DRUG DELIVERY STUDY OF SINGLE-WALL CARBON NANOTUBES COVALENT FUNCTIONALIZED WITH CISPLATIN

Carbon nanotubes are widely studied components for drug delivery systems due to their high surface area and low chemical reactivity. The research presented in this paper deals with the synthesis of drug delivery systems based on single walled carbon nanotubes (SWCNTs) and the well-known cancer treatment drug Cisplatin. The new nanomaterials obtained through covalent bonding between carboxyl groups from the SWCNTs surface and amino groups from the Cisplatin structure were characterized from structural point of view. To evaluate the content of drug released the Inductively Coupled Plasma Mass Spectrometry (ICP-MS) was employed. The releasing profile shows a slow rate in the beginning followed by a spectacular increase after 180 minutes which means that this type of system could be used for prolonged release

A Unified Functional Network Target for Deep Brain Stimulation in Obsessive-Compulsive Disorder

BACKGROUND: Multiple deep brain stimulation (DBS) targets have been proposed for treating intractable obsessive-compulsive disorder (OCD). Here, we investigated whether stimulation effects of different target sites would be mediated by one common or several segregated functional brain networks. METHODS: First, seeding from active electrodes of 4 OCD patient cohorts (N = 50) receiving DBS to anterior limb of the internal capsule or subthalamic nucleus zones, optimal functional connectivity profiles for maximal Yale-Brown Obsessive Compulsive Scale improvements were calculated and cross-validated in leave-one-cohort-out and leave-one-patient-out designs. Second, we derived optimal target-specific connectivity patterns to determine brain regions mutually predictive of clinical outcome for both targets and others predictive for either target alone. Functional connectivity was defined using resting-state functional magnetic resonance imaging data acquired in 1000 healthy participants. RESULTS: While optimal functional connectivity profiles showed both commonalities and differences between target sites, robust cross-predictions of clinical improvements across OCD cohorts and targets suggested a shared network. Connectivity to the anterior cingulate cortex, insula, and precuneus, among other regions, was predictive regardless of stimulation target. Regions with maximal connectivity to these commonly predictive areas included the insula, superior frontal gyrus, anterior cingulate cortex, and anterior thalamus, as well as the original stereotactic targets. CONCLUSIONS: Pinpointing the network modulated by DBS for OCD from different target sites identified a set of brain regions to which DBS electrodes associated with optimal outcomes were functionally connected-regardless of target choice. On these grounds, we establish potential brain areas that could prospectively inform additional or alternative neuromodulation targets for obsessive-compulsive disorder

What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from theENIGMABipolar Disorder Working Group

MRI‐derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta‐Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis‐driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large‐scale meta‐ and mega‐analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large‐scale, collaborative studies of mental illness

Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals

Fronto-limbic white matter (WM) abnormalities are assumed to lie at the heart of the pathophysiology of bipolar disorder (BD); however, diffusion tensor imaging (DTI) studies have reported heterogeneous results and it is not clear how the clinical heterogeneity is related to the observed differences. This study aimed to identify WM abnormalities that differentiate patients with BD from healthy controls (HC) in the largest DTI dataset of patients with BD to date, collected via the ENIGMA network. We gathered individual tensor-derived regional metrics from 26 cohorts leading to a sample size of N = 3033 (1482 BD and 1551 HC). Mean fractional anisotropy (FA) from 43 regions of interest (ROI) and average whole-brain FA were entered into univariate mega- and meta-analyses to differentiate patients with BD from HC. Mega-analysis revealed significantly lower FA in patients with BD compared with HC in 29 regions, with the highest effect sizes observed within the corpus callosum (R2 = 0.041, Pcorr < 0.001) and cingulum (right: R2 = 0.041, left: R2 = 0.040, Pcorr < 0.001). Lithium medication, later onset and short disease duration were related to higher FA along multiple ROIs. Results of the meta-analysis showed similar effects. We demonstrated widespread WM abnormalities in BD and highlighted that altered WM connectivity within the corpus callosum and the cingulum are strongly associated with BD. These brain abnormalities could represent a biomarker for use in the diagnosis of BD. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org

Photoluminescence of Ho3+ :YVO4 crystals

Emission spectra of Ho3+-doped YVO4 crystals are studied in the visible and infrared spectral regions. Be3+ sides the emission bands at 544 nm and at about 1950 and 2017 nm due to Ho, we observed a broad emission band at 6 10 nm at low temperatures like 15 K in the highly doped crystals with the Ho3+ concentrations of more than 0.5 mol %. The excitation band for this broad emission is located at 390 nm which is near the edge of band gap of the crystal. It is suggested that the 610 nm band is attributed to defects related to oxygen vacancies around V4+ ions. (c) 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

fMRI evidence for abnormal resting-state functional connectivity in euthymic bipolar patients

Background Neural substrates of bipolar disorder (BD) have frequently been characterized by dysregulation of fronto-limbic networks that may persist during euthymic periods. Only a few studies have investigated euthymic bipolar patients (BP) functional connectivity at rest. The current study aims to assess resting-state functional connectivity in euthymic BP in order to identify trait abnormalities responsible for enduring mood dysregulation in these patients. Methods Medial prefrontal cortex (mPFC) functional connectivity was investigated in 20 euthymic BP and 20 healthy subjects (HS). The functional connectivity maps were compared across groups using a between-group random effect analysis. Additional region of interest (ROI) analysis focused on mPFC–amygdala functional connectivity as well as correlations between the clinical features in euthymic BP was also conducted. Results A significant difference between euthymic BP and HS was observed in terms of connectivity between the mPFC and the right dorsolateral prefrontal cortex (dlPFC). A significant negative correlation between the activity of these regions was found in HS but not in euthymic BP. In addition, euthymic BP showed greater connectivity between mPFC and right amygdala compared to HS, which was also correlated with the duration of the disease. Limitations The BP group was heterogeneous with respect to the bipolarity subtype and the medication. The robustness of results could be improved with an increased sample size. Conclusions Compared to HS, the euthymic BP showed abnormal decoupling (decreased functional connectivity) activity between mPFC–dlPFC and hyperconnectivity (increased functional connectivity) and between mPFC and amygdala. These abnormalities could underlie the pathophysiology of BD, and may deteriorate further in accordance with disease duration

Cognition - the core of major depressive disorder

Cognitive deficits have been only recently recognized as a major phenotype determinant of major depressive disorder, although they are an integral part of the definition of the depressive state. Congruent evidence suggest that these cognitive deficits persist beyond the acute phase and may be identified at all ages. The aim of the current study was to review the main meta-analyses on cognition and depression, which encompasses a large range of cognitive domains. Therefore, we discuss the "cold" (attention, memory, executive functions) and "hot" (emotional bias) cognitive impairments in MDD, as well as those of social cognition domains (empathy, theory of mind). Several factors interfere with cognition in MDD such as clinical (melancholic, psychotic...) features, age, age of onset, illness severity, medication and comorbid condition. As still debated in the literature, the type of relationship between the severity of cognitive symptoms and functioning in depression is detailed, thus highlighting their predictive value of functional outcome, independently of the affective symptoms. A better identification of the cognitive deficits in MDD and a monitoring of the effects of different treatments require appropriate instruments, which may be developed by taking advantage of the increasing success of computing tools. Overall, current data suggest a core role for different cognitive deficits in MDD, therefore opening new perspectives for optimizing the treatment of depression