g., the inferior frontal gyrus, supplementary motor area, insula and fusiform gyrus) and several driven hubs predominantly located in the components of the default mode network (e.g., the precuneus, posterior cingulate gyrus, medial prefrontal cortex and inferior parietal lobule). Further split-half analyses indicated that our results were highly reproducible between two independent subgroups. The current study demonstrated the directions of spontaneous information flow and causal influences in the directed brain networks, thus providing new insights into our understanding of human brain functional connectome

Independent measure of the neutrino mixing angle θ13 via neutron capture on hydrogen at Daya Bay

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The muon system of the Daya Bay Reactor antineutrino experiment

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Search for a Light Sterile Neutrino at Daya Bay

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