Notes

Preoperative look at neurovascular interactions pertaining to microvascular decompression: Visualization making use of Brainvis within individuals using idiopathic trigeminal neuralgia.
Glutathione (GSH) and GSH/glutathione peroxidase (GPX) enzyme system is essential for normal intracellular homeostasis and gets disturbed under pathophysiologic conditions including endothelial dysfunction. Overproduction of reactive oxidative species (ROS) and reactive nitrogen species (RNS) including superoxide (O2•-), and the loss of nitric oxide (NO) bioavailability is a characteristic of endothelial dysfunction. The GSH/GPX system play an important role in eliminating ROS/RNS. Studies have provided important information regarding the interactions of ROS/RNS with the GSH/GPX in biological systems; however, it is not clear how this cross talk affect these reactive species and GSH/GPX enzyme system, under physiologic and oxidative/nitrosative stress conditions. In the present study, we developed a detailed endothelial cell kinetic model to understand the relationship amongst the key enzyme systems including GSH, GPX, peroxiredoxin (Prx) and reactive species, such as hydrogen peroxide (H2O2), peroxynitrite (ONOO-), and dinitrogen trioxide (N2O3). Our simulation results showed that the alterations in the generation rates of O2•- and NO led to the formation of a wide range of ROS and RNS. Simulations performed by varying the ratio of O2•- to NO generation rates as well as GSH and GPX concentrations showed that the GPX reducing capacity was dependent on GSH availability, level of oxidative/nitrosative stress, and can be attributed to N2O3 levels, but not to H2O2 and ONOO-. Our results showed that N2O3 mediated switch-like depletion in GSH and the incorporation of Prx had no considerable effect on the ROS/RNS species other than ONOO- and H2O2. The analysis presented in this study will improve our understanding of vascular diseases in which the levels and oxidation states of GSH, GPX and/or Prx are significantly altered and pharmacological interventions show limited benefits. BACKGROUND Antipsychotics, especially most of the second-generation antipsychotics, have a high risk for metabolic syndrome and antipsychotic-induced weight gain (AIWG). A promoter variant of the leptin (LEP) gene, -2548G/A (rs7799039), has been associated with AIWG in several studies. read more The aim of this study was to evaluate this association in the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) sample, followed by meta-analysis. METHODS We investigated the association between rs7799039 and AIWG in a sub-sample of European (N = 164) individuals from the CATIE study. Body mass index (BMI) change and weight gain (presence or absence) was analyzed using ANCOVA and logistic regression, respectively. For the meta-analysis, a literature search was conducted using MEDLINE, Embase, and PsycINFO up to October 2019. The pooled odds ratio was calculated for presence or absence of weight gain (≥7% weight change) using a random effects model. RESULTS We did not detect an association between rs7799039 and BMI change or weight gain (presence or absence) in the CATIE sample. As for the meta-analysis, we included 12 studies. No significant associations between the LEP rs7799039 polymorphism and AIWG were observed under the allelic genetic model (allele A vs. allele G) (OR = 1.10 [0.71, 1.70], p = .68). In the subgroup analyses of first-episode schizophrenia patients, a significant association between the A-allele and weight gain was observed, respectively (OR = 2.32 [1.41, 3.82], p = .0009). CONCLUSIONS The present meta-analysis showed no significant effect of rs7799039 on AIWG. link2 However, this variant may influence AIWG in first-episode schizophrenia patients. Further investigation of a larger and more homogenous sample is required to elucidate the role of the LEP gene in AIWG. OBJECTIVE Major depressive disorder (MDD) is a neuropsychiatric disorder associated with functional dysconnectivity in emotion regulation system. State characteristics which measure the current presence of depressive symptoms, and trait characteristics which indicate the long-term vulnerability to depression are two important features of MDD. However, the relationships between trait and state characteristics of MDD and functional connectivity (FC) within the emotion regulation system still remain unclear. METHODS This study aims to examine the neural biological mechanisms of trait characteristics measured by the Affective Neuroscience Personality Scale (ANPS) and state anhedonia measured by the Snaith-Hamilton Pleasure Scale (SHAPS) in MDD. Sixty-three patients with MDD and 63 well-matched healthy controls (HCs) underwent resting-state functional magnetic resonance imaging. A spatial pairwise clustering and the network-based analysis approaches were adopted to identify the abnormal FC networks. Support vector regression was utilized to predict the trait and state characteristics based on abnormal FCs. RESULTS Four disrupted subnetworks mainly involving the prefrontal-limbic-striatum system were observed in MDD. Importantly, the abnormal FC between the left amygdala (AMYG)/hippocampus (HIP) and right AMYG/HIP could predict the SADNESS scores of ANPS (trait characteristics) in MDD. While the aberrant FC between the medial prefrontal cortex (mPFC)/anterior cingulate gyrus (ACC) and AMYG/parahippocampal gyrus could predict the state anhedonia scores (state characteristics). CONCLUSIONS The present findings give first insights into the neural biological basis underlying the trait and state characteristics associated with functional dysconnectivity within the emotion regulation system in MDD. Accumulating evidence indicates that patients with severe mental disorders, including major depression, bipolar disorder and schizophrenia present with various alterations of the gut microbiota and increased intestinal permeability. link3 In addition, the hypothalamic-pituitary-adrenal (HPA) axis dysregulation and subclinical inflammation have been reported in this group