422 results on '"Toschi, N."'
Search Results
252. Association of cerebrospinal fluid α-synuclein with total and phospho-tau 181 protein concentrations and brain amyloid load in cognitively normal subjective memory complainers stratified by Alzheimer's disease biomarkers.
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Vergallo A, Bun RS, Toschi N, Baldacci F, Zetterberg H, Blennow K, Cavedo E, Lamari F, Habert MO, Dubois B, Floris R, Garaci F, Lista S, and Hampel H
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- Aged, Alzheimer Disease diagnosis, Apolipoprotein E4 genetics, Biomarkers cerebrospinal fluid, Cognition, Cohort Studies, Cross-Sectional Studies, Diagnostic Self Evaluation, Female, Humans, Male, Positron-Emission Tomography, Prodromal Symptoms, Amyloid metabolism, Brain diagnostic imaging, Brain metabolism, Memory Disorders diagnosis, alpha-Synuclein cerebrospinal fluid, tau Proteins cerebrospinal fluid
- Abstract
Introduction: Several neurodegenerative brain proteinopathies, including Alzheimer's disease (AD), are associated with cerebral deposition of insoluble aggregates of α-synuclein. Previous studies reported a trend toward increased cerebrospinal fluid (CSF) α-synuclein (α-syn) concentrations in AD compared with other neurodegenerative diseases and healthy controls., Methods: The pathophysiological role of CSF α-syn in asymptomatic subjects at risk of AD has not been explored. We performed a large-scale cross-sectional observational monocentric study of preclinical individuals at risk for AD (INSIGHT-preAD)., Results: We found a positive association between CSF α-syn concentrations and brain β-amyloid deposition measures as mean cortical standard uptake value ratios. We demonstrate positive correlations between CSF α-syn and both CSF t-tau and p-tau
181 concentrations., Discussion: Animal models presented evidence, indicating that α-syn may synergistically and directly induce fibrillization of both tau and β-amyloid. Our data indicate an association of CSF α-syn with AD-related pathophysiological mechanisms, during the preclinical phase of the disease., (Copyright © 2018 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)- Published
- 2018
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253. The role of intraoperative stroke volume variation on bleeding during functional endoscopic sinus surgery.
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Di Mauro R, Lucci F, Martino F, Silvi MB, Gidaro E, Di Lorenzo S, Toschi N, Di Girolamo S, and Dauri M
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- Adult, Aged, Chronic Disease, Endoscopy, Female, Hemodynamics, Humans, Male, Middle Aged, Prospective Studies, Rhinitis complications, Rhinitis physiopathology, Sinusitis complications, Sinusitis physiopathology, Young Adult, Blood Loss, Surgical, Monitoring, Intraoperative methods, Rhinitis surgery, Sinusitis surgery, Stroke Volume
- Abstract
Background: Functional endoscopic sinus surgery (FESS) is a minimally-invasive surgical technique for patients with paranasal sinus pathology. Surgical bleeding reduces operative field visibility and increases the incidence of serious complications. Epinephrine injection into the nasal mucosa and controlled hypotension are used to minimize bleeding. Hypotension carries risks and sometimes does not reduce surgical bleeding. The goal of this study is to discover which hemodynamic parameter better correlates with surgical bleeding., Methods: We enrolled 55 patients undergoing FESS. Inclusion criteria: male or female with chronic rhinosinusitis (CRS), older than 18 years, ASA I to III and primary surgery. Exclusion criteria: ASA>III, cerebrovascular and cardiac disorders, supraventricular tachycardia, renal or hepatic diseases, non-treated arterial hypertension, beta-blocking agent therapy, platelet-inhibiting agent or anticoagulant therapy, coagulopathy, pregnancy, clotting disorders, presence of neoplastic lesions and history of cranio-facial surgery. We used standard ASA plus ClearSight to assess hemodynamic parameters. Surgical procedures were performed by one surgeon and divided in ten surgical times (from T0 to T9). Intraoperative bleeding was assessed using the Fromme-Boezaart Scale., Results: Analysis between all the hemodynamic parameters registered and the Fromme-Boezaart Score showed a negative correlation between surgical bleeding and stroke volume variation (SVV) only. When dichotomizing according to Fromme-Boezaart Score (above or below 2), SVV was the only parameter which showed significant differences between groups. A cut-off of 12.5% in SVV is optimal to distinguish the group with the better surgical visibility from the group with the worst one., Conclusions: Targeting SVV larger than 12% achieves a possible reduction of the intraoperative bleeding in patients undergoing FESS.
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- 2018
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254. Spectral Domain Optical Coherence Tomography Assessment of Macular and Optic Nerve Alterations in Patients with Glaucoma and Correlation with Visual Field Index.
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Martucci A, Toschi N, Cesareo M, Giannini C, Pocobelli G, Garaci F, Mancino R, and Nucci C
- Abstract
Introduction: To evaluate the sectorial thickness of single retinal layers and optic nerve using spectral domain optic coherence tomography (SD-OCT) and highlight the parameters with the best diagnostic accuracy in distinguishing between normal and glaucoma subjects at different stages of the disease., Material and Methods: For this cross-sectional study, 25 glaucomatous (49 eyes) and 18 age-matched healthy subjects (35 eyes) underwent a complete ophthalmologic examination including visual field testing. Sectorial thickness values of each retinal layer and of the optic nerve were measured using SD-OCT Glaucoma Module Premium Edition (GMPE) software. Each parameter was compared between the groups, and the layers and sectors with the best area under the receiver operating characteristic curve (AUC) were identified. Correlation of visual field index with the most relevant structural parameters was also evaluated., Results and Discussion: All subjects were grouped according to stage as follows: Controls (CTRL); Early Stage Group (EG) (Stage 1 + Stage 2); Advanced Stage Group (AG) (Stage 3 + Stage 4 + Stage 5). mGCL TI, mGCL TO, mIPL TO, mean mGCL, cpRNFLt NS, and cpRNFLt TI showed the best results in terms of AUC according classification proposed by Swets (0.9 < AUC < 1.0). These parameters also showed significantly different values among group when CTRL vs EG, CTRL vs AG, and EG vs AG were compared. SD-OCT examination showed significant sectorial thickness differences in most of the macular layers when glaucomatous patients at different stages of the disease were compared each other and to the controls.
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- 2018
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255. Effect of Alzheimer's disease risk and protective factors on cognitive trajectories in subjective memory complainers: An INSIGHT-preAD study.
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Teipel SJ, Cavedo E, Lista S, Habert MO, Potier MC, Grothe MJ, Epelbaum S, Sambati L, Gagliardi G, Toschi N, Greicius MD, Dubois B, and Hampel H
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- Aged, Aged, 80 and over, Alzheimer Disease epidemiology, Alzheimer Disease metabolism, Amyloid metabolism, Apolipoproteins E genetics, Brain diagnostic imaging, Brain metabolism, Brain pathology, Diagnostic Self Evaluation, Disease Progression, Educational Status, Female, Follow-Up Studies, Humans, Longitudinal Studies, Male, Memory Disorders epidemiology, Memory Disorders metabolism, Nonlinear Dynamics, Organ Size, Protective Factors, Alzheimer Disease diagnostic imaging, Alzheimer Disease psychology, Cognition, Memory Disorders diagnostic imaging
- Abstract
Introduction: Cognitive change in people at risk of Alzheimer's disease (AD) such as subjective memory complainers is highly variable across individuals., Methods: We used latent class growth modeling to identify distinct classes of nonlinear trajectories of cognitive change over 2 years follow-up from 265 subjective memory complainers individuals (age 70 years and older) of the INSIGHT-preAD cohort. We determined the effect of cortical amyloid load, hippocampus and basal forebrain volumes, and education on the cognitive trajectory classes., Results: Latent class growth modeling identified distinct nonlinear cognitive trajectories. Education was associated with higher performing trajectories, whereas global amyloid load and basal forebrain atrophy were associated with lower performing trajectories., Discussion: Distinct classes of cognitive trajectories were associated with risk and protective factors of AD. These associations support the notion that the identified cognitive trajectories reflect different risk for AD that may be useful for selecting high-risk individuals for intervention trials., (Copyright © 2018 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)
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- 2018
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256. Carotid Artery Stent Placement and Carotid Endarterectomy: A Challenge for Urgent Treatment after Stroke-Early and 12-Month Outcomes in a Comprehensive Stroke Center.
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Rocco A, Sallustio F, Toschi N, Rizzato B, Legramante J, Ippoliti A, Ascoli Marchetti A, Pampana E, Gandini R, and Diomedi M
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- Aged, Aged, 80 and over, Carotid Stenosis complications, Carotid Stenosis diagnostic imaging, Carotid Stenosis mortality, Endovascular Procedures adverse effects, Endovascular Procedures mortality, Feasibility Studies, Female, Humans, Ischemic Attack, Transient diagnostic imaging, Ischemic Attack, Transient etiology, Ischemic Attack, Transient mortality, Male, Middle Aged, Recurrence, Retrospective Studies, Risk Factors, Secondary Prevention methods, Stroke diagnostic imaging, Stroke etiology, Stroke mortality, Time Factors, Treatment Outcome, Carotid Stenosis therapy, Endarterectomy, Carotid adverse effects, Endarterectomy, Carotid mortality, Endovascular Procedures instrumentation, Ischemic Attack, Transient therapy, Secondary Prevention instrumentation, Stents, Stroke therapy
- Abstract
Purpose: To compare feasibility, 12-month outcome, and periprocedural and postprocedural risks between carotid artery stent (CAS) placement and carotid endarterectomy (CEA) performed within 1 week after transient ischemic attack (TIA) or mild to severe stroke onset in a single comprehensive stroke center., Materials and Methods: Retrospective analysis of prospective data collected from 1,148 patients with ischemic stroke admitted to a single stroke unit between January 2013 and July 2015 was conducted. Among 130 consecutive patients with symptomatic carotid stenosis, 110 (10 with TIA, 100 with stroke) with a National Institutes of Health Stroke Scale (NIHSS) score < 20 and a prestroke modified Rankin Scale (mRS) score < 2 were eligible for CAS placement or CEA and treated according to the preference of the patient or a surrogate. Periprocedural (< 48 h) and postprocedural complications, functional outcome, stroke, and death rate up to 12 months were analyzed., Results: Sixty-two patients were treated with CAS placement and 48 were treated with CEA. Several patients presented with moderate or major stroke (45.8% CEA, 64.5% CAS). NIHSS scores indicated slightly greater severity at onset in patients treated with a CAS vs CEA (6.6 ± 5.7 vs 4.2 ± 3.4; P = .08). Complication rates were similar between groups. mRS scores showed a significant improvement over time and a significant interaction with age in both groups. Similar incidences of death or stroke were shown on survival analysis. A subanalysis in patients with NIHSS scores ≥ 4 showed no differences in complication rate and outcome., Conclusions: CAS placement and CEA seem to offer early safe and feasible secondary stroke prevention treatments in experienced centers, even after major atherosclerotic stroke., (Copyright © 2018 SIR. Published by Elsevier Inc. All rights reserved.)
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- 2018
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257. A Multi-modal Convolutional Neural Network Framework for the Prediction of Alzheimer's Disease.
