Combined analysis of multimodal brain imaging data for the study and prevention of major depressive disorders in high risk offspring

The serotonin (5‐HT) neurotransmitter system has been implicated in the pathogenesis of major depression (Blier et al., 1990; Czesak et al., 2006; Lemonde et al., 2003; Stockmeier et al., 1998). This system can be investigated in vivo via Positron Emission Tomography (PET), a nuclear imaging technology that uses radioactively labeled molecules (i.e. radioligands) to quantify and visualize biological processes, such as blood flow, brain metabolism, and distribution of proteins throughout the body. In investigations related to depression specifically, PET is used for measuring in vivo the closest quantification to in vitro concentration of available receptors of the serotonin system (i.e. the binding potential, BPF) (Innis et al., 2007)

Non-Invasive Fully Quantitative Positron Emission Tomography Imaging

Positron emission tomography (PET), a nuclear imaging technology for in vivo quantification of blood flow, metabolism, and protein distribution, is an invaluable tool for developing novel personalized therapies for high morbidity and mortality brain disorders (Benton et al., 2007; Depression Guideline Panel, 1999; Michalak et al., 2008; Trivedi, 2003; Vogt et al., 1994)

A hybrid deconvolution approach for estimation of in vivo non-displaceable binding for brain PET targets without a reference region

Background and aim Estimation of a PET tracer’s non-displaceable distribution volume (VND) is required for quantification of specific binding to its target of interest. VND is generally assumed to be comparable brain-wide and is determined either from a reference region devoid of the target, often not available for many tracers and targets, or by imaging each subject before and after blocking the target with another molecule that has high affinity for the target, which is cumbersome and involves additional radiation exposure. Here we propose, and validate for the tracers [11C]DASB and [11C]CUMI-101, a new data-driven hybrid deconvolution approach (HYDECA) that determines VND at the individual level without requiring either a reference region or a blocking study. Methods HYDECA requires the tracer metabolite-corrected concentration curve in blood plasma and uses a singular value decomposition to estimate the impulse response function across several brain regions from measured time activity curves. HYDECA decomposes each region’s impulse response function into the sum of a parametric non-displaceable component, which is a function of VND, assumed common across regions, and a nonparametric specific component. These two components differentially contribute to each impulse response function. Different regions show different contributions of the two components, and HYDECA examines data across regions to find a suitable common VND. HYDECA implementation requires determination of two tuning parameters, and we propose two strategies for objectively selecting these parameters for a given tracer: using data from blocking studies, and realistic simulations of the tracer. Using available test-retest data, we compare HYDECA estimates of VND and binding potentials to those obtained based on VND estimated using a purported reference region. Results For [11C]DASB and [11C]CUMI-101, we find that regardless of the strategy used to optimize the tuning parameters, HYDECA provides considerably less biased estimates of VND than those obtained, as is commonly done, using a non-ideal reference region. HYDECA test-retest reproducibility is comparable to that obtained using a VND determined from a non-ideal reference region, when considering the binding potentials BPP and BPND. Conclusions HYDECA can provide subject-specific estimates of VND without requiring a blocking study for tracers and targets for which a valid reference region does not exist

Assessment of immunostimulatory responses to the antimiR-22 oligonucleotide compound RES-010 in human peripheral blood mononuclear cells

microRNA-22 (miR-22) is a key regulator of lipid and energy homeostasis and represents a promising therapeutic target for NAFLD and obesity. We have previously identified a locked nucleic acid (LNA)-modified antisense oligonucleotide compound complementary to miR-22, designated as RES-010 that mediated robust inhibition of miR-22 function in cultured cells and in vivo. In this study we investigated the immune potential of RES-010 in human peripheral blood mononuclear cells (PBMCs). We treated fresh human peripheral blood mononuclear cells isolated from six healthy volunteers with different concentrations of the RES-010 compound and assessed its proinflammatory effects by quantifying IL-1β, IL-6, IFN-γ, TNF-α, IFN-α2a, IFN-β, IL-10, and IL-17A in the supernatants collected 24 h of treatment with RES-010. The T-cell activation markers, CD69, HLA-DR, and CD25 were evaluated by flow cytometry after 24 and 144 h of treatment, respectively, whereas cell viability was assessed after 24 h of treatment with RES-010. Our results show that RES-010 compound does not induce any significant immunostimulatory responses in human PBMCs in vitro compared to controls, implying that the proinflammatory potential of RES-010 is low.</p

