Diagnosis, Assessment, and Treatment of Non-Pulmonary Arterial Hypertension Pulmonary Hypertension

The 4th World Symposium on Pulmonary Hypertension was the first international meeting to focus not only on pulmonary arterial hypertension (PAH) but also on the so-called non-PAH forms of pulmonary hypertension (PH). The term ""non-PAH PH"" summarizes those forms of PH that are found in groups 2 to 5 of the current classification of PH, that is, those forms associated with left heart disease, chronic lung disease, recurrent venous thromboembolism, and other diseases. Many of these forms of PH are much more common than PAH, but all of them have been less well studied, especially in terms of medical therapy. The working group on non-PAH PH focused mainly on 4 conditions: chronic obstructive lung disease, interstitial lung disease, chronic thromboembolic PH, and left heart disease. The medical literature regarding the role of PH in these diseases was reviewed, and recommendations regarding diagnosis and treatment of PH in these conditions are provided. Given the lack of robust clinical trials addressing PH in any of these conditions, it is important to conduct further studies to establish the role of medical therapy in non-PAH PH. (J Am Coll Cardiol 2009;54:S85-96) (C) 2009 by the American College of Cardiology Foundation

AP-1 and Egr DNA-binding activities are increased in rat brain during ethanol withdrawal

The DNA-binding activities of AP-1 and Egr proteins were investigated in nuclear extracts of rat brain regions during ethanol withdrawal. Both DNA-binding activities were transiently elevated in the hippocampus and cerebellum 16 h after withdrawal. In the cerebral cortex, AP-1 and Egr DNA-binding activities increased at 16 h and persisted until 32 and 72 h, respectively. The AP-1 DNA-binding activities in all regions at all times after withdrawal were composed of FosB, c-Jun, JunB, and JunD. c-Fos was detected at all times in the cerebral cortex, at 16 h only in the hippocampus, and from 16 to 72 h in the cerebellum. Withdrawal severity did not affect the composition of the AP-1 DNA-binding activities. Two Egr DNA-binding activities were present in the cortex and hippocampus. The faster-migrating complex predominated in hippocampus, and only the slower-migrating complex (identified as Egr-1) was present in the cerebellum. The increase in DNA-binding activity of immediate early gene-encoded transcription factors supports their proposed role in initiating a cascade of altered gene expression underlying the long-term neuronal response to ethanol withdrawal.

AT(1) receptor participates in the cardiac hypertrophy induced by resistance training in rats

Resistance training is accompanied by cardiac hypertrophy, but the role of the renin-angiotensin system (RAS) in this response is elusive. We evaluated this question in 36 male Wistar rats divided into six groups: control (n = 6); trained (n = 6); control + losartan (10 mg.kg(-1).day(-1), n = 6); trained + losartan (n = 6); control + high-salt diet (1%, n = 6); and trained + high-salt diet (1%, n = 6). High salt was used to inhibit the systemic RAS and losartan to block the AT(1) receptor. The exercise protocol consisted of: 4 x 12 bouts, 5x/wk during 8 wk, with 65-75% of one repetition maximum. Left ventricle weight-to-body weight ratio increased only in trained and trained + high-salt diet groups (8.5% and 10.6%, P < 0.05) compared with control. Also, none of the pathological cardiac hypertrophy markers, atrial natriuretic peptide, and alpha MHC (alpha-myosin heavy chain)-to-beta MHC ratio, were changed. ACE activity was analyzed by fluorometric assay (systemic and cardiac) and plasma renin activity (PRA) by RIA and remained unchanged upon resistance training, whereas PRA decreased significantly with the high-salt diet. Interestingly, using Western blot analysis and RT-PRC, no changes were observed in cardiac AT(2) receptor levels, whereas the AT(1) receptor gene (56%, P < 0.05) and protein (31%, P < 0.05) expressions were upregulated in the trained group. Also, cardiac ANG II concentration evaluated by ELISA remained unchanged (23.27 +/- 2.4 vs. 22.01 +/- 0.8 pg/mg, P > 0.05). Administration of a subhypotensive dose of losartan prevented left ventricle hypertrophy in response to the resistance training. Altogether, we provide evidence that resistance training-induced cardiac hypertrophy is accompanied by induction of AT(1) receptor expression with no changes in cardiac ANG II, which suggests a local activation of the RAS consistent with the hypertrophic response.

