Conception d'un microsystème informatique dédicacé au traitement des signaux électrophysiologiques du sommeil. THEME I3 Applications du traitement du signal

Le présent article décrit une méthode d'analyse automatique de tracés polygraphiques de sommeil. Une application temps réel du logiciel sur microsystème est évoquée. Un tel système permet notamment - d'alléger le travail de cotation (± 4 heures par nuit analysée et par patient) - de réduire la part de subjectivité et les différences d'interprétation entre cotateurs créant ainsi une structure d'analyse plus rigoureuse. Les techniques d'analyse du signal employées sont: - la prédiction linéaire pour les électroencéphalogrammes ; - la corrélation pour la détection de mouvements oculaires; - le sous-échantillonnage pour l'électromyogramme . Un arbre de décision déterministe conduit aux stades de sommeil. Le taux d'accord avec l'analyse visuelle avoisine les 80 %

Positron emission tomography and histopathology in Creutzfeldt-Jakob disease

We studied a 62-year-old man with Creutzfeldt-Jakob disease (CJD), using positron emission tomography (PET) and (18F)-2-fluoro-2-deoxy-D-glucose (FDG). Glucose metabolism was heterogeneously decreased throughout the brain. At autopsy, regional distributions of spongiosis, astrogliosis, and neuronal loss correlated with premortem regional metabolic deficits. These results suggest that PET with FDG may provide metabolic regional markers for CJD neuropathology.Case ReportsJournal ArticleResearch Support, Non-U.S. Gov'tinfo:eu-repo/semantics/publishe

Brain glucose metabolism and dopamine D2 receptor analysis in a patient with hemiparkinsonism-hemiatrophy syndrome.

We report findings on brain glucose metabolism and dopamine D2 receptors generated by positron emission tomography (PET) in a 67-year-old woman with right hemiparkinsonism-hemiatrophy syndrome (HP-HA). PET with [18F]-fluorodeoxyglucose (FDG) showed marked glucose metabolism asymmetry. There were significant reductions in glucose uptake at the level of the basal ganglia and, to lesser extent, in the fronto-parietal cortex contralateral to the clinically involved side. These changes were different from those found in a patient with hemi-Parkinson's disease who was scanned under similar conditions. Because the patient with HP-HA had only minimal response to levodopa therapy, we evaluated post-synaptic dopaminergic structures using PET with [18F]-fluoroethylspiperone (FESP). No striatal binding asymmetry was found in FESP/PET, which suggests a sparing of striatal dopamine D2 receptors. The changes in FDG uptake which we found were in brain areas relevant to the clinical features of HP-HA syndrome. In addition, our study provides evidence that FDG/PET may help to differentiate HP-HA syndrome from hemi-Parkinson's disease. In most instances, since HP-HA is associated with a more benign clinical course than Parkinson's disease, this distinction is of clinical important

CSES Module 3 Full Release

The module was administered as a post-election interview. The resulting data are provided along with voting, demographic, district and macro variables in a single dataset. CSES Variable List The list of variables is being provided on the CSES Website to help in understanding what content is available from CSES, and to compare the content available in each module. Themes: MICRO-LEVEL DATA: Identification and study administration variables: weighting factors; election type; date of election 1st and 2nd round; study timing (post election study, pre-election and post-election study, between rounds of majoritarian election); mode of interview; gender of interviewer; date questionnaire administered; primary electoral district of respondent; number of days the interview was conducted after the election Demography: age; gender; education; marital status; union membership; union membership of others in household; business association membership, farmers´ association membership; professional association membership; current employment status; main occupation; socio economic status; employment type - public or private; industrial sector; current employment status, occupation, socio economic status, employment type - public or private, and industrial sector of spouse; household income; number of persons in household; number of children in household under the age of 18; attendance at religious services; religiosity; religious denomination; language usually spoken at home; race; ethnicity; region of residence; rural or urban residence Survey variables: most important issues of election; candidates competencies to deal with most important issues; difference who is in power and who people vote for; evaluation of governments performance; party and leader that represent respondent´s view best; sympathy scale for selected parties and political leaders; assessment of parties and political leaders on a left-right-scale; self-assessment on a left-right-scale; differences of choice options; campaign involvement; satisfaction with democracy; party identification; intensity of party identification; respondent cast a ballot at the current and the previous election; vote choice (presidential, lower house and upper house elections) at the current and the previous election; respondent cast candidate preference vote at the current and the previous election; political information items DISTRICT-LEVEL DATA: number of seats contested in electoral district; number of candidates; number of party lists; percent vote of different parties; official voter turnout in electoral district MACRO-LEVEL DATA: election outcomes by parties in current (lower house/upper house) legislative election; percent of seats in lower house received by parties in current lower house/upper house election; percent of seats in upper house received by parties in current lower house/upper house election; percent of votes received by presidential candidate of parties in current elections; electoral turnout; party of the president and the prime minister before and after the election; number of portfolios held by each party in cabinet, prior to and after the most recent election; size of the cabinet after the most recent election; number of parties participating in election; ideological families of parties; left-right position of parties assigned by experts and alternative dimensions; most salient factors in the election; fairness of the election; formal complaints against national level results; election irregularities reported; scheduled and held date of election; irregularities of election date; extent of election violence and post election violence; geographic concentration of violence; post-election protest; electoral alliances permitted during the election campaign; existing electoral alliances; requirements for joint party lists; possibility of apparentement and types of apparentement agreements; multi-party endorsements on ballot; votes cast; voting procedure; voting rounds; party lists close, open, or flexible; transferable votes; cumulated votes if more than one can be cast; compulsory voting; party threshold; unit for the threshold; freedom house rating; democracy-autocracy polity IV rating; age of the current regime; regime: type of executive; number of months since last lower house and last presidential election; electoral formula for presidential elections; electoral formula in all electoral tiers (majoritarian, proportional or mixed); for lower and upper houses was coded: number of electoral segments; linked electoral segments; dependent formulae in mixed systems; subtypes of mixed electoral systems; district magnitude (number of members elected from each district); number of secondary and tertiary electoral districts; fused vote; size of the lower house; GDP growth (annual percent); GDP per capita; inflation, GDP Deflator (annual percent); Human development index; total population; total unemployment; constitutional federal structure; number of legislative chambers; electoral results data available; effective number of electoral and parliamentary partie

CSES Module 1-3 Harmonized Trend File

Für weitere Informationen zur Variablenliste siehe die Dokumentation (Codebook) des CSES Module 1-3 Harmonized Trend File. Informationen zum Inhalt können den Studiennummern ZA5179 CSES Module 1 Full Release, ZA5180 CSES Module 2 Full Release, und ZA5181 CSES Module 3 Full Release entnommen werden