of patients. Although it has been found that the HPA axis dysregulation appears as a consequence of psychosocial stress, especially traumatic life events, the exact mechanisms of this observation remain unclear. Animal model studies have unraveled several mechanisms linking the gut microbiota with the HPA axis dysfunction. Indeed, the gut microbiota can activate the HPA axis through several mediators that cross the blood-brain barrier and include microbial antigens, cytokines and prostaglandins. There is also evidence that various microbial species can affect ileal corticosterone production that may impact the activity of the HPA axis. However, some metabolites released by various microbes, e.g., short-chain fatty acids, can attenuate the HPA axis response. Moreover, several bacteria release neurotransmitters that can directly interact with vagal afferents. It has been postulated that the HPA axis activation can impact the gut microbiota and intestinal permeability. In this article, we discuss various mechanisms linking the gut microbiota with the HPA axis activity and summarize current evidence for a cross-talk between the gut-brain axis and the HPA axis from studies of patients with mood and psychotic disorders. Finally, we show potential clinical implications that can arise from future studies investigating the HPA axis activity with respect to the gut microbiota in severe mental disorders. Functional brain networks are shaped and constrained by the underlying structural network. However, functional networks are not merely a one-to-one reflection of the structural network. Several theories have been put forward to understand the relationship between structural and functional networks. However, it remains unclear how these theories can be unified. Two existing recent theories state that 1) functional networks can be explained by all possible walks in the structural network, which we will refer to as the series expansion approach, and 2) functional networks can be explained by a weighted combination of the eigenmodes of the structural network, the so-called eigenmode approach. To elucidate the unique or common explanatory power of these approaches to estimate functional networks from the structural network, we analysed the relationship between these two existing views. Using linear algebra, we first show that the eigenmode approach can be written in terms of the series expansion approach, i.e., wathese results provide an important step towards unification of existing theories regarding the structure-function relationships in brain networks. The quantification of brain white matter properties is a key area of application of Magnetic Resonance Imaging (MRI), with much effort focused on using MR techniques to quantify tissue microstructure. While diffusion MRI probes white matter (WM) microstructure by characterising the sensitivity of Brownian motion of water molecules to anisotropic structures, susceptibility-based techniques probe the tissue microstructure by observing the effect of interaction between the tissue and the magnetic field. Here, we unify these two complementary approaches by combining ultra-strong (300 mT/m) gradients with a novel Diffusion-Filtered Asymmetric Spin Echo (D-FASE) technique. Using D-FASE we can separately assess the evolution of the intra- and extra-axonal signals under the action of susceptibility effects, revealing differences in the behaviour in different fibre tracts. We observed that the effective relaxation rate of the ASE signal in the corpus callosum decreases with increasing b-value in all subjects (from 17.1±0.7s-1 at b=0s/mm2 to 14.6±0.7s-1 at b=4800s/mm2), while this dependence on b in the corticospinal tract is less pronounced (from 12.0±1.1s-1 at b=0s/mm2 to 10.7±0.5s-1 at b=4800s/mm2 ). Voxelwise analysis of the signal evolution with respect to b-factor and acquisition delay using a microscopic model demonstrated differences in gradient echo signal evolution between the intra- and extra-axonal pools. Corpus callosum dysgenesis (CCD) is a developmental brain condition in which some white matter fibers fail to find their natural course across the midplane, reorganizing instead to form new aberrant pathways. This type of white matter reorganization is known as long-distance plasticity (LDP). The present work aimed to characterize the Balb/c mouse strain as a model of CCD. We employed high-resolution anatomical MRI in 81 Balb/c and 27 C57bl6 mice to show that the Balb/c mouse strain presents a variance in the size of the CC that is 3.9 times higher than the variance of normotypical C57bl6. We also performed high-resolution diffusion-weighted imaging (DWI) in 8 Balb/c and found that the Balb/c strain shows aberrant white matter bundles, such as the Probst (5/8 animals) and the Sigmoid bundles (7/8 animals), which are similar to those found in humans with CCD. Using a histological tracer technique, we confirmed the existence of these aberrant bundles in the Balb/c strain. Interestingly, we also identified sigmoid-like fibers in the C57bl6 strain, thought to a lesser degree. Next, we used a connectome approach and found widespread brain connectivity differences between Balb/c and C57bl6 strains. The Balb/c strain also exhibited increased variability of global connectivity. These findings suggest that the Balb/c strain presents local and global changes in brain structural connectivity. This strain often presents with callosal abnormalities, along with the Probst and the Sigmoid bundles, making it is an attractive animal model for CCD and LDP in general. Our results also show that even the C57bl6 strain, which typically serves as a normotypical control animal in a myriad of studies, presents sigmoid-fashion pattern fibers laid out in the brain. These results suggest that these aberrant fiber pathways may not necessarily be a pathological hallmark, but instead an alternative roadmap for misguided axons. Such findings offer new insights for interpreting the significance of CCD-associated LDP in humans.
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