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Spasov SE, Passamonti L, Duggento A, Lio P, and Toschi N
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- Humans, Magnetic Resonance Imaging, Nerve Net, Neural Networks, Computer, Alzheimer Disease
- Abstract
This paper presents a multi-modal Alzheimer's disease (AD) classification framework based on a convolutional neural network (CNN) architecture. The devised model takes structural MRI, and clinical assessment and genetic (APOe4) measures as inputs. Our CNN structure is designed to be efficient in its use of parameters which reduces overfitting, computational complexity, memory requirements and speed of prototyping. This is achieved by factorising the convolutional layers in parallel streams which also enables the simultaneous extraction of high and low level feature representations. Our method consistently achieves high classification results in discriminating between AD and control subjects with an average of 99% accuracy, 98% sensitivity, 100% specificity and an AUC of 1 across all test folds. Our study confirms that careful tuning of CNN characteristics can result in a framework which delivers extremely accurate predictions in a clinical problem despite data paucity, opening new avenues for application to prediction tasks which regard patient stratification, prediction of clinical evolution and eventually personalised medicine applications.
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- 2018
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258. A realistic neuronal network and neurovascular coupling model for the study of multivariate directed connectivity in fMRI data.
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Duggento A, Passamonti L, Guerrisi M, and Toschi N
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- Brain, Connectome, Humans, Neurons, Magnetic Resonance Imaging, Neurovascular Coupling
- Abstract
The use of Multivariate Granger Causality (MVGC) in estimating directed Blood-Oxygen-Level- Dependant (BOLD) connectivity is still controversial. This is mostly due to the short data Ienghts typically available in func- tional MRI (fMRI) acquisitions, to the very nature of the BOLD acquisition strategy (which yields extremely low signal- to-noise-ratio) and importantly to the fact that neuronal activi- ty is convolved with a slow-varying haemodynamic response function (HRF) which therefore generates a temporal confound which is arduous to account for when basing MVGC estimates on vector autoregressive models (VAR). In this paper, we em- ploy realistic complex network models based on Izhikevich neuronal populations, interlinked by realistic neuronal fiber bundles which exert compounded directed influences and cas- cade into Baloon-model-like neurovascular coupling, to explore and validate the MVGC approach to directed connectivity es- timation in realistic fMRI conditions and in a complex directed network setting. In particular, we show in silico that the top 1 percentile of a BOLD connectivity matrix estimated with MVGC from BOLD data similar to the one provided by the Human Connectome Project (HCP) has a Positive Predictive Value very close to 1, hence corroborating the evidence that the "strongest" connections can be safely studied with this method in fMRI.
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- 2018
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259. Structural connectome of the human vestibular, pre-motor, and navigation network<sup/>.
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Indovina I, Riccelli R, Passamonti L, Maffei V, Bosco G, Lacquaniti F, and Toschi N
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- Adult, Humans, Parietal Lobe physiology, Thalamus physiology, Young Adult, Connectome, Vestibule, Labyrinth physiology
- Abstract
The aim of this study is to characterize modules and hubs within the multimodal vestibular system and, particularly, to test the centrality of posterior peri-sylvian regions. Structural connectivity matrices from 50 unrelated healthy right-handed subjects from the Human Connectome Project (HCP) database were analyzed using multishell diffusion-weighted data, probabilistic tractography (constrained spherical-deconvolution informed filtering of tractograms) in combination with subject-specific grey matter parcellations. Network nodes included parcellated regions within the vestibular, pre-motor and navigation system. Module calculation produced two and three modules in the right and left hemisphere, respectively. On the right, regions were grouped into a vestibular and pre-motor module, and into a visual-navigation module. On the left this last module was split into an inferior and superior component. In the thalamus, a region comprising the mediodorsal and anterior complex, and lateral and inferior pulvinar, was included in the ipsilateral navigation module, while the remaining thalamus was clustered with the ipsilateral vestibular pre-motor module. Hubs were located bilaterally in regions encompassing the inferior parietal cortex and the precuneus. This analysis revealed a dorso-lateral path within the multi-modal vestibular system related to vestibular / motor control, and a ventro-medial path related to spatial orientation / navigation. Posterior peri-sylvian regions may represent the main hubs of the whole modular network.
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- 2018
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260. Radiological, Histological and Chemical Analysis of Breast Microcalcifications: Diagnostic Value and Biological Significance.
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Bonfiglio R, Scimeca M, Toschi N, Pistolese CA, Giannini E, Antonacci C, Ciuffa S, Tancredi V, Tarantino U, Albonici L, and Bonanno E
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- Calcification, Physiologic physiology, Female, Humans, Mammography methods, Osteoblasts pathology, Retrospective Studies, Tumor Microenvironment physiology, Breast pathology, Breast Neoplasms pathology, Calcinosis pathology
- Abstract
Classification of mammary microcalcifications is based on radiological and histological characteristics that are routinely evaluated during the diagnostic path for the identification of breast cancer, or in patients at risk of developing breast cancer. The main aim of this study was to explore the relationship between the imaging parameters most commonly used for the study of mammary microcalcifications and the corresponding histological and chemical properties. To this end, we matched the radiographic characteristics of microcalcifications to breast lesion type, histology of microcalcifications and elemental composition of microcalcifications as obtained by energy dispersive x ray (EDX)-microanalysis. In addition, we investigated the properties of breast cancer microenvironment, under the hypothesis that microcalcification formation could result from a mineralization process similar to that occurring during bone osteogenesis. In this context, breast lesions with and without microcalcifications were compared in terms of the expression of the main molecules detected during bone mineralization (BMP-2, BMP-4, PTX3, RANKL OPN and RUNX2). Our data indicate that microcalcifications classified by mammography as "casting type" are prevalently made of hydroxyapatite magnesium substituted and are associated with breast cancer types with the poorest prognosis. Moreover, breast cancer cells close to microcalcifications expressed higher levels of bone mineralization markers as compared to cells found in breast lesions without microcalcifications. Notably, breast lesions with microcalcifications were characterized by the presence of breast-osteoblast-like cells. In depth studies of microcalcifications characteristics could support a new interpretation about the genesis of ectopic calcification in mammary tissue. Candidating this phenomenon as an integral part of the tumorigenic process therefore has the potential to improve the clinical management of patients early during their diagnostic path.
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- 2018
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261. A probabilistic template of human mesopontine tegmental nuclei from in vivo 7T MRI.
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Bianciardi M, Strong C, Toschi N, Edlow BL, Fischl B, Brown EN, Rosen BR, and Wald LL
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- Adult, Diffusion Tensor Imaging methods, Echo-Planar Imaging methods, Female, Humans, Male, Image Processing, Computer-Assisted methods, Magnetic Resonance Imaging methods, Neuroimaging methods, Tegmentum Mesencephali diagnostic imaging
- Abstract
Mesopontine tegmental nuclei such as the cuneiform, pedunculotegmental, oral pontine reticular, paramedian raphe and caudal linear raphe nuclei, are deep brain structures involved in arousal and motor function. Dysfunction of these nuclei is implicated in the pathogenesis of disorders of consciousness and sleep, as well as in neurodegenerative diseases. However, their localization in conventional neuroimages of living humans is difficult due to limited image sensitivity and contrast, and a stereotaxic probabilistic neuroimaging template of these nuclei in humans does not exist. We used semi-automatic segmentation of single-subject 1.1mm-isotropic 7T diffusion-fractional-anisotropy and T
2 -weighted images in healthy adults to generate an in vivo probabilistic neuroimaging structural template of these nuclei in standard stereotaxic (Montreal Neurological Institute, MNI) space. The template was validated through independent manual delineation, as well as leave-one-out validation and evaluation of nuclei volumes. This template can enable localization of five mesopontine tegmental nuclei in conventional images (e.g. 1.5T, 3T) in future studies of arousal and motor physiology (e.g. sleep, anesthesia, locomotion) and pathology (e.g. disorders of consciousness, sleep disorders, Parkinson's disease). The 7T magnetic resonance imaging procedure for single-subject delineation of these nuclei may also prove useful for future 7T studies of arousal and motor mechanisms., (Copyright © 2017 Elsevier Inc. All rights reserved.)- Published
- 2018
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262. Multivariate Granger causality unveils directed parietal to prefrontal cortex connectivity during task-free MRI.
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Duggento A, Passamonti L, Valenza G, Barbieri R, Guerrisi M, and Toschi N
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- Connectome, Humans, Image Processing, Computer-Assisted, Multivariate Analysis, Magnetic Resonance Imaging, Nerve Net diagnostic imaging, Prefrontal Cortex diagnostic imaging
- Abstract
While a large body of research has focused on the study of functional brain "connectivity", few investigators have focused on directionality of brain-brain interactions which, in spite of the mostly bidirectional anatomical substrates, cannot be assumed to be symmetrical. We employ a multivariate Granger Causality-based approach to estimating directed in-network interactions and quantify its advantages using extensive realistic synthetic BOLD data simulations to match Human Connectome Project (HCP) data specification. We then apply our framework to resting state functional MRI (rs-fMRI) data provided by the HCP to estimate the directed connectome of the human brain. We show that the functional interactions between parietal and prefrontal cortices commonly observed in rs-fMRI studies are not symmetrical, but consists of directional connectivity from parietal areas to prefrontal cortices rather than vice versa. These effects are localized within the same hemisphere and do not generalize to cross-hemispheric functional interactions. Our data are consistent with neurophysiological evidence that posterior parietal cortices involved in processing and integration of multi-sensory information modulate the function of more anterior prefrontal regions implicated in action control and goal-directed behaviour. The directionality of functional connectivity can provide an additional layer of information in interpreting rs-fMRI studies both in health and disease.
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- 2018
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263. Alzheimer's disease biomarker-guided diagnostic workflow using the added value of six combined cerebrospinal fluid candidates: Aβ 1-42 , total-tau, phosphorylated-tau, NFL, neurogranin, and YKL-40.
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Hampel H, Toschi N, Baldacci F, Zetterberg H, Blennow K, Kilimann I, Teipel SJ, Cavedo E, Melo Dos Santos A, Epelbaum S, Lamari F, Genthon R, Dubois B, Floris R, Garaci F, and Lista S
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- Aged, Alzheimer Disease classification, Amyloid beta-Peptides cerebrospinal fluid, Area Under Curve, Biomarkers cerebrospinal fluid, Chitinase-3-Like Protein 1 cerebrospinal fluid, Cognitive Dysfunction cerebrospinal fluid, Cognitive Dysfunction classification, Cross-Sectional Studies, Diagnosis, Differential, Female, Frontotemporal Dementia cerebrospinal fluid, Frontotemporal Dementia classification, Humans, Male, Middle Aged, Neurofilament Proteins cerebrospinal fluid, Nuclear Proteins cerebrospinal fluid, Peptide Fragments cerebrospinal fluid, RNA-Binding Proteins, ROC Curve, Retrospective Studies, tau Proteins cerebrospinal fluid, Alzheimer Disease cerebrospinal fluid
- Abstract
Introduction: The diagnostic and classificatory performances of all combinations of three core (amyloid β peptide [i.e., Aβ
1-42 ], total tau [t-tau], and phosphorylated tau) and three novel (neurofilament light chain protein, neurogranin, and YKL-40) cerebrospinal fluid biomarkers of neurodegeneration were compared among individuals with mild cognitive impairment (n = 41), Alzheimer's disease dementia (ADD; n = 35), frontotemporal dementia (FTD; n = 9), and cognitively healthy controls (HC; n = 21), using 10-fold cross-validation., Methods: The combinations ranking in the top 10 according to diagnostic accuracy in differentiating between distinct diagnostic categories were identified., Results: The single biomarkers or biomarker combinations generating the best area under the receiver operating characteristics (AUROCs) were the following: the combination [amyloid β peptide + phosphorylated tau + neurofilament light chain] for distinguishing between ADD patients and HC (AUROC = 0.86), t-tau for distinguishing between ADD and FTD patients (AUROC = 0.82), and t-tau for distinguishing between FTD patients and HC (AUROC = 0.78)., Conclusions: Novel and established cerebrospinal fluid markers perform with at least fair accuracy in the discrimination between ADD and FTD. The classification of mild cognitive impairment individuals was poor., (Copyright © 2017 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)- Published
- 2018
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264. Can Serum Cystatin C predict long-term survival in cardiac surgery patients?