Immediate early gene expression and delayed cell death in limbic areas of the rat brain after kainic acid treatment and recovery in the cold

Systemic injection of kainic acid (KA) results in characteristic behaviors and programmed cell death in some regions of the rat brain. We used KA followed by recovery at 4 degrees C to restrict damage to limbic structures and compared patterns of immediate early gene (IEG) expression and associated DNA binding activity in these damaged areas with that in spared brain regions. Male Wistar rats were injected with BA (12 mg/kg, ip) and kept at 4 degrees C for 5 h. This treatment reduced the severity of behaviors and restricted damage (observed by Nissl staining) to the CA1 and CA3 regions of the hippocampus and an area including the entorhinal cortex. DNA laddering, characteristic of apoptosis, was first evident in the hippocampus and the entorhinal cortex 18 and 22 h after RA, respectively. The pattern of IEG mRNA induction fell into three classes: IEGs that were induced in both damaged and spared areas (c-fos, fos B, jun B, and egr-1), IEGs that were induced specifically in the damaged areas (fra-2 and c-jun), and an IEG that was significantly induced by saline injection and/or the cold treatment (jun D). The pattern of immunoreactivity closely followed that of mRNA expression. Binding to the AP-1 and EGR DNA consensus sequences increased in all three regions studied. This study describes a unique modification of the animal model of ICA-induced neurotoxicity which may prove a useful tool for dissecting the molecular cascade that ultimately results in programmed cell death. (C) 1997 Academic Press.

rTMS treatment for depression in Parkinson`s disease increases BOLD responses in the left prefrontal cortex

The mechanisms underlying the effects of antidepressant treatment in patients with Parkinson`s disease (PD) are unclear. The neural changes after successful therapy investigated by neuroimaging methods can give insights into the mechanisms of action related to a specific treatment choice. To study the mechanisms of neural modulation of repetitive transcranial magnetic Stimulation (rTMS) and fluoxetine, 21 PD depressed patients were randomized into only two active treatment groups for 4 wk: active rTMS over left dorsolateral prefrontal cortex (DLPFC) (5 Hz rTMS; 120% motor threshold) with placebo pill and sham rTMS with fluoxetine 20mg/d. Event-related functional magnetic resonance imaging (fMRI) with emotional stimuli was performed before and after treatment - in two sessions (test and re-test) at each time-point. The two groups of treatment had a significant, similar mood improvement. After rTMS treatment, there were brain activity decreases in left fusiform gyrus, cerebellum and right DLPFC and brain activity increases in left DLPFC and anterior cingulate gyrus compared to baseline. In contrast, after fluoxetine treatment, there were brain activity increases in right premotor and right medial prefrontal cortex. There was a significant interaction effect between groups vs. time in the left medial prefrontal cortex, suggesting that the activity in this area changed differently in the two treatment groups. Our findings show that antidepressant effects of rTMS and fluoxetine in PD are associated with changes in different areas of the depression-related neural network.

Volume reduction of the corpus callosum and its relationship with deficits in interhemispheric transfer of information in recent-onset psychosis

The present study aimed to investigate the presence of corpus callosum (CC) volume deficits in a population-based recent-onset psychosis (ROP) sample, and whether CC volume relates to interhemispheric communication deficits. For this purpose, we used voxel-based morphometry comparisons of magnetic resonance imaging data between ROP (n = 122) and healthy control (n = 94) subjects. Subgroups (38 ROP and 39 controls) were investigated for correlations between CC volumes and performance on the Crossed Finger Localization Test (CFLT). Significant CC volume reductions in ROP subjects versus controls emerged after excluding substance misuse and non-right-handedness. CC reductions retained significance in the schizophrenia subgroup but not in affective psychoses subjects. There were significant positive correlations between CC volumes and CFLT scores in ROP subjects, specifically in subtasks involving interhemispheric communication. From these results, we can conclude that CC volume reductions are present in association with ROP. The relationship between such deficits and CFLT performance suggests that interhemispheric communication impairments are directly linked to CC abnormalities in ROP. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

Neural activity changes to emotional stimuli in healthy individuals under chronic use of clomipramine

Previous functional magnetic resonance imaging (fMRI) studies examined neural activity responses to emotive stimuli in healthy individuals after acute/subacute administration of antidepressants. We now report the effects of repeated use of the antidepressant clomipramine on fMRI data acquired during presentation of emotion-provoking and neutral stimuli on healthy volunteers. A total of 12 volunteers were evaluated with fMRI after receiving low doses of clomipramine for 4 weeks and again after 4 weeks of washout. Fear-, happiness-, anger-provoking and neutral pictures from the International Affective Picture System (IAPS) were used. Data analysis was performed with statistical parametric mapping (P < 0.05). Paired t-test comparisons for each condition between medicated and unmedicated states showed, to negative valence paradigms, decrease in brain activity in the amygdala when participants were medicated. We also demonstrated, across both positive and negative valence paradigms, consistent decreases in brain activity in the medicated state in the anterior cingulate gyrus and insula. This is the first report of modulatory effects of repeated antidepressant use on the central representation of somatic states in response to emotions of both negative and positive valences in healthy individuals. Also, our results corroborate findings of antidepressant-induced temporolimbic activity changes to emotion-provoking stimuli obtained in studies of subjects treated acutely with such agents.

