University of Antwerp

About: University of Antwerp is a education organization based out in Antwerp, Belgium. It is known for research contribution in the topics: Population & Context (language use). The organization has 16682 authors who have published 48837 publications receiving 1689748 citations. The organization is also known as: Universiteit Antwerpen & UAntwerp.

Drug-induced stimulation and suppression of action monitoring in healthy volunteers

Abstract: Action monitoring has been studied extensively by means of measuring the error-related negativity (ERN). The ERN is an event-related potential (ERP) elicited immediately after an erroneous response and is thought to originate in the anterior cingulate cortex (ACC). Although the ACC has a central role in the brain, only a few studies have been performed to investigate directly the effects of drugs on action monitoring. A recent theory argues that the mesencephalic dopamine system carries an error signal to the ACC, where it generates the ERN. ERPs and behavioral measurements were obtained from 12 healthy volunteers performing an Eriksen Flankers task. On each of the 4 test days, the stimulant d-amphetamine, the sedative lorazepam, the antidepressant mirtazapine, or a placebo was orally administered in a double-blind, four-way crossover design. The indirect dopamine agonist amphetamine led to a strong enlargement of ERN amplitudes without affecting reaction times. Lorazepam and mirtazapine both showed slowing of responses, but only lorazepam led to reduced ERN amplitudes. Administration of amphetamine leads to stimulated action monitoring, reflected in increased ERN amplitudes. This result provides evidence for dopaminergic involvement in action monitoring and is in line with differences in ERN amplitude found in neuropsychiatric disorders also suggesting dopaminergic involvement. The different effects for lorazepam and mirtazapine are probably caused by the neurobiological characteristics of these two types of sedation. Action monitoring is suppressed after administration of lorazepam, because the GABAergic pathways directly inhibit ACC functioning, whereas the histaminergic pathways of mirtazapine do not innervate the ACC directly.

Prevalence and Evolutionary Origins of the del(GJB6-D13S1830) Mutation in the DFNB1 Locus in Hearing-Impaired Subjects: a Multicenter Study

Abstract: Mutations in GJB2, the gene encoding connexin-26 at the DFNB1 locus on 13q12, are found in as many as 50% of subjects with autosomal recessive, nonsyndromic prelingual hearing impairment. However, genetic diagnosis is complicated by the fact that 10%–50% of affected subjects with GJB2 mutations carry only one mutant allele. Recently, a deletion truncating the GJB6 gene (encoding connexin-30), near GJB2 on 13q12, was shown to be the accompanying mutation in ∼50% of these deaf GJB2 heterozygotes in a cohort of Spanish patients, thus becoming second only to 35delG at GJB2 as the most frequent mutation causing prelingual hearing impairment in Spain. Here, we present data from a multicenter study in nine countries that shows that the deletion is present in most of the screened populations, with higher frequencies in France, Spain, and Israel, where the percentages of unexplained GJB2 heterozygotes fell to 16.0%–20.9% after screening for the del(GJB6-D13S1830) mutation. Our results also suggest that additional mutations remain to be identified, either in DFNB1 or in other unlinked genes involved in epistatic interactions with GJB2. Analysis of haplotypes associated with the deletion revealed a founder effect in Ashkenazi Jews and also suggested a common founder for countries in Western Europe. These results have important implications for the diagnosis and counseling of families with DFNB1 deafness.

Delayed autumn phenology in the Northern Hemisphere is related to change in both climate and spring phenology.

Abstract: The timing of the end of the vegetation growing season (EOS) plays a key role in terrestrial ecosystem carbon and nutrient cycles. Autumn phenology is, however, still poorly understood, and previous studies generally focused on few species or were very limited in scale. In this study, we applied four methods to extract EOS dates from NDVI records between 1982 and 2011 for the Northern Hemisphere, and determined the temporal correlations between EOS and environmental factors (i.e., temperature, precipitation and insolation), as well as the correlation between spring and autumn phenology, using partial correlation analyses. Overall, we observed a trend toward later EOS in ~70% of the pixels in Northern Hemisphere, with a mean rate of 0.18 ± 0.38 days yr-1 . Warming preseason temperature was positively associated with the rate of EOS in most of our study area, except for arid/semi-arid regions, where the precipitation sum played a dominant positive role. Interestingly, increased preseason insolation sum might also lead to a later date of EOS. In addition to the climatic effects on EOS, we found an influence of spring vegetation green-up dates on EOS, albeit biome dependent. Our study, therefore, suggests that both environmental factors and spring phenology should be included in the modeling of EOS to improve the predictions of autumn phenology as well as our understanding of the global carbon and nutrient balances.

Comparative Physico-mechanical Characterization of New Hybrid Restorative Materials with Conventional Glass-ionomer and Resin Composite Restorative Materials

Abstract: The recently developed hybrid restorative materials contain the essential components of conventional glass ionomers and light-cured resins. The objective of this study was to determine several physical and mechanical properties of eight such materials in comparison with two conventional glass ionomers, one micro-filled, and one ultrafine compact-filled resin composite. The two resin composites and two of the three polyacid-modified resin composites could be polished to a higher gloss than the conventional as well as the resin-modified glass ionomers. After abrasion, surface roughness increased for all materials, but not at the same extent, being the least for the conventional resin composites and one polyacid-modified resin composite, Dyract. In contrast to the later resin composites, of which the surface roughness is principally determined by the presence of protruding filler particles above the resin matrix, roughness of conventional and resin-modified glass ionomers results from both protruding filler particles and intruding porosities. The mean particle size of the hybrid restorative materials fell between the smaller mean particle size of the resin composites and the larger one of the conventional glass ionomers. The micro-hardness and Young's modulus values varied substantially among all eight hybrid restorative materials. For all the resin-modified glass-ionomer restorative materials, the Young's modulus reached a maximum value one month after mixing and remained relatively stable thereafter. The Young's modulus of the conventional and the polyacid-modified resin composites decreased slightly after one month. The conventional glass-ionomer materials undoubtedly set the slowest, since their Young's modulus took six months to reach its maximum. The flexural fatigue limit of the hybrid restorative materials is comparable with that of the micro-filled composite. From this investigation, it can be concluded that the physico-mechanical properties vary widely among the eight hybrid restorative materials, indicating that these materials probably have yet to achieve their optimum properties. Their mechanical strength is inadequate for use in stress-bearing areas, and their appearance keeps them from use where esthetics is a primary concern.

Maximum Likelihood Estimation of Signal Amplitude and Noise Variance From MR Data

Abstract: In MRI, the raw data, which are acquired in spatial frequency space, are intrinsically complex valued and corrupted by Gaussian-distributed noise. After applying an inverse Fourier transform, the data remain complex valued and Gaussian distributed. If the signal amplitude is to be estimated, one has two options. It can be estimated directly from the complex valued data set, or one can first perform a magnitude operation on this data set, which changes the distribution of the data from Gaussian to Rician, and estimate the signal amplitude from the obtained magnitude image. Similarly, the noise variance can be estimated from both the complex and magnitude data sets. This article addresses the question whether it is better to use complex valued data or magnitude data for the estimation of these parameters using the maximum likelihood method. As a performance criterion, the mean-squared error (MSE) is used.