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Rovella V, Marrone G, Dessì M, Ferrannini M, Toschi N, Pellegrino A, Casasco M, Di Daniele N, and Noce A
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- Aged, Biomarkers blood, Cardiac Surgical Procedures, Cystatin C metabolism, Diabetes Mellitus, Type 2, Female, Humans, Inflammation metabolism, Male, Middle Aged, Predictive Value of Tests, Risk Factors, Survival Analysis, Cystatin C blood
- Abstract
Renal dysfunction is a risk factor for morbidity and mortality in cardiac surgery patients. Serum Cystatin C (sCysC) is a well-recognized marker of early renal dysfunction but few reports evaluate its prognostic cardio-vascular role. The aim of the study is to consider the prognostic value of sCysC for cardiovascular mortality. Four hundred twenty-four cardiac-surgery patients (264 men and 160 women) were enrolled. At admission, all patients were tested for renal function and inflammatory status. Patients were subdivided in subgroups according to the values of the following variables: sCysC, serum Creatinine (sCrea), age, high sensitivity-C Reactive Protein, fibrinogen, surgical procedures and Kaplan-Meier cumulative survival curves were plotted. The primary end-point was cardiovascular mortality. In order to evaluate the simultaneous independent impact of all measured variables on survival we fitted a multivariate Cox-Proportional Hazard Model (CPHM). In Kaplan-Meier analysis 124 patients (29.4%) reached the end-point. In multivariate CPHM, the only significant predictors of mortality were sCysC (p<0.00001, risk ratio: 1.529, CI: 1.29-1.80) and age (p=0.039, risk ratio: 1.019, CI: 1.001-1.037). When replacing sCysC with sCrea, the only significant predictor of mortality was sCrea (p=0.0026; risk ratio 1.20; CI: 1.06-1.36). Increased levels of sCysC can be considered a useful biomarker of cardiovascular mortality in cardiac-surgery patients.
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- 2018
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265. The lncRNA H19 positively affects the tumorigenic properties of glioblastoma cells and contributes to NKD1 repression through the recruitment of EZH2 on its promoter.
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Fazi B, Garbo S, Toschi N, Mangiola A, Lombari M, Sicari D, Battistelli C, Galardi S, Michienzi A, Trevisi G, Harari-Steinfeld R, Cicchini C, and Ciafrè SA
- Abstract
The still largely obscure molecular events in the glioblastoma oncogenesis, a primary brain tumor characterized by an inevitably dismal prognosis, impel for investigation. The importance of Long noncoding RNAs as regulators of gene expression has recently become evident. Among them, H19 has a recognized oncogenic role in several types of human tumors and was shown to correlate to some oncogenic aspects of glioblastoma cells. Here we, hypothesyze that in glioblastoma H19 exerts its function through the interaction with the catalytic subunit of the PRC2 complex, EZH2. By employing a factor analysis on a SAGE dataset of 12 glioblastoma samples, we show that H19 expression in glioblastoma tissues correlates with that of several genes involved in glioblastoma growth and progression. H19 knock-down reduces viability, migration and invasiveness of two distinct human glioblastoma cell lines. Most importantly, we provide a mechanistic perspective about the role of H19 in glioblastoma cells, by showing that its expression is inversely linked to that of NKD1, a negative regulator of Wnt pathway, suggesting that H19 might regulate NKD1 transcription via EZH2-induced H3K27 trimethylation of its promoter. Indeed, we showed that H19 binds EZH2 in glioblastoma cells, and that EZH2 binding to NKD1 and other promoters is impaired by H19 silencing. In this work we describe H19 as part of an epigenetic modulation program executed by EZH2, that results in the repression of Nkd1. We believe that our results can provide a new piece to the complex puzzle of H19 function in glioblastoma., Competing Interests: CONFLICTS OF INTEREST The authors declare that they have no conflicts of interest.
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- 2018
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266. Functional connectome of the five-factor model of personality.
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Toschi N, Riccelli R, Indovina I, Terracciano A, and Passamonti L
- Abstract
A key objective of the emerging field of personality neuroscience is to link the great variety of the enduring dispositions of human behaviour with reliable markers of brain function. This can be achieved by analyzing large sets of data with methods that model whole-brain connectivity patterns. To meet these expectations, we exploited a large repository of personality and neuroimaging measures made publicly available via the Human Connectome Project. Using connectomic analyses based on graph theory, we computed global and local indices of functional connectivity (e.g., nodal strength, efficiency, clustering, betweenness centrality) and related these metrics to the five-factor-model (FFM) personality traits (i.e., neuroticism, extraversion, openness, agreeableness, and conscientiousness). The maximal information coefficient was used to assess for linear and non-linear statistical dependencies across the graph 'nodes', which were defined as distinct brain circuits identified via independent component analysis. Multi-variate regression models and 'train/test' machine-learning approaches were also used to examine the associations between FFM traits and connectomic indices as well as to test for the generalizability of the main findings, whilst accounting for age and sex differences. Conscientiousness was the sole FFM trait linked to measures of higher functional connectivity in the fronto-parietal and default mode networks. This might provide a mechanistic explanation of the behavioural observation that conscientious people are reliable and efficient in goal-setting or planning. Our study provides new inputs to understanding the neurological basis of personality and contributes to the development of more realistic models of the brain dynamics that mediate personality differences.
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- 2018
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267. Blood-Based Biomarker Screening with Agnostic Biological Definitions for an Accurate Diagnosis Within the Dimensional Spectrum of Neurodegenerative Diseases.
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Baldacci F, Lista S, O'Bryant SE, Ceravolo R, Toschi N, and Hampel H
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- Early Diagnosis, Humans, Mass Screening, Biomarkers blood, Neurodegenerative Diseases blood, Neurodegenerative Diseases diagnosis, Precision Medicine methods
- Abstract
The discovery, development, and validation of novel candidate biomarkers in Alzheimer's disease (AD) and other neurodegenerative diseases (NDs) are increasingly gaining momentum. As a result, evolving diagnostic research criteria of NDs are beginning to integrate biofluid and neuroimaging indicators of pathophysiological mechanisms. More than 10% of people aged over 65 suffer from NDs. There is an urgent need for a refined two-stage diagnostic model to first initiate an early, sensitive, and noninvasive process in primary care settings. Individuals that meet detection criteria will then be channeled to more specific, costly (positron-emission tomography), and invasive (cerebrospinal fluid) assessment methods for confirmatory biological characterization and diagnosis.A reliable and sensitive blood test for AD and other NDs is not yet established; however, it would provide the golden screening gate for an efficient primary care management. A limitation to the development of a large-scale blood-screening biomarker-based test is the traditional application of clinically descriptive criteria for the categorization of single late-stage ND constructs. These are genetically and biologically heterogeneous, reflected in multiple pathophysiological mechanisms and subsequent pathologies throughout a dimensional continuum. Evidence suggests that a shared, "open-source" integrated multilevel categorization of NDs that clusters individuals based on descriptive clinical phenotypes and pathophysiological biomarker signatures will provide the next incremental step toward an improved diagnostic process of NDs. This intermediate objective toward unbiased biomarker-guided early detection of individuals at risk for NDs is currently carried out by the international pilot Alzheimer Precision Medicine Initiative Cohort Program (APMI-CP).
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- 2018
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268. Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology.
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Hampel H, Toschi N, Babiloni C, Baldacci F, Black KL, Bokde ALW, Bun RS, Cacciola F, Cavedo E, Chiesa PA, Colliot O, Coman CM, Dubois B, Duggento A, Durrleman S, Ferretti MT, George N, Genthon R, Habert MO, Herholz K, Koronyo Y, Koronyo-Hamaoui M, Lamari F, Langevin T, Lehéricy S, Lorenceau J, Neri C, Nisticò R, Nyasse-Messene F, Ritchie C, Rossi S, Santarnecchi E, Sporns O, Verdooner SR, Vergallo A, Villain N, Younesi E, Garaci F, and Lista S
- Subjects
- Animals, Brain diagnostic imaging, Humans, Neurology, Neurophysiology, Systems Biology, Translational Research, Biomedical, Alzheimer Disease diagnosis, Alzheimer Disease therapy, Precision Medicine
- Abstract
The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular, and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an "omics"-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical, and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer's disease. The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group "Alzheimer Precision Medicine" (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development toward breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND.
- Published
- 2018
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269. Prediction of postoperative outcomes using intraoperative hemodynamic monitoring data.
- Author
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Prasad V, Guerrisi M, Dauri M, Coniglione F, Tisone G, De Carolis E, Cillis A, Canichella A, Toschi N, and Heldt T
- Subjects
- Area Under Curve, Humans, Mortality, Odds Ratio, Prognosis, Hemodynamic Monitoring, Hemodynamics, Monitoring, Intraoperative
- Abstract
Major surgeries can result in high rates of adverse postoperative events. Reliable prediction of which patient might be at risk for such events may help guide peri- and postoperative care. We show how archiving and mining of intraoperative hemodynamic data in orthotopic liver transplantation (OLT) can aid in the prediction of postoperative 180-day mortality and acute renal failure (ARF), improving upon predictions that rely on preoperative information only. From 101 patient records, we extracted 15 preoperative features from clinical records and 41 features from intraoperative hemodynamic signals. We used logistic regression with leave-one-out cross-validation to predict outcomes, and incorporated methods to limit potential model instabilities from feature multicollinearity. Using only preoperative features, mortality prediction achieved an area under the receiver operating characteristic curve (AUC) of 0.53 (95% CI: 0.44-0.78). By using intraoperative features, performance improved significantly to 0.82 (95% CI: 0.56-0.91, P = 0.001). Similarly, including intraoperative features (AUC = 0.82; 95% CI: 0.66-0.94) in ARF prediction improved performance over preoperative features (AUC = 0.72; 95% CI: 0.50-0.85), though not significantly (P = 0.32). We conclude that inclusion of intraoperative hemodynamic features significantly improves prediction of postoperative events in OLT. Features strongly associated with occurrence of both outcomes included greater intraoperative central venous pressure and greater transfusion volumes.
