Chronic Neuropsychological Sequelae in a Patient with Nontumorous Anti-NMDA-Receptor Encephalitis

Anti-N-methyl-D-aspartate receptor encephalitis is a neurological, autoimmune disorder tightly conceptualized only as recently as the mid-2000s. It presents itself in a combination of psychiatric, neurological, and autonomic features. We observe a unique case with probable earlier episode (prior to the mid-2000s conceptualization of the disease) and a later relapse, accompanying a comprehensive neuropsychological profile tracked after the relapse and subsequent improvement. Neurocognitive findings revealed residual frontal deficits with mood changes even in the state after plasmapheresis. This case is the first to describe posttreatment cognition in anti-NMDAR encephalitis after probable serial autoimmune episodes

PPAR? Downregulation by TGF in Fibroblast and Impaired Expression and Function in Systemic Sclerosis: A Novel Mechanism for Progressive Fibrogenesis

The nuclear orphan receptor peroxisome proliferator-activated receptor-gamma (PPAR-γ) is expressed in multiple cell types in addition to adipocytes. Upon its activation by natural ligands such as fatty acids and eicosanoids, or by synthetic agonists such as rosiglitazone, PPAR-γ regulates adipogenesis, glucose uptake and inflammatory responses. Recent studies establish a novel role for PPAR-γ signaling as an endogenous mechanism for regulating transforming growth factor-ß (TGF-ß)- dependent fibrogenesis. Here, we sought to characterize PPAR-γ function in the prototypic fibrosing disorder systemic sclerosis (SSc), and delineate the factors governing PPAR-γ expression. We report that PPAR-γ levels were markedly diminished in skin and lung biopsies from patients with SSc, and in fibroblasts explanted from the lesional skin. In normal fibroblasts, treatment with TGF-ß resulted in a time- and dose-dependent down-regulation of PPAR-γ expression. Inhibition occurred at the transcriptional level and was mediated via canonical Smad signal transduction. Genome-wide expression profiling of SSc skin biopsies revealed a marked attenuation of PPAR-γ levels and transcriptional activity in a subset of patients with diffuse cutaneous SSc, which was correlated with the presence of a ''TGF-ß responsive gene signature'' in these biopsies. Together, these results demonstrate that the expression and function of PPAR-γ are impaired in SSc, and reveal the existence of a reciprocal inhibitory cross-talk between TGF-ß activation and PPAR-γ signaling in the context of fibrogenesis. In light of the potent anti-fibrotic effects attributed to PPAR-γ, these observations lead us to propose that excessive TGF-ß activity in SSc accounts for impaired PPAR-γ function, which in turn contributes to unchecked fibroblast activation and progressive fibrosis. © 2010 Wei et al

Uncertainty quantification in graph-based classification of high dimensional data

Classification of high dimensional data finds wide-ranging applications. In many of these applications equipping the resulting classification with a measure of uncertainty may be as important as the classification itself. In this paper we introduce, develop algorithms for, and investigate the properties of, a variety of Bayesian models for the task of binary classification; via the posterior distribution on the classification labels, these methods automatically give measures of uncertainty. The methods are all based around the graph formulation of semi-supervised learning. We provide a unified framework which brings together a variety of methods which have been introduced in different communities within the mathematical sciences. We study probit classification in the graph-based setting, generalize the level-set method for Bayesian inverse problems to the classification setting, and generalize the Ginzburg-Landau optimization-based classifier to a Bayesian setting; we also show that the probit and level set approaches are natural relaxations of the harmonic function approach introduced in [Zhu et al 2003]. We introduce efficient numerical methods, suited to large data-sets, for both MCMC-based sampling as well as gradient-based MAP estimation. Through numerical experiments we study classification accuracy and uncertainty quantification for our models; these experiments showcase a suite of datasets commonly used to evaluate graph-based semi-supervised learning algorithms.Comment: 33 pages, 14 figure

Feature extraction based on bio-inspired model for robust emotion recognition

Emotional state identification is an important issue to achieve more natural speech interactive systems. Ideally, these systems should also be able to work in real environments in which generally exist some kind of noise. Several bio-inspired representations have been applied to artificial systems for speech processing under noise conditions. In this work, an auditory signal representation is used to obtain a novel bio-inspired set of features for emotional speech signals. These characteristics, together with other spectral and prosodic features, are used for emotion recognition under noise conditions. Neural models were trained as classifiers and results were compared to the well-known mel-frequency cepstral coefficients. Results show that using the proposed representations, it is possible to significantly improve the robustness of an emotion recognition system. The results were also validated in a speaker independent scheme and with two emotional speech corpora.Fil: Albornoz, Enrique Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Milone, Diego Humberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Rufiner, Hugo Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentin

Suv4-20h Histone Methyltransferases Promote Neuroectodermal Differentiation by Silencing the Pluripotency-Associated Oct-25 Gene