Characterization of Superparamagnetic Iron Oxide Coated with Silicone Used as Contrast Agent for Magnetic Resonance Image for the Gastrointestinal Tract

The present work is a report of the characterization of superparamagnetic iron oxide nanoparticles coated with silicone used as a contrast agent in magnetic resonance imaging of the gastrointestinal tract. The hydrodynamic size of the contrast agent is 281.2 rim, where it was determined by transmission electron microscopy and a Fe(3)O(4) crystalline structure was identified by X-ray diffraction, also confirmed by Mossbauer Spectroscopy. The blocking temperature of 190 K was determined from magnetic measurements based on the Zero Field Cooled and Field Cooled methods. The hysteresis loops were measured at different temperatures below and above the blocking temperature. Ferromagnetic resonance analysis indicated the superparamagnetic nature of the nanoparticles and a strong temperature dependence of the peak-to-peak linewidth Delta H(pp), giromagnetic factor g, number of spins N(S) and relaxation time T(2) were observed. This behavior can be attributed to an increase in the superexchange interaction.

Use of SVM Methods with Surface-Based Cortical and Volumetric Subcortical Measurements to Detect Alzheimer`s Disease

Here, we examine morphological changes in cortical thickness of patients with Alzheimer`s disease (AD) using image analysis algorithms for brain structure segmentation and study automatic classification of AD patients using cortical and volumetric data. Cortical thickness of AD patients (n = 14) was measured using MRI cortical surface-based analysis and compared with healthy subjects (n = 20). Data was analyzed using an automated algorithm for tissue segmentation and classification. A Support Vector Machine (SVM) was applied over the volumetric measurements of subcortical and cortical structures to separate AD patients from controls. The group analysis showed cortical thickness reduction in the superior temporal lobe, parahippocampal gyrus, and enthorhinal cortex in both hemispheres. We also found cortical thinning in the isthmus of cingulate gyrus and middle temporal gyrus at the right hemisphere, as well as a reduction of the cortical mantle in areas previously shown to be associated with AD. We also confirmed that automatic classification algorithms (SVM) could be helpful to distinguish AD patients from healthy controls. Moreover, the same areas implicated in the pathogenesis of AD were the main parameters driving the classification algorithm. While the patient sample used in this study was relatively small, we expect that using a database of regional volumes derived from MRI scans of a large number of subjects will increase the SVM power of AD patient identification.

Depression in Parkinson`s disease: Convergence from voxel-based morphometry and functional magnetic resonance imaging in the limbic thalamus

Depression is the most frequent psychiatric disorder in Parkinson`s disease (PD). Although evidence Suggests that depression in PD is related to the degenerative process that underlies the disease, further studies are necessary to better understand the neural basis of depression in this population of patients. In order to investigate neuronal alterations underlying the depression in PD, we studied thirty-six patients with idiopathic PD. Twenty of these patients had the diagnosis of major depression disorder and sixteen did not. The two groups were matched for PD motor severity according to Unified Parkinson Disease Rating Scale (UPDRS). First we conducted a functional magnetic resonance imaging (fMRI) using an event-related parametric emotional perception paradigm with test retest design. Our results showed decreased activation in the left mediodorsal (MD) thalamus and in medial prefrontall cortex in PD patients with depression compared to those without depression. Based upon these results and the increased neuron count in MD thalamus found in previous studies, we conducted a region of interest (ROI) guided voxel-based morphometry (VBM) study comparing the thalamic volume. Our results showed an increased volume in mediodorsal thalamic nuclei bilaterally. Converging morphological changes and functional emotional processing in mediodorsal thalamus highlight the importance of limbic thalamus in PD depression. In addition this data supports the link between neurodegenerative alterations and mood regulation. (C) 2009 Elsevier Inc. All rights reserved.