- Published
- 2017
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270. Altered Insular and Occipital Responses to Simulated Vertical Self-Motion in Patients with Persistent Postural-Perceptual Dizziness.
- Author
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Riccelli R, Passamonti L, Toschi N, Nigro S, Chiarella G, Petrolo C, Lacquaniti F, Staab JP, and Indovina I
- Abstract
Background: Persistent postural-perceptual dizziness (PPPD) is a common functional vestibular disorder characterized by persistent symptoms of non-vertiginous dizziness and unsteadiness that are exacerbated by upright posture, self-motion, and exposure to complex or moving visual stimuli. Recent physiologic and neuroimaging data suggest that greater reliance on visual cues for postural control (as opposed to vestibular cues-a phenomenon termed visual dependence) and dysfunction in central visuo-vestibular networks may be important pathophysiologic mechanisms underlying PPPD. Dysfunctions are thought to involve insular regions that encode recognition of the visual effects of motion in the gravitational field., Methods: We tested for altered activity in vestibular and visual cortices during self-motion simulation obtained via a visual virtual-reality rollercoaster stimulation using functional magnetic resonance imaging in 15 patients with PPPD and 15 healthy controls (HCs). We compared between groups differences in brain responses to simulated displacements in vertical vs horizontal directions and correlated the difference in directional responses with dizziness handicap in patients with PPPD., Results: HCs showed increased activity in the anterior bank of the central insular sulcus during vertical relative to horizontal motion, which was not seen in patients with PPPD. However, for the same comparison, dizziness handicap correlated positively with activity in the visual cortex (V1, V2, and V3) in patients with PPPD., Conclusion: We provide novel insight into the pathophysiologic mechanisms underlying PPPD, including functional alterations in brain processes that affect balance control and reweighting of space-motion inputs to favor visual cues. For patients with PPPD, difficulties using visual data to discern the effects of gravity on self-motion may adversely affect balance control, particularly for individuals who simultaneously rely too heavily on visual stimuli. In addition, increased activity in the visual cortex, which correlated with severity of dizziness handicap, may be a neural correlate of visual dependence.
- Published
- 2017
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271. Diagnostic accuracy of CSF neurofilament light chain protein in the biomarker-guided classification system for Alzheimer's disease.
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Lista S, Toschi N, Baldacci F, Zetterberg H, Blennow K, Kilimann I, Teipel SJ, Cavedo E, Dos Santos AM, Epelbaum S, Lamari F, Dubois B, Floris R, Garaci F, and Hampel H
- Subjects
- Aged, Alzheimer Disease diagnosis, Amyloid beta-Peptides cerebrospinal fluid, Biomarkers cerebrospinal fluid, Cohort Studies, Female, Humans, Male, Middle Aged, Peptide Fragments cerebrospinal fluid, Pilot Projects, Retrospective Studies, tau Proteins cerebrospinal fluid, Alzheimer Disease cerebrospinal fluid, Alzheimer Disease classification, Neurofilament Proteins cerebrospinal fluid
- Abstract
We assessed the diagnostic accuracy of cerebrospinal fluid (CSF) neurofilament light chain (NFL) protein in the classification of patients with Alzheimer's disease (AD) and cognitively healthy control individuals (HCs) and patients with frontotemporal dementia (FTD) as comparisons. Particularly, we tested the performance of CSF NFL concentration in differentiating patient groups stratified by fluid biomarker profiles, independently of the severity of cognitive impairment (mild cognitive impairment (MCI) and AD dementia individuals), using a biomarker-guided descriptive classification system for AD. CSF NFL concentrations were examined in a multicenter cross-sectional study of 108 participants stratified in AD pathophysiology-negative (both CSF tau and the 42-amino acid-long amyloid-beta (Aβ) peptide (Aβ
1-42 )) (n = 15), tau pathology-positive only (n = 15), Aβ pathology-positive only (n = 13), AD pathophysiology-positive (n = 33), FTD (n = 9) patients, and HCs (n = 23), according to the biomarker-based classification system. The performance of CSF NFL in discriminating AD pathophysiology-positive patients from HCs is fair, whereas the ability in differentiating tau-positive patients from HCs is poor. The classificatory performance in distinguishing AD pathophysiology-positive patients from FTD is unsatisfactory., (Copyright © 2017 Elsevier Ltd. All rights reserved.)- Published
- 2017
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272. Exposure to ultrafine particles in different transport modes in the city of Rome.
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Grana M, Toschi N, Vicentini L, Pietroiusti A, and Magrini A
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- Air Pollution analysis, Air Pollution statistics & numerical data, Cities, Environmental Exposure analysis, Humans, Italy, Railroads, Seasons, Silicones, Air Pollutants analysis, Environmental Exposure statistics & numerical data, Particulate Matter analysis, Transportation statistics & numerical data
- Abstract
There is evidence of adverse health impacts from human exposure to particulate air pollution, including increased rates of respiratory and cardiovascular illness, hospitalizations, and pre-mature mortality. Most recent hypotheses assign an important role to ultrafine particles (UFP) (<0.1 μm) and to associated transition metals (in particular Fe). In a large city like Rome, where many active people spend more than one hour per day in private or public transportation, it may be important to evaluate the level of exposure to harmful pollutants which occurs during urban travelling. In this context, the aim of this work was to examine the relative contribution of different transport modes to total daily exposure. We performed experimental measurements during both morning and evening traffic peak hours throughout the winter season (December 2013-March 2014), for a total of 98 trips. Our results suggest that the lowest UFP exposures are experienced by underground train commuters, with an average number concentration of 14 134 cm
-3 , and are largely a reflection of the routes being at greater distance from vehicular traffic. Motorcyclists experienced significantly higher average concentrations (73 168 cm-3 ) than all other exposure classes, and this is most likely a result of the presence of high-concentration and short-duration peaks which do not occur when the same routes are traveled by car. UFP concentrations in subway train environments were found to be comparable to urban background levels. Still, in underground trains we found the highest values of PM10 mass concentration with a maximum value of 422 μg/m3 . PM10 concentration in trains was found to be four and two times higher than what was measured in car and motorbike trips, respectively. Transport mode contribution to total integrated UFP daily exposure was found to be 16.3%-20.9% while travelling by car, 28.7% for motorbike trips, and 8.7% for subway trips. Due to lower exposure times, commuting by car and motorbike is comparable to other daily activities in terms of exposure. Our data can provide relevant information for transport decision-making and increase environmental awareness in the hope that the information about inhaled pollutants can translate into a more rational approach to urban travelling., (Copyright © 2017 Elsevier Ltd. All rights reserved.)- Published
- 2017
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273. Two-level diagnostic classification using cerebrospinal fluid YKL-40 in Alzheimer's disease.
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Baldacci F, Toschi N, Lista S, Zetterberg H, Blennow K, Kilimann I, Teipel S, Cavedo E, Dos Santos AM, Epelbaum S, Lamari F, Dubois B, Floris R, Garaci F, Bonuccelli U, and Hampel H
- Subjects
- Aged, Biomarkers cerebrospinal fluid, Cognitive Dysfunction cerebrospinal fluid, Cognitive Dysfunction diagnosis, Cross-Sectional Studies, Female, Frontotemporal Dementia cerebrospinal fluid, Humans, Male, Middle Aged, ROC Curve, Retrospective Studies, Alzheimer Disease cerebrospinal fluid, Alzheimer Disease diagnosis, Chitinase-3-Like Protein 1 cerebrospinal fluid
- Abstract
Introduction: We assessed the diagnostic accuracy of cerebrospinal fluid (CSF) YKL-40 in discriminating (1) clinical Alzheimer's disease (AD) from cognitively healthy controls (HCs) and frontotemporal dementia (FTD) (level I) and (2) patients stratified by different pathophysiological profiles from HCs and FTD following a novel unbiased/descriptive categorization based on CSF biomarkers, independent of cognitive impairment severity (level II)., Methods: YKL-40 was compared among HCs (n = 21), mild cognitive impairment (n = 41), AD (n = 35), and FTD (n = 9) (level I) and among HCs (n = 21), AD pathophysiology (tau and amyloid β) negative (n = 15), tau positive (n = 15), amyloid β positive (n = 13), AD pathophysiology positive (n = 33), and FTD (n = 9) (level II)., Results: Level I: YKL-40 discriminated AD from HC and FTD (area under the receiver operating characteristic curves [AUROCs] = 0.69, 0.71). Level II: YKL-40 discriminated tau-positive individuals and AD pathophysiology-positive individuals from HC, AD pathophysiology-positive patients from FTD (AUROCs = 0.76, 0.72, 0.73)., Discussion: YKL-40 demonstrates fair performance in distinguishing tau-positive patients from HCs, suggesting it may aid clinical diagnosis and support a biomarker-guided pathophysiological stratification., (Copyright © 2017 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)
- Published
- 2017
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274. Sex Differences in the Relationship Between Conduct Disorder and Cortical Structure in Adolescents.
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Smaragdi A, Cornwell H, Toschi N, Riccelli R, Gonzalez-Madruga K, Wells A, Clanton R, Baker R, Rogers J, Martin-Key N, Puzzo I, Batchelor M, Sidlauskaite J, Bernhard A, Martinelli A, Kohls G, Konrad K, Baumann S, Raschle N, Stadler C, Freitag C, Sonuga-Barke EJS, De Brito S, and Fairchild G
- Subjects
- Adolescent, Conduct Disorder diagnostic imaging, Conduct Disorder physiopathology, Female, Humans, Male, Parietal Lobe diagnostic imaging, Prefrontal Cortex diagnostic imaging, Conduct Disorder pathology, Magnetic Resonance Imaging methods, Parietal Lobe pathology, Prefrontal Cortex pathology, Sex Characteristics
- Abstract
Objective: Previous studies have reported reduced cortical thickness and surface area and altered gyrification in frontal and temporal regions in adolescents with conduct disorder (CD). Although there is evidence that the clinical phenotype of CD differs between males and females, no studies have examined whether such sex differences extend to cortical and subcortical structure., Method: As part of a European multisite study (FemNAT-CD), structural magnetic resonance imaging (MRI) data were collected from 48 female and 48 male participants with CD and from 104 sex-, age-, and pubertal-status-matched controls (14-18 years of age). Data were analyzed using surface-based morphometry, testing for effects of sex, diagnosis, and sex-by-diagnosis interactions, while controlling for age, IQ, scan site, and total gray matter volume., Results: CD was associated with cortical thinning and higher gyrification in ventromedial prefrontal cortex in both sexes. Males with CD showed lower, and females with CD showed higher, supramarginal gyrus cortical thickness compared with controls. Relative to controls, males with CD showed higher gyrification and surface area in superior frontal gyrus, whereas the opposite pattern was seen in females. There were no effects of diagnosis or sex-by-diagnosis interactions on subcortical volumes. Results are discussed with regard to attention-deficit/hyperactivity disorder, depression, and substance abuse comorbidity, medication use, handedness, and CD age of onset., Conclusion: We found both similarities and differences between males and females in CD-cortical structure associations. This initial evidence that the pathophysiological basis of CD may be partly sex-specific highlights the need to consider sex in future neuroimaging studies and suggests that males and females may require different treatments., (Copyright © 2017 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.)