Post-translational modifications (PTMs) of histones exert fundamental roles in regulating gene expression. During development, groups of PTMs are constrained by unknown mechanisms into combinatorial patterns, which facilitate transitions from uncommitted embryonic cells into differentiated somatic cell lineages. Repressive histone modifications such as H3K9me3 or H3K27me3 have been investigated in detail, but the role of H4K20me3 in development is currently unknown. Here we show that Xenopus laevis Suv4-20h1 and h2 histone methyltransferases (HMTases) are essential for induction and differentiation of the neuroectoderm. Morpholino-mediated knockdown of the two HMTases leads to a selective and specific downregulation of genes controlling neural induction, thereby effectively blocking differentiation of the neuroectoderm. Global transcriptome analysis supports the notion that these effects arise from the transcriptional deregulation of specific genes rather than widespread, pleiotropic effects. Interestingly, morphant embryos fail to repress the Oct4-related Xenopus gene Oct-25. We validate Oct-25 as a direct target of xSu4-20h enzyme mediated gene repression, showing by chromatin immunoprecipitaton that it is decorated with the H4K20me3 mark downstream of the promoter in normal, but not in double-morphant, embryos. Since knockdown of Oct-25 protein significantly rescues the neural differentiation defect in xSuv4-20h double-morphant embryos, we conclude that the epistatic relationship between Suv4-20h enzymes and Oct-25 controls the transit from pluripotent to differentiation-competent neural cells. Consistent with these results in Xenopus, murine Suv4-20h1/h2 double-knockout embryonic stem (DKO ES) cells exhibit increased Oct4 protein levels before and during EB formation, and reveal a compromised and biased capacity for in vitro differentiation, when compared to normal ES cells. Together, these results suggest a regulatory mechanism, conserved between amphibians and mammals, in which H4K20me3-dependent restriction of specific POU-V genes directs cell fate decisions, when embryonic cells exit the pluripotent state

Chronic Neuropsychological Sequelae in a Patient with Nontumorous Anti-NMDA-Receptor Encephalitis

Anti-N-methyl-D-aspartate receptor encephalitis is a neurological, autoimmune disorder tightly conceptualized only as recently as the mid-2000s. It presents itself in a combination of psychiatric, neurological, and autonomic features. We observe a unique case with probable earlier episode (prior to the mid-2000s conceptualization of the disease) and a later relapse, accompanying a comprehensive neuropsychological profile tracked after the relapse and subsequent improvement. Neurocognitive findings revealed residual frontal deficits with mood changes even in the state after plasmapheresis. This case is the first to describe posttreatment cognition in anti-NMDAR encephalitis after probable serial autoimmune episodes

Retargeted adenoviruses for radiation-guided gene delivery

The combination of radiation with radiosensitizing gene delivery or oncolytic viruses promises to provide an advantage that could improve the therapeutic results for glioblastoma. X-rays can induce significant molecular changes in cancer cells. We isolated the GIRLRG peptide that binds to radiation-inducible 78 kDa glucose-regulated protein (GRP78), which is overexpressed on the plasma membranes of irradiated cancer cells and tumor-associated microvascular endothelial cells. The goal of our study was to improve tumor-specific adenovirus-mediated gene delivery by selectively targeting the adenovirus binding to this radiation-inducible protein. We employed an adenoviral fiber replacement approach to conduct a study of the targeting utility of GRP78-binding peptide. We have developed fiber-modified adenoviruses encoding the GRP78-binding peptide inserted into the fiber-fibritin. We have evaluated the reporter gene expression of fiber-modified adenoviruses in vitro using a panel of glioma cells and a human D54MG tumor xenograft model. The obtained results demonstrated that employment of the GRP78-binding peptide resulted in increased gene expression in irradiated tumors following infection with fiber-modified adenoviruses, compared with untreated tumor cells. These studies demonstrate the feasibility of adenoviral retargeting using the GRP78-binding peptide that selectively recognizes tumor cells responding to radiation treatment

Flow Measurements via Two-particle Azimuthal Correlations in Au + Au Collisions at sqrt(s_NN) = 130 GeV

Two particle azimuthal correlation functions are presented for charged hadrons produced in Au + Au collisions at RHIC sqrt(s_NN) = 130 GeV. The measurements permit determination of elliptic flow without event-by-event estimation of the reaction plane. The extracted elliptic flow values v_2 show significant sensitivity to both the collision centrality and the transverse momenta of emitted hadrons, suggesting rapid thermalization and relatively strong velocity fields. When scaled by the eccentricity of the collision zone, epsilon, the scaled elliptic flow shows little or no dependence on centrality for charged hadrons with relatively low p_T. A breakdown of this epsilon scaling is observed for charged hadrons with p_T > 1.0 GeV/c for the most central collisions.Comment: 6 pages, RevTeX 3, 4 figures, 307 authors, submitted to Phys. Rev. Lett. on 11 April 2002. Plain text data tables for the points plotted in figures for this and previous PHENIX publications are (will be made) publicly available at http://www.phenix.bnl.gov/phenix/WWW/run/phenix/papers.htm

Net Charge Fluctuations in Au + Au Interactions at sqrt(s_NN) = 130 GeV

Data from Au + Au interactions at sqrt(s_NN) = 130 GeV, obtained with the PHENIX detector at RHIC, are used to investigate local net charge fluctuations among particles produced near mid-rapidity. According to recent suggestions, such fluctuations may carry information from the Quark Gluon Plasma. This analysis shows that the fluctuations are dominated by a stochastic distribution of particles, but are also sensitive to other effects, like global charge conservation and resonance decays.Comment: 6 pages, RevTeX 3, 3 figures, 307 authors, submitted to Phys. Rev. Lett. on 21 March, 2002. Plain text data tables for the points plotted in figures for this and previous PHENIX publications are (will be made) publicly available at http://www.phenix.bnl.gov/phenix/WWW/run/phenix/papers.htm