Improved detection of incipient vascular changes by a biotechnological platform combining post mortem MRI in situ with neuropathology

The histopathological counterpart of white matter hyperintensities is a matter of debate. Methodological and ethical limitations have prevented this question to be elucidated. We want to introduce a protocol applying state-of-the-art methods in order to solve fundamental questions regarding the neuroimaging-neuropathological uncertainties comprising the most common white matter hyperintensities [WMHs] seen in aging. By this protocol, the correlation between signal features in in situ, post mortem MRI-derived methods, including DTI and MTR and quantitative and qualitative histopathology can be investigated. We are mainly interested in determining the precise neuroanatomical substrate of incipient WMHs. A major issue in this protocol is the exact co-registration of small lesion in a tridimensional coordinate system that compensates tissue deformations after histological processing. The protocol is based on four principles: post mortem MRI in situ performed in a short post mortem interval, minimal brain deformation during processing, thick serial histological sections and computer-assisted 3D reconstruction of the histological sections. This protocol will greatly facilitate a systematic study of the location, pathogenesis, clinical impact, prognosis and prevention of WMHs. (C) 2009 Elsevier B.V. All rights reserved.

Hyperdopaminergia and NMDA Receptor Hypofunction Disrupt Neural Phase Signaling

Neural phase signaling has gained attention as a putative coding mechanism through which the brain binds the activity of neurons across distributed brain areas to generate thoughts, percepts, and behaviors. Neural phase signaling has been shown to play a role in various cognitive processes, and it has been suggested that altered phase signaling may play a role in mediating the cognitive deficits observed across neuropsychiatric illness. Here, we investigated neural phase signaling in two mouse models of cognitive dysfunction: mice with genetically induced hyperdopaminergia [dopamine transporter knock-out (DAT-KO) mice] and mice with genetically induced NMDA receptor hypofunction [NMDA receptor subunit-1 knockdown (NR1-KD) mice]. Cognitive function in these mice was assessed using a radial-arm maze task, and local field potentials were recorded from dorsal hippocampus and prefrontal cortex as DAT-KO mice, NR1-KD mice, and their littermate controls engaged in behavioral exploration. Our results demonstrate that both DAT-KO and NR1-KD mice display deficits in spatial cognitive performance. Moreover, we show that persistent hyperdopaminergia alters interstructural phase signaling, whereas NMDA receptor hypofunction alters interstructural and intrastructural phase signaling. These results demonstrate that dopamine and NMDA receptor dependent glutamate signaling play a critical role in coordinating neural phase signaling, and encourage further studies to investigate the role that deficits in phase signaling play in mediating cognitive dysfunction.

Evaluating SVM and MLDA in the extraction of discriminant regions for mental state prediction

Pattern recognition methods have been successfully applied in several functional neuroimaging studies. These methods can be used to infer cognitive states, so-called brain decoding. Using such approaches, it is possible to predict the mental state of a subject or a stimulus class by analyzing the spatial distribution of neural responses. In addition it is possible to identify the regions of the brain containing the information that underlies the classification. The Support Vector Machine (SVM) is one of the most popular methods used to carry out this type of analysis. The aim of the current study is the evaluation of SVM and Maximum uncertainty Linear Discrimination Analysis (MLDA) in extracting the voxels containing discriminative information for the prediction of mental states. The comparison has been carried out using fMRI data from 41 healthy control subjects who participated in two experiments, one involving visual-auditory stimulation and the other based on bimanual fingertapping sequences. The results suggest that MLDA uses significantly more voxels containing discriminative information (related to different experimental conditions) to classify the data. On the other hand, SVM is more parsimonious and uses less voxels to achieve similar classification accuracies. In conclusion, MLDA is mostly focused on extracting all discriminative information available, while SVM extracts the information which is sufficient for classification. (C) 2009 Elsevier Inc. All rights reserved.

Hyperplane navigation: A method to set individual scores in fMRI group datasets

Recent studies have demonstrated that spatial patterns of fMRI BOLD activity distribution over the brain may be used to classify different groups or mental states. These studies are based on the application of advanced pattern recognition approaches and multivariate statistical classifiers. Most published articles in this field are focused on improving the accuracy rates and many approaches have been proposed to accomplish this task. Nevertheless, a point inherent to most machine learning methods (and still relatively unexplored in neuroimaging) is how the discriminative information can be used to characterize groups and their differences. In this work, we introduce the Maximum Uncertainty Linear Discrimination Analysis (MLDA) and show how it can be applied to infer groups` patterns by discriminant hyperplane navigation. In addition, we show that it naturally defines a behavioral score, i.e., an index quantifying the distance between the states of a subject from predefined groups. We validate and illustrate this approach using a motor block design fMRI experiment data with 35 subjects. (C) 2008 Elsevier Inc. All rights reserved.