- Published
- 2017
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275. Dynamic inter-network connectivity in the human brain.
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Riccelli R, Passamonti L, Duggento A, Guerrisi M, Indovina I, and Toschi N
- Subjects
- Attention, Connectome, Humans, Magnetic Resonance Imaging, Nerve Net, Brain
- Abstract
Recently, the field of functional brain connectivity has shifted its attention on studying how functional connectivity (FC) between remote regions changes over time. It is becoming increasingly evident that the human "connectome" is a dynamical entity whose variations are effected over very short timescales and reflect crucial mechanisms which underline the physiological functioning of the brain. In this study, we employ ad-hoc statistical and surrogate data generation methods to quantify whether and which brain networks displayed dynamic behaviors in a very large sample of healthy subjects provided by the Human Connectome Project (HCP). Our findings provided evidences that there are specific pairs of networks and specific networks within the healthy brain that are more likely to display dynamic behaviors. This new set of findings supports the notion that studying the time-variant connectivity in the brain could reveal useful and important properties about brain functioning in health and disease.
- Published
- 2017
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276. Dynamical brain connectivity estimation using GARCH models: An application to personality neuroscience.
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Riccelli R, Passamonti L, Duggento A, Guerrisi M, Indovina I, Terracciano A, and Toschi N
- Subjects
- Connectome, Humans, Magnetic Resonance Imaging, Personality, Brain
- Abstract
It has recently become evident that the functional connectome of the human brain is a dynamical entity whose time evolution carries important information underpinning physiological brain function as well as its disease-related aberrations. While simple sliding window approaches have had some success in estimating dynamical brain connectivity in a functional MRI (fMRI) context, these methods suffer from limitations related to the arbitrary choice of window length and limited time resolution. Recently, Generalized autoregressive conditional heteroscedastic (GARCH) models have been employed to generate dynamical covariance models which can be applied to fMRI. Here, we employ a GARCH-based method (dynamic conditional correlation - DCC) to estimate dynamical brain connectivity in the Human Connectome Project (HCP) dataset and study how the dynamic functional connectivity behaviors related to personality as described by the five-factor model. Openness, a trait related to curiosity and creativity, is the only trait associated with significant differences in the amount of time-variability (but not in absolute median connectivity) of several inter-network functional connections in the human brain. The DCC method offers a novel window to extract dynamical information which can aid in elucidating the neurophysiological underpinning of phenomena to which conventional static brain connectivity estimates are insensitive.
- Published
- 2017
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277. Resting-state brain correlates of instantaneous autonomic outflow.
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Valenza G, Duggento A, Passamonti L, Diciotti S, Tessa C, Barbieri R, and Toschi N
- Subjects
- Autonomic Nervous System, Brain Mapping, Humans, Magnetic Resonance Imaging, Rest, Brain
- Abstract
A prominent pathway of brain-heart interaction is represented by autonomic nervous system (ANS) heartbeat modulation. While within-brain resting state networks have been the object of intense functional Magnetic Resonance Imaging (fMRI) research, technological and methodological limitations have hampered research on the central correlates of cardiovascular control dynamics. Here we combine the high temporal and spatial resolution as well as data volume afforded by the Human Connectome Project with a probabilistic model of heartbeat dynamics to characterize central correlates of sympathetic and parasympathetic ANS activity at rest. We demonstrate an involvement of a number of brain regions such as the Insular cortex, Frontal Gyrus, Lateral Occipital Cortex, Paracingulate and Cingulate Gyrus and Precuneous Cortex, as well as subcortical structures (Thalamus, Putamen, Pallidum, Brain-Stem, Hippocampus, Amygdala, and Right Caudate) in the modulation of ANS-mediated cardiovascular control, possibly indicating a broader definition of the central autonomic network (CAN). Our findings provide a basis for an informed neurobiological interpretation of the numerous studies which employ HRV-related measures as standalone biomarkers in health and disease.
- Published
- 2017
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278. Resting-state brain correlates of cardiovascular complexity.
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Valenza G, Duggento A, Passamonti L, Diciotti S, Tessa C, Toschi N, and Barbieri R
- Subjects
- Brain Mapping, Gray Matter, Humans, Magnetic Resonance Imaging, Rest, Temporal Lobe, Brain
- Abstract
While estimates of complex heartbeat dynamics have provided effective prognostic and diagnostic markers for a wide range of pathologies, brain correlates of complex cardiac measures in general and of complex sympatho-vagal dynamics in particular are still unknown. In this study we combine resting state functional Magnetic Resonance Imaging (fMRI) and physiological signal acquisition from 34 healthy subjects selected from the Human Connectome Project (HCP) repository with inhomogeneous point-process approximate and sample heartbeat entropy measures (ipApEn and ipSampEn) to investigate brain areas involved in complex cardiovascular control. Our results show that activity in the Temporal Gyrus, Frontal Orbital Cortex, Temporal Fusiform and Opercular cortices, Planum Temporale, and Paracingulate cortex are negatively correlated with ipApEn dynamics. Activity in the same cortical areas as well as in the Temporal Fusiform cortex are negatively correlated with ipSampEn dynamics. No significant positive correlations were found. These pioneering results suggest that cardiovascular complexity at rest is linked to a few specific cortical brain structures, including crucial areas connected with parasympathetic outflow. This corroborates the hypothesis of a multidimensional central network which controls nonlinear cardiac dynamics under a predominantly vagally-driven tone.
- Published
- 2017
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279. Estimating directed brain-brain and brain-heart connectivity through globally conditioned Granger causality approaches.
- Author
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Duggento A, Passamonti L, Guerrisi M, Valenza G, Barbieri R, and Toschi N
- Subjects
- Connectome, Heart, Humans, Magnetic Resonance Imaging, Models, Statistical, Nerve Net, Brain
- Abstract
While a large body of research has focused on the study of within-brain physiological networks (i.e. brain connectivity) as well as their disease-related aberration, few investigators have focused on estimating the directionality of these brain-brain interaction which, given the complexity of brain networks, should be properly conditioned in order to avoid the high number of false positives commonly encountered when using bivariate approaches to brain connectivity estimation. Additionally, the constituents of a number of brain subnetworks, and in particular of the central autonomic network (CAN), are still not completely determined. In this study we present and validate a global conditioning approach to reconstructing directed networks using complex synthetic networks of nonlinear oscillators. We then employ our framework, along with a probabilistic model for heartbeat generation, to characterize the directed functional connectome of the human brain and to establish which parts of this connectome effect the directed central modulation of peripheral autonomic cardiovascular control. We demonstrate the effectiveness of our conditioning approach and unveil a top-down directed influence of the default mode network on the salience network, which in turn is seen to be the strongest modulator of directed autonomic cardiovascular control.
- Published
- 2017
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280. Simultaneous estimation of the in-mean and in-variance causal connectomes of the human brain.
- Author
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Duggento A, Passamonti L, Guerrisi M, and Toschi N
- Subjects
- Connectome, Humans, Magnetic Resonance Imaging, Rest, Brain
- Abstract
In recent years, the study of the human connectome (i.e. of statistical relationships between non spatially contiguous neurophysiological events in the human brain) has been enormously fuelled by technological advances in high-field functional magnetic resonance imaging (fMRI) as well as by coordinated world wide data-collection efforts like the Human Connectome Project (HCP). In this context, Granger Causality (GC) approaches have recently been employed to incorporate information about the directionality of the influence exerted by a brain region on another. However, while fluctuations in the Blood Oxygenation Level Dependent (BOLD) signal at rest also contain important information about the physiological processes that underlie neurovascular coupling and associations between disjoint brain regions, so far all connectivity estimation frameworks have focused on central tendencies, hence completely disregarding so-called in-variance causality (i.e. the directed influence of the volatility of one signal on the volatility of another). In this paper, we develop a framework for simultaneous estimation of both in-mean and in-variance causality in complex networks. We validate our approach using synthetic data from complex ensembles of coupled nonlinear oscillators, and successively employ HCP data to provide the very first estimate of the in-variance connectome of the human brain.
- Published
- 2017
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281. Early axonal damage in normal appearing white matter in multiple sclerosis: Novel insights from multi-shell diffusion MRI.
- Author
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De Santis S, Granberg T, Ouellette R, Treaba CA, Qiuyun Fan, Herranz E, Mainero C, and Toschi N
- Subjects
- Axons, Brain, Diffusion Magnetic Resonance Imaging, Diffusion Tensor Imaging, Humans, Multiple Sclerosis, White Matter
- Abstract
Conventional diffusion-weighted MR imaging techniques provide limited specificity in disentangling disease-related microstructural alterations involving changes in both axonal density and myelination. By simultaneously probing multiple diffusion regimens, multi-shell diffusion MRI is capable of increasing specificity to different tissue sub-compartments and hence separate different contributions to changes in diffusion-weighted signal attenuation. Advanced multi-shell diffusion models impose significant requirements on the amount of diffusion weighting (i.e. gradient coil performance) and angular resolution (i.e. in-scanner subject time), which commonly limits their applicability in a clinical setting. In this paper, we apply a high-b-value, high angular resolution multi-shell diffusion MRI protocol to a population of early multiple sclerosis (MS) patients and healthy controls. Through the Composite Hindered and Restricted Model of Diffusion (CHARMED) model, we extract indices for axonal density as well as parameters sensitive to myelin. We demonstrate increased sensitivity to microstructural changes in normal appearing white matter and in lesions in MS as compared to traditional models like DTI. These changes appear to be predominantly in axonal density, pointing towards the existence of axonal damage mechanisms in early MS.
- Published
- 2017
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282. Silver nanoparticles inhaled during pregnancy reach and affect the placenta and the foetus.
- Author
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Campagnolo L, Massimiani M, Vecchione L, Piccirilli D, Toschi N, Magrini A, Bonanno E, Scimeca M, Castagnozzi L, Buonanno G, Stabile L, Cubadda F, Aureli F, Fokkens PH, Kreyling WG, Cassee FR, and Pietroiusti A
- Subjects
- Animals, Cytokines analysis, Female, Mice, Pregnancy, Inhalation Exposure adverse effects, Inhalation Exposure analysis, Maternal Exposure adverse effects, Metal Nanoparticles administration & dosage, Metal Nanoparticles toxicity, Placenta chemistry, Placenta drug effects, Silver administration & dosage, Silver pharmacokinetics, Silver toxicity
- Abstract
Recently, interest for the potential impact of consumer-relevant engineered nanoparticles on pregnancy has dramatically increased. This study investigates whether inhaled silver nanoparticles (AgNPs) reach and cross mouse placental barrier and induce adverse effects. Apart from their relevance for the growing use in consumer products and biomedical applications, AgNPs are selected since they can be unequivocally identified in tissues. Pregnant mouse females are exposed during the first 15 days of gestation by nose-only inhalation to a freshly produced aerosol of 18-20 nm AgNPs for either 1 or 4 h, at a particle number concentration of 3.80 × 107 part./cm
-3 and at a mass concentration of 640 μg/m³. AgNPs are identified and quantitated in maternal tissues, placentas and foetuses by transmission electron microscopy coupled with energy-dispersive X-ray spectroscopy and single-particle inductively coupled plasma mass spectrometry. Inhalation of AgNPs results in increased number of resorbed foetuses associated with reduced oestrogen plasma levels, in the 4 h/day exposed mothers. Increased expression of pregnancy-relevant inflammatory cytokines is also detected in the placentas of both groups. These results prove that NPs are able to reach and cross the mouse placenta and suggest that precaution should be taken with respect to acute exposure to nanoparticles during pregnancy.- Published
- 2017
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283. Infectious disease ward admission positively influences P. jiroveci pneumonia (PjP) outcome: A retrospective analysis of 116 HIV-positive and HIV-negative immunocompromised patients.