RIQUALIFICAZIONE DELLE AREE DEL QUADRANTE NORD E NORD EST DI TORINO: AMBITO "SCALO VANCHIGLIA"

La costruzione di un’ipotesi di lavoro convincente per le aree di concorso deve misurarsi con tutto il territorio cittadino e deve conseguentemente affrontare il problema nella sua interezza, inserendo i tre ambiti all’interno di un discorso unitario. Per questo motivo abbiamo scelto di lavorare su tutte le tre aree di concorso, suggerendo una strategia unitaria, pur riconoscendo i tre temi come distinti e proponendo soluzioni rigorosamente indipendenti e contenute all’interno degli ambiti di concorso. Occuparsi di una sola area rischia infatti di restringere eccessivamente il campo della ricerca, limitando gli scopi del progetto ed incoraggiando a trascurare le conseguenze che si producono sulle altre parti della città. Al contrario, lavorare a tutte le tre aree contemporaneamente significa dotarsi, per ogni progetto, di ulteriori strumenti di verifica interna. L’identità delle singole aree di concorso emerge con maggiore nettezza dal confronto con le altre. La chiarezza del discorso globale si traduce in precisione delle proposte specifiche.La nostra proposta accetta alcuni suggerimenti dalla Torino storica: riconosce i tempi lunghi della crescita della città e prescrive un'umiltà di fondo per tutti gli edifici che propone di realizzare (propone di realizzare case che sanno di non essere le uniche al mondo). Dalla città storica, accettiamo anche di pensare lo spazio pubblico come qualcosa di prezioso, e quindi relativamente raro, non esteso uniformemente in base a fraintesi criteri di equità. Per avere qualità, lo spazio pubblico deve infatti essere distribuito con precisione. Questa precisione è possibile solo riducendo la quantità di spazio pubblico ed aumentandone la qualità e l’intensità. In sostituzione di sconfinate estensioni di (presunto) spazio pubblico senza alcun tratto distintivo è possibile introdurre ampie porzioni di verde privato o servizi, che possono contribuire alla figura della città senza essere immediatamente accessibili a tutti. Il verde privato consente inoltre alla città di produrre almeno una parte dei prodotti agricoli che consuma e di ridurre i costi di gestione di un verde pubblico comunque inefficiente, consentendo di concentrare le risorse su alcuni luoghi ben definiti. Si può così costruire una città intensa e verde allo stesso tempo, capace di nutrire i suoi abitanti e capace di produrre la pressione urbana sufficiente ad attivarne gli spazi pubblici

A Log-normal Dispersion Model for Parametric Deconvolution of DSC-MRI Images: Assessment on Simulated Data

none3noneZANDERIGO F; A. BERTOLDO; COBELLI CZanderigo, Francesca; Bertoldo, Alessandra; Cobelli, Claudi

Nonlinear Stochastic Regularization to Characterize Tissue Residue Function in Bolus-Tracking MRI: Assessment and Comparison With SVD, Block-Circulant SVD, and Tikhonov

An accurate characterization of tissue residue function R(t) in bolus-tracking magnetic resonance imaging is of crucial importance to quantify cerebral hemodynamics. R(t) estimation requires to solve a deconvolution problem. The most popular deconvolution method is singular value decomposition (SVD). However, SVD is known to bear some limitations, e.g., R(t) profiles exhibit nonphysiological oscillations and take on negative values. In addition, SVD estimates are biased in presence of bolus delay and dispersion. Recently, other deconvolution methods have been proposed, in particular block-circulant SVD (cSVD) and Tikhonov regularization (TIKH). Here we propose a new method based on nonlinear stochastic regularization (NSR). NSR is tested on simulated data and compared with SVD, cSVD, and TIKH in presence and absence of bolus dispersion. A clinical case in one patient has also been considered. NSR is shown to perform better than SVD, cSVD, and TIKH in reconstructing both the peak and the residue function, in particular when bolus dispersion is considered. In addition, differently from SVD, cSVD, and TIKH, NSR always provides positive and smooth R(t)