- Author
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Ricciardi A, Gentilotti E, Coppola L, Maffongelli G, Cerva C, Malagnino V, Mari A, Di Veroli A, Berrilli F, Apice F, Toschi N, Di Cave D, Parisi SG, Andreoni M, and Sarmati L
- Subjects
- Adult, Aged, Aged, 80 and over, Anti-Bacterial Agents pharmacology, Anti-Bacterial Agents therapeutic use, Communicable Diseases, Comorbidity, Female, HIV Infections complications, HIV Infections drug therapy, HIV Seropositivity, Humans, Immunocompromised Host, Italy epidemiology, Male, Middle Aged, Odds Ratio, Outcome Assessment, Health Care, Pneumonia, Pneumocystis diagnosis, Pneumonia, Pneumocystis drug therapy, Pneumonia, Pneumocystis etiology, Retrospective Studies, Risk Factors, Tomography, X-Ray Computed, Young Adult, HIV Infections epidemiology, Patient Admission, Patients' Rooms, Pneumocystis carinii classification, Pneumocystis carinii genetics, Pneumocystis carinii isolation & purification, Pneumonia, Pneumocystis epidemiology
- Abstract
P. jiroveci (Pj) causes a potentially fatal pneumonia in immunocompromised patients and the factors associated with a bad outcome are poorly understood. A retrospective analysis on Pj pneumonia (PjP) cases occurring in Tor Vergata University Hospital, Italy, during the period 2011-2015. The patients' demographic, clinical and radiological characteristics and the Pj genotypes were considered. The study population included 116 patients, 37.9% of whom had haematological malignancy or underwent haematological stem cell transplantation (HSCT), 22.4% had HIV infection, 16.4% had chronic lung diseases (CLD), 7.8% had a solid cancer, and 3.4% underwent a solid organ transplant (SOT). The remaining 12.1% had a miscellaneous other condition. At univariate analysis, being older than 60 years was significantly correlated with a severe PjP (OR [95%CI] 2.52 [0.10-5.76]; p = 0.031) and death (OR [95%CI] 2.44 [1.05-5.70]; p = 0.036), while a previous trimethoprim/sulfamethoxazole (TMP/SMX) prophylaxis were significantly associated with a less severe pneumonia (OR[95%CI] 0.35 [0.15-0.84], p = 0.023); moreover, death due to PjP was significantly more frequent in patients with CLD (OR[95%CI] 3.26 [1.17-9.05]; p = 0.019) while, admission to the Infectious Diseases Unit was significantly associated with fewer deaths (OR[95%CI] 0.10 [0.03-0.36], p = 0.002). At multivariate analysis, a better PjP outcome was observed in patients taking TMP/SMX prophylaxis and that were admitted to the Infectious Diseases Unit (OR[95%CI] 0.27 [0.07-1.03], p = 0.055, OR[95%CI] 0.16 [0.05-0.55]; p = 0.004, respectively). In conclusion, in our study population, TMP/SMX prophylaxis and infectious disease specialist approach were variables correlated with a better PjP outcome.
- Published
- 2017
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284. Functional connectivity in amygdalar-sensory/(pre)motor networks at rest: new evidence from the Human Connectome Project.
- Author
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Toschi N, Duggento A, and Passamonti L
- Subjects
- Connectome methods, Diffusion Tensor Imaging methods, Female, Humans, Magnetic Resonance Imaging methods, Male, Motor Cortex, Nerve Net, Neural Pathways, Amygdala physiology, Rest physiology
- Abstract
The word 'e-motion' derives from the Latin word 'ex-moveo' which literally means 'moving away from something/somebody'. Emotions are thus fundamental to prime action and goal-directed behavior with obvious implications for individual's survival. However, the brain mechanisms underlying the interactions between emotional and motor cortical systems remain poorly understood. A recent diffusion tensor imaging study in humans has reported the existence of direct anatomical connections between the amygdala and sensory/(pre)motor cortices, corroborating an initial observation in animal research. Nevertheless, the functional significance of these amygdala-sensory/(pre)motor pathways remain uncertain. More specifically, it is currently unclear whether a distinct amygdala-sensory/(pre)motor circuit can be identified with resting-state functional magnetic resonance imaging (rs-fMRI). This is a key issue, as rs-fMRI offers an opportunity to simultaneously examine distinct neural circuits that underpin different cognitive, emotional and motor functions, while minimizing task-related performance confounds. We therefore tested the hypothesis that the amygdala and sensory/(pre)motor cortices could be identified as part of the same resting-state functional connectivity network. To this end, we examined independent component analysis results in a very large rs-fMRI data-set drawn from the Human Connectome Project (n = 820 participants, mean age: 28.5 years). To our knowledge, we report for the first time the existence of a distinct amygdala-sensory/(pre)motor functional network at rest. rs-fMRI studies are now warranted to examine potential abnormalities in this circuit in psychiatric and neurological diseases that may be associated with alterations in the amygdala-sensory/(pre)motor pathways (e.g. conversion disorders, impulse control disorders, amyotrophic lateral sclerosis and multiple sclerosis)., (© 2017 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)
- Published
- 2017
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285. E3 Ligase RNF126 Directly Ubiquitinates Frataxin, Promoting Its Degradation: Identification of a Potential Therapeutic Target for Friedreich Ataxia.
- Author
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Benini M, Fortuni S, Condò I, Alfedi G, Malisan F, Toschi N, Serio D, Massaro DS, Arcuri G, Testi R, and Rufini A
- Subjects
- Catalysis, Cell Line, HEK293 Cells, Humans, Mitochondrial Proteins metabolism, Proteasome Endopeptidase Complex metabolism, Frataxin, Friedreich Ataxia metabolism, Iron-Binding Proteins metabolism, Ubiquitin metabolism, Ubiquitin-Protein Ligases metabolism, Ubiquitination physiology
- Abstract
Friedreich ataxia (FRDA) is a severe genetic neurodegenerative disease caused by reduced expression of the mitochondrial protein frataxin. To date, there is no therapy to treat this condition. The amount of residual frataxin critically affects the severity of the disease; thus, attempts to restore physiological frataxin levels are considered therapeutically relevant. Frataxin levels are controlled by the ubiquitin-proteasome system; therefore, inhibition of the frataxin E3 ligase may represent a strategy to achieve an increase in frataxin levels. Here, we report the identification of the RING E3 ligase RNF126 as the enzyme that specifically mediates frataxin ubiquitination and targets it for degradation. RNF126 interacts with frataxin and promotes its ubiquitination in a catalytic activity-dependent manner, both in vivo and in vitro. Most importantly, RNF126 depletion results in frataxin accumulation in cells derived from FRDA patients, highlighting the relevance of RNF126 as a new therapeutic target for Friedreich ataxia., (Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.)
- Published
- 2017
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286. Complexity Variability Assessment of Nonlinear Time-Varying Cardiovascular Control.
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Valenza G, Citi L, Garcia RG, Taylor JN, Toschi N, and Barbieri R
- Subjects
- Adult, Case-Control Studies, Electrocardiography, Female, Humans, Male, Models, Cardiovascular, Nonlinear Dynamics, Young Adult, Cardiovascular System physiopathology, Depressive Disorder, Major physiopathology, Heart Failure physiopathology, Parkinson Disease physiopathology, Stress Disorders, Post-Traumatic physiopathology
- Abstract
The application of complex systems theory to physiology and medicine has provided meaningful information about the nonlinear aspects underlying the dynamics of a wide range of biological processes and their disease-related aberrations. However, no studies have investigated whether meaningful information can be extracted by quantifying second-order moments of time-varying cardiovascular complexity. To this extent, we introduce a novel mathematical framework termed complexity variability, in which the variance of instantaneous Lyapunov spectra estimated over time serves as a reference quantifier. We apply the proposed methodology to four exemplary studies involving disorders which stem from cardiology, neurology and psychiatry: Congestive Heart Failure (CHF), Major Depression Disorder (MDD), Parkinson's Disease (PD), and Post-Traumatic Stress Disorder (PTSD) patients with insomnia under a yoga training regime. We show that complexity assessments derived from simple time-averaging are not able to discern pathology-related changes in autonomic control, and we demonstrate that between-group differences in measures of complexity variability are consistent across pathologies. Pathological states such as CHF, MDD, and PD are associated with an increased complexity variability when compared to healthy controls, whereas wellbeing derived from yoga in PTSD is associated with lower time-variance of complexity.
- Published
- 2017
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287. Resting state fMRI regional homogeneity correlates with cognition measures in subcortical vascular cognitive impairment.
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Diciotti S, Orsolini S, Salvadori E, Giorgio A, Toschi N, Ciulli S, Ginestroni A, Poggesi A, De Stefano N, Pantoni L, Inzitari D, and Mascalchi M
- Subjects
- Aged, Brain diagnostic imaging, Brain Mapping, Cerebrovascular Disorders diagnostic imaging, Cerebrovascular Disorders psychology, Cognition physiology, Cognitive Dysfunction diagnostic imaging, Executive Function physiology, Female, Humans, Longitudinal Studies, Magnetic Resonance Imaging, Male, Neuropsychological Tests, Rest, Brain physiopathology, Cerebrovascular Disorders physiopathology, Cognitive Dysfunction physiopathology
- Abstract
Background: The hyperintensity of cerebral white matter (WM) in T2-weighted MR images of elderly subjects due to small vessel disease (SVD) is associated with variable clinical features including mild cognitive impairment (MCI), also termed subcortical vascular cognitive impairment (SVCI). The latter is typically characterized by psychomotor slowing, attention deficits, and executive dysfunctions. We hypothesized that functional brain changes might be associated with these distinctive cognitive deficits in patients with SVCI., Methods: Resting-state fMRI (rsfMRI) signal was assessed in conjunction with performance on the Montreal Cognitive Assessment battery (MoCA) and Stroop test in 67 subjects with MCI and moderate to severe extension of cerebral WM T2 hyperintensities qualifying for SVCI. We performed a whole-brain analysis of regional homogeneity (ReHo) of rsfMRI in conjunction with cognitive test scores., Results: We observed a significant (p<0.05) negative association between ReHo and MoCA scores, with higher ReHo in the left posterior cerebellum (crus I) of patients with greater global cognitive impairment, and a significant positive association between ReHo and Stroop scores, with higher ReHo in the middle cingulate cortex bilaterally of patients with worse executive functions., Conclusion: ReHo of rsfMRI is significantly correlated with measurements of the cognitive deficits which are distinctive of SVCI. The increased activity could have a maladaptive or compensatory significance towards specific aspects of cognition., (Copyright © 2016 Elsevier B.V. All rights reserved.)
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- 2017
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288. Cerebrospinal Fluid Neurogranin as a Biomarker of Neurodegenerative Diseases: A Cross-Sectional Study.
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Lista S, Toschi N, Baldacci F, Zetterberg H, Blennow K, Kilimann I, Teipel SJ, Cavedo E, Dos Santos AM, Epelbaum S, Lamari F, Dubois B, Nisticò R, Floris R, Garaci F, and Hampel H
- Subjects
- Aged, Amyloid beta-Peptides cerebrospinal fluid, Biomarkers cerebrospinal fluid, Cross-Sectional Studies, Female, Humans, Male, Middle Aged, Peptide Fragments cerebrospinal fluid, tau Proteins cerebrospinal fluid, Neurodegenerative Diseases cerebrospinal fluid, Neurogranin cerebrospinal fluid
- Abstract
We investigated cerebrospinal fluid (CSF) concentrations of the postsynaptic biomarker neurogranin at baseline in cognitively healthy controls (HC) compared to individuals with mild cognitive impairment (MCI), patients with Alzheimer's disease (AD) dementia, and patients with frontotemporal dementia (FTD). CSF neurogranin was quantified using an in-house immunoassay in a cross-sectional multicenter study of 108 participants [AD dementia (n = 35), FTD (n = 9), MCI (n = 41), cognitively HC (n = 23)]. CSF neurogranin concentrations were significantly higher in AD patients compared with both HC subjects and FTD patients, suggesting that increased CSF neurogranin concentrations may indicate AD-related pathophysiology. CSF neurogranin was independently associated with both total tau and hyperphosphorylated tau proteins, whereas a non-significant correlation with the 42-amino acid-long amyloid-β peptide was evident. CSF neurogranin, however, was not superior to core AD biomarkers in differentiating HC from the three diagnostic groups, and it did not improve their diagnostic accuracy. We conclude that further classification and longitudinal studies are required to shed more light into the potential role of neurogranin as a pathophysiological biomarker of neurodegenerative diseases.
- Published
- 2017
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289. Motion sickness increases functional connectivity between visual motion and nausea-associated brain regions.
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Toschi N, Kim J, Sclocco R, Duggento A, Barbieri R, Kuo B, and Napadow V
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- Adult, Brain diagnostic imaging, Brain Mapping, Cerebrovascular Circulation physiology, Electrocardiography, Female, Heart Rate physiology, Humans, Magnetic Resonance Imaging, Motion Sickness diagnostic imaging, Nausea diagnostic imaging, Neural Pathways diagnostic imaging, Neural Pathways physiopathology, Oxygen blood, Photic Stimulation, Brain physiopathology, Motion Perception physiology, Motion Sickness physiopathology, Nausea physiopathology
- Abstract
The brain networks supporting nausea not yet understood. We previously found that while visual stimulation activated primary (V1) and extrastriate visual cortices (MT+/V5, coding for visual motion), increasing nausea was associated with increasing sustained activation in several brain areas, with significant co-activation for anterior insula (aIns) and mid-cingulate (MCC) cortices. Here, we hypothesized that motion sickness also alters functional connectivity between visual motion and previously identified nausea-processing brain regions. Subjects prone to motion sickness and controls completed a motion sickness provocation task during fMRI/ECG acquisition. We studied changes in connectivity between visual processing areas activated by the stimulus (MT+/V5, V1), right aIns and MCC when comparing rest (BASELINE) to peak nausea state (NAUSEA). Compared to BASELINE, NAUSEA reduced connectivity between right and left V1 and increased connectivity between right MT+/V5 and aIns and between left MT+/V5 and MCC. Additionally, the change in MT+/V5 to insula connectivity was significantly associated with a change in sympathovagal balance, assessed by heart rate variability analysis. No state-related connectivity changes were noted for the control group. Increased connectivity between a visual motion processing region and nausea/salience brain regions may reflect increased transfer of visual/vestibular mismatch information to brain regions supporting nausea perception and autonomic processing. We conclude that vection-induced nausea increases connectivity between nausea-processing regions and those activated by the nauseogenic stimulus. This enhanced low-frequency coupling may support continual, slowly evolving nausea perception and shifts toward sympathetic dominance. Disengaging this coupling may be a target for biobehavioral interventions aimed at reducing motion sickness severity., (Copyright © 2016 Elsevier B.V. All rights reserved.)
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- 2017
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290. Biomarker-guided classification scheme of neurodegenerative diseases.
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Baldacci F, Lista S, Garaci F, Bonuccelli U, Toschi N, and Hampel H
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- 2016
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291. Predicting seizures in untreated temporal lobe epilepsy using point-process nonlinear models of heartbeat dynamics.
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Valenza G, Romigi A, Citi L, Placidi F, Izzi F, Albanese M, Scilingo EP, Marciani MG, Duggento A, Guerrisi M, Toschi N, and Barbieri R
- Subjects
- Electrocardiography, Humans, Nonlinear Dynamics, Epilepsy, Temporal Lobe diagnosis, Heart Rate, Seizures diagnosis
- Abstract
Symptoms of temporal lobe epilepsy (TLE) are frequently associated with autonomic dysregulation, whose underlying biological processes are thought to strongly contribute to sudden unexpected death in epilepsy (SUDEP). While abnormal cardiovascular patterns commonly occur during ictal events, putative patterns of autonomic cardiac effects during pre-ictal (PRE) periods (i.e. periods preceding seizures) are still unknown. In this study, we investigated TLE-related heart rate variability (HRV) through instantaneous, nonlinear estimates of cardiovascular oscillations during inter-ictal (INT) and PRE periods. ECG recordings from 12 patients with TLE were processed to extract standard HRV indices, as well as indices of instantaneous HRV complexity (dominant Lyapunov exponent and entropy) and higher-order statistics (bispectra) obtained through definition of inhomogeneous point-process nonlinear models, employing Volterra-Laguerre expansions of linear, quadratic, and cubic kernels. Experimental results demonstrate that the best INT vs. PRE classification performance (balanced accuracy: 73.91%) was achieved only when retaining the time-varying, nonlinear, and non-stationary structure of heartbeat dynamical features. The proposed approach opens novel important avenues in predicting ictal events using information gathered from cardiovascular signals exclusively.
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- 2016
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292. Forecasting nanoparticle toxicity using nonlinear predictive regressor learning systems.
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Toschi N, Ciulli S, Diciotti S, Duggento A, Guerrisi M, Magrini A, Campagnolo L, and Pietroiusti A
- Subjects
- Nonlinear Dynamics, Support Vector Machine, Algorithms, Models, Statistical, Nanoparticles toxicity
- Abstract
Nanoparticle (NP) toxicity is determined by a vast number of topological, sterical, physico-chemical as well as biological properties, rendering a priori evaluation of the effect of NP on biological tissue as arduous as it is necessary and urgent. We aimed at mining the HORIZON 2020 MODENA COST NP cytotoxicity database through nonlinear predictive regressor learning systems in order to assess the power of available NP descriptors and assay characteristics in predicting NP toxicity. Specifically, we assessed the results of cytotoxicity assays performed on 57 NP and trained two different nonlinear regressors (Support Vector Regressors [SVR] with polynomical kernels and Radial Basis Function [RBF] regressors) within a nested-cross validation scheme for parameter optimization to predict toxicity as quantified by EC25, EC50 and slope while using the regressional ReliefF algorithm (RReliefF) for feature selection. Available NP attributes were material, coating, cell type, dispersion protocol, shape, 1st and 2nd dimension, aspect ratio, surface area, zeta potential and size in situ. In most regressor learning systems, after feature selection with the RReliefF algorithm, the correlation between real and estimated toxicity endpoint values increased monotonically with the number of included features, reaching values above 0.90. The best performance was obtained with RBF regressors, and the most informative features in predicting toxicity endpoints were related to nanoparticle structure. These trends did not change significantly between toxicity endpoints. In conclusion, EC25, EC50 and slope can be predicted with high correlation using purely data-driven, machine learning methods in Adenosine triphosphate (ATP)-based NP cytotoxicity assays.
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- 2016
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293. Reconstructing multivariate causal structure between functional brain networks through a Laguerre-Volterra based Granger causality approach.
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Duggento A, Valenza G, Passamonti L, Guerrisi M, Barbieri R, and Toschi N
- Subjects
- Humans, Models, Statistical, Multivariate Analysis, Brain anatomy & histology, Brain diagnostic imaging, Brain physiology, Magnetic Resonance Imaging methods, Signal Processing, Computer-Assisted
- Abstract
Classical multivariate approaches based on Granger causality (GC) which estimate functional connectivity in the brain are almost exclusively based on autoregressive models. Nevertheless, information available from past samples is limited due to both signal autocorrelation and necessarily low model orders. Consequently, multiple time-scales interactions are usually unaccounted for. To overcome these limitations, in this study we propose the use of discrete-time orthogonal Laguerre basis functions within a Wiener-Volterra decomposition of the BOLD signals to perform effective GC assessments of brain functional connectivity. We validate our method in synthetic noisy oscillator networks, and analyze experimental fMRI data from 30 healthy subjects publicly available within the Human Connectome Project (HCP). Synthetic results demonstrate that our Laguerre-Volterra based GC estimates outperform classical approaches in terms of accuracy in detecting true causal links while rejecting false causal links in complex nonlinear networks. Human data analysis shows for the first time that the default mode network modulates both the salience network as well as fronto-temporal circuits in a causal fashion.
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- 2016
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294. Distribution-aware estimation of the minimum achievable uncertainty in diffusion-tensor imaging (DTI).
- Author
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Duggento A, Giannelli M, Tessa C, Lanzafame S, Guerrisi M, and Toschi N
- Subjects
- Adult, Algorithms, Anisotropy, Echo-Planar Imaging methods, Healthy Volunteers, Humans, Magnetic Resonance Imaging methods, Male, Monte Carlo Method, Neuroimaging methods, Phantoms, Imaging, Signal-To-Noise Ratio, Uncertainty, White Matter diagnostic imaging, Brain diagnostic imaging, Diffusion Tensor Imaging methods, Image Processing, Computer-Assisted methods
- Abstract
Diffusion tensor imaging (DTI) provides exquisite sensitivity to structural and microstructural characteristics of brain tissue, and is routinely employed in advanced neuroimaging applications. DTI is commonly performed using intrinsically noisy echo-planar imaging techniques and poses high demands both on scanner performance and on in-scanner subject time, which in turn is directly related to the number of diffusion-weighting direction one requires. While DTI-derived indices such as fractional anisotropy (FA), diffusion tensor trace and anisotropy mode have proven extremely useful in characterizing disease-related aberrations, their estimation is commonly performed using fitting routines that do not properly take into account MRI noise distribution. In this paper, we present a distribution-aware maximum likelihood tensor estimation framework which also allows, for the first time, separate local noise estimation in both diffusion weighted and reference images. We validate our framework using multiple water phantom diffusion weighted acquisitions, and demonstrate its feasibility in human data. We then employ our framework within Monte Carlo simulations to show how the minimum achievable uncertainty attainable in DTI depends on signal-to-noise ratio (SNR) and number of diffusion gradient directions, demonstrating that these dependencies could be recast into simple power laws which may serve as guidelines for application-specific DTI protocol design.
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- 2016
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295. Brain-heart linear and nonlinear dynamics during visual emotional elicitation in healthy subjects.
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Valenza G, Greco A, Gentili C, Lanata A, Toschi N, Barbieri R, Sebastiani L, Menicucci D, Gemignani A, and Scilingo EP
- Subjects
- Electroencephalography, Humans, Signal Processing, Computer-Assisted, Brain physiology, Emotions physiology, Heart Rate physiology, Linear Models, Nonlinear Dynamics
- Abstract
This study investigates brain-heart dynamics during visual emotional elicitation in healthy subjects through linear and nonlinear coupling measures of EEG spectrogram and instantaneous heart rate estimates. To this extent, affective pictures including different combinations of arousal and valence levels, gathered from the International Affective Picture System, were administered to twenty-two healthy subjects. Time-varying maps of cortical activation were obtained through EEG spectral analysis, whereas the associated instantaneous heartbeat dynamics was estimated using inhomogeneous point-process linear models. Brain-Heart linear and nonlinear coupling was estimated through the Maximal Information Coefficient (MIC), considering EEG time-varying spectra and point-process estimates defined in the time and frequency domains. As a proof of concept, we here show preliminary results considering EEG oscillations in the θ band (4-8 Hz). This band, indeed, is known in the literature to be involved in emotional processes. MIC highlighted significant arousal-dependent changes, mediated by the prefrontal cortex interplay especially occurring at intermediate arousing levels. Furthermore, lower and higher arousing elicitations were associated to not significant brain-heart coupling changes in response to pleasant/unpleasant elicitations.
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- 2016
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296. Prediction of Impaired Performance in Trail Making Test in MCI Patients With Small Vessel Disease Using DTI Data.
- Author
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Ciulli S, Citi L, Salvadori E, Valenti R, Poggesi A, Inzitari D, Mascalchi M, Toschi N, Pantoni L, and Diciotti S
- Subjects
- Aged, Aged, 80 and over, Brain diagnostic imaging, Female, Humans, Machine Learning, Male, Neuropsychological Tests, Support Vector Machine, Cerebrovascular Disorders diagnostic imaging, Cognitive Dysfunction diagnosis, Diffusion Tensor Imaging methods, Image Interpretation, Computer-Assisted methods
- Abstract
Mild cognitive impairment (MCI) is a common condition in patients with diffuse hyperintensities of cerebral white matter (WM) in T2-weighted magnetic resonance images and cerebral small vessel disease (SVD). In MCI due to SVD, the most prominent feature of cognitive impairment lies in degradation of executive functions, i.e., of processes that supervise the organization and execution of complex behavior. The trail making test is a widely employed test sensitive to cognitive processing speed and executive functioning. MCI due to SVD has been hypothesized to be the effect of WM damage, and diffusion tensor imaging (DTI) is a well-established technique for in vivo characterization of WM. We propose a machine learning scheme tailored to 1) predicting the impairment in executive functions in patients with MCI and SVD, and 2) examining the brain substrates of this impairment. We employed data from 40 MCI patients with SVD and created feature vectors by averaging mean diffusivity (MD) and fractional anisotropy maps within 50 WM regions of interest. We trained support vector machines (SVMs) with polynomial as well as radial basis function kernels using different DTI-derived features while simultaneously optimizing parameters in leave-one-out nested cross validation. The best performance was obtained using MD features only and linear kernel SVMs, which were able to distinguish an impaired performance with high sensitivity (72.7%-89.5%), specificity (71.4%-83.3%), and accuracy (77.5%-80.0%). While brain substrates of executive functions are still debated, feature ranking confirm that MD in several WM regions, not limited to the frontal lobes, are truly predictive of executive functions.
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- 2016
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297. White matter microstructural damage and depressive symptoms in patients with mild cognitive impairment and cerebral small vessel disease: the VMCI-Tuscany Study.
- Author
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Pasi M, Poggesi A, Salvadori E, Diciotti S, Ciolli L, Del Bene A, Marini S, Nannucci S, Pescini F, Valenti R, Ginestroni A, Toschi N, Mascalchi M, Inzitari D, and Pantoni L
- Subjects
- Activities of Daily Living, Aged, Aged, 80 and over, Analysis of Variance, Atrophy pathology, Cerebral Cortex pathology, Diffusion Tensor Imaging, Female, Geriatric Assessment methods, Humans, Longitudinal Studies, Magnetic Resonance Imaging, Male, Neuropsychological Tests, Psychiatric Status Rating Scales, Stroke, Lacunar pathology, Temporal Lobe pathology, White Matter ultrastructure, Cerebral Small Vessel Diseases pathology, Cognitive Dysfunction pathology, Cognitive Dysfunction psychology, Depressive Disorder pathology, White Matter pathology
- Abstract
Background and Purpose: Disruption of cortical-subcortical circuits related to small vessel disease (SVD) may predispose to depression in the elderly. We aimed to determine the independent association between white matter (WM) microstructural damage, evaluated with diffusion tensor imaging (DTI), and depressive symptoms in a cohort of elderly subjects with mild cognitive impairment (MCI) and SVD., Methods: The vascular mild cognitive impairment (VMCI)-Tuscany Study is an observational multicentric longitudinal study that enrolled patients with MCI and moderate to severe degrees of WM hyperintensities on MRI. Lacunar infarcts, cortical atrophy, medial temporal lobe atrophy, microbleeds, and DTI-derived indices (mean diffusivity, MD and fractional anisotropy, FA) were evaluated on baseline MRI. Geriatric Depression Scale (GDS) (score 0-15) was used to assess depressive symptoms. An extensive neuropsychological battery, Instrumental Activities of Daily Living scale, and the Short Physical Performance Battery were used for cognitive, functional, and motor assessments, respectively., Results: Seventy-six patients (mean age: 75.1 ± 6.8 years) were included. Univariate analyses showed a significant association between GDS score and both DTI-derived indices (MD: r = 0.307, p = 0.007; FA: r = -0.245; p = 0.033). The association remained significant after adjustment for age, WM hyperintensities severity, global cognitive, functional and motor performances, and antidepressant therapy (MD: r = 0.361, p = 0.002; FA: r = -0.277; p = 0.021)., Conclusions: These results outline the presence of an association between WM microstructural damage and depressive symptoms in MCI patients with SVD. This relationship does not seem to be mediated by disability, cognitive, and motor impairment, thus supporting the vascular depression hypothesis., (Copyright © 2015 John Wiley & Sons, Ltd.)
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- 2016
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298. In vivo functional connectome of human brainstem nuclei of the ascending arousal, autonomic, and motor systems by high spatial resolution 7-Tesla fMRI.
- Author
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Bianciardi M, Toschi N, Eichner C, Polimeni JR, Setsompop K, Brown EN, Hämäläinen MS, Rosen BR, and Wald LL
- Subjects
- Adult, Algorithms, Arousal, Autonomic Nervous System diagnostic imaging, Brain Mapping methods, Female, Humans, Image Processing, Computer-Assisted methods, Male, Motor Neurons pathology, Probability, Young Adult, Brain Stem diagnostic imaging, Brain Stem physiopathology, Connectome, Magnetic Resonance Imaging
- Abstract
Objective: Our aim was to map the in vivo human functional connectivity of several brainstem nuclei with the rest of the brain by using seed-based correlation of ultra-high magnetic field functional magnetic resonance imaging (fMRI) data., Materials and Methods: We used the recently developed template of 11 brainstem nuclei derived from multi-contrast structural MRI at 7 Tesla as seed regions to determine their connectivity to the rest of the brain. To achieve this, we used the increased contrast-to-noise ratio of 7-Tesla fMRI compared with 3 Tesla and time-efficient simultaneous multi-slice imaging to cover the brain with high spatial resolution (1.1-mm isotropic nominal resolution) while maintaining a short repetition time (2.5 s)., Results: The delineated Pearson's correlation-based functional connectivity diagrams (connectomes) of 11 brainstem nuclei of the ascending arousal, motor, and autonomic systems from 12 controls are presented and discussed in the context of existing histology and animal work., Conclusion: Considering that the investigated brainstem nuclei play a crucial role in several vital functions, the delineated preliminary connectomes might prove useful for future in vivo research and clinical studies of human brainstem function and pathology, including disorders of consciousness, sleep disorders, autonomic disorders, Parkinson's disease, and other motor disorders.
- Published
- 2016
- Full Text
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299. Uncovering brain-heart information through advanced signal and image processing.
- Author
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Valenza G, Toschi N, and Barbieri R
- Subjects
- Brain physiology
- Abstract
Through their dynamical interplay, the brain and the heart ensure fundamental homeostasis and mediate a number of physiological functions as well as their disease-related aberrations. Although a vast number of ad hoc analytical and computational tools have been recently applied to the non-invasive characterization of brain and heart dynamic functioning, little attention has been devoted to combining information to unveil the interactions between these two physiological systems. This theme issue collects contributions from leading experts dealing with the development of advanced analytical and computational tools in the field of biomedical signal and image processing. It includes perspectives on recent advances in 7 T magnetic resonance imaging as well as electroencephalogram, electrocardiogram and cerebrovascular flow processing, with the specific aim of elucidating methods to uncover novel biological and physiological correlates of brain-heart physiology and physiopathology., (© 2016 The Author(s).)
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- 2016
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300. Globally conditioned Granger causality in brain-brain and brain-heart interactions: a combined heart rate variability/ultra-high-field (7 T) functional magnetic resonance imaging study.
- Author
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Duggento A, Bianciardi M, Passamonti L, Wald LL, Guerrisi M, Barbieri R, and Toschi N
- Subjects
- Magnetic Resonance Imaging methods
- Abstract
The causal, directed interactions between brain regions at rest (brain-brain networks) and between resting-state brain activity and autonomic nervous system (ANS) outflow (brain-heart links) have not been completely elucidated. We collected 7 T resting-state functional magnetic resonance imaging (fMRI) data with simultaneous respiration and heartbeat recordings in nine healthy volunteers to investigate (i) the causal interactions between cortical and subcortical brain regions at rest and (ii) the causal interactions between resting-state brain activity and the ANS as quantified through a probabilistic, point-process-based heartbeat model which generates dynamical estimates for sympathetic and parasympathetic activity as well as sympathovagal balance. Given the high amount of information shared between brain-derived signals, we compared the results of traditional bivariate Granger causality (GC) with a globally conditioned approach which evaluated the additional influence of each brain region on the causal target while factoring out effects concomitantly mediated by other brain regions. The bivariate approach resulted in a large number of possibly spurious causal brain-brain links, while, using the globally conditioned approach, we demonstrated the existence of significant selective causal links between cortical/subcortical brain regions and sympathetic and parasympathetic modulation as well as sympathovagal balance. In particular, we demonstrated a causal role of the amygdala, hypothalamus, brainstem and, among others, medial, middle and superior frontal gyri, superior temporal pole, paracentral lobule and cerebellar regions in modulating the so-called central autonomic network (CAN). In summary, we show that, provided proper conditioning is employed to eliminate spurious causalities, ultra-high-field functional imaging coupled with physiological signal acquisition and GC analysis is able to quantify directed brain-brain and brain-heart interactions reflecting central modulation of ANS outflow., (© 2016 The Author(s).)
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- 2016
- Full Text
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