Auditory cortical tuning to statistical regularities in phonology

Objective: Ample behavioral evidence suggests that distributional properties of the language environment influence the processing of speech. Yet, how these characteristics are reflected in neural processes remains largely unknown. The present ERP study investigates neurophysiological correlates of phonotactic probability: the distributional frequency of phoneme combinations. Methods: We employed an ERP measure indicative of experience-dependent auditory memory traces, the mismatch negativity (MMN). We presented pairs of non-words that differed by the degree of phonotactic probability in a codified passive oddball design that minimizes the contribution of acoustic processes. Results: In Experiment 1 the non-word with high phonotactic probability (notsel) elicited a significantly enhanced MMN as compared to the non-word with low phonotactic probability (notkel). In Experiment 2 this finding was replicated with a non-word pair with a smaller acoustic difference (notsel–notfel). An MMN enhancement was not observed in a third acoustic control experiment with stimuli having comparable phonotactic probability (so–fo). Conclusions: Our data suggest that auditory cortical responses to phoneme clusters are modulated by statistical regularities of phoneme combinations. Significance: This study indicates that the language environment is relevant in shaping the neural processing of speech. Furthermore, it provides a potentially useful design for investigating implicit phonological processing in children with anomalous language functions like dyslexia

The testosterone metabolism of <i>Neomysis integer</i>: the quest continues… (poster)

Both vertebrate and invertebrate species use enzymatic biotransformations for detoxication and elimination of xenobiotics. Testosterone has been used as a substrate to study the multiplicity of these enzymes. Since many of these enzymes are under hormone control, disruption of the hormone function can lead to potential effects on enzyme function and subsequently steroid homeostasis. The testosterone metabolism has therefore been proposed as a biomarker of exposure to endocrine disruptive compounds.In a previous study, the estuarine crustacean Neomysis integer (Crustacea, Mysidacea) was exposed to both testosterone and [14C]-testosterone. Identification and quantification of testosterone metabolites and endogenous steroids was done using TLC and LC-MSn (Verslycke et al., Gen. Comp. Endocrinol., accepted). The use of liquid chromatography coupled with multiple mass spectrometry allows a unique quantification of both endogenously produced steroids and in vivo produced metabolites in single mysid. Recent research has focused on the potential use of these biotransformations as a predictive biomarker for exposure to known endocrine disruptors. In this context, quantitative changes in the biotransformation profile of testosterone were evaluated after exposure to tributyltin (TBT), a compound used in antifouling paint, which has been suspected to interfere with steroid metabolism. The resulting protocol allows a quantitative and qualitative evaluation of the effect of TBT on the testosterone metabolism of N. integer. The results of these exposures will be presented and a possible mechanism of disruption through interaction with the P450 enzyme system is proposed.Future research on the steroid metabolism of N. integer could result in the development of predictive biomarkers for detection of endocrine disruption in estuarine environments

Polynomial scaling approximations and dynamic correlation corrections to doubly occupied configuration interaction wave functions

A class of polynomial scaling methods that approximate Doubly Occupied Configuration Interaction (DOCI) wave functions and improve the description of dynamic correlation is introduced. The accuracy of the resulting wave functions is analysed by comparing energies and studying the overlap between the newly developed methods and full configuration interaction wave functions, showing that a low energy does not necessarily entail a good approximation of the exact wave function. Due to the dependence of DOCI wave functions on the single-particle basis chosen, several orbital optimisation algorithms are introduced. An energy-based algorithm using the simulated annealing method is used as a benchmark. As a computationally more affordable alternative, a seniority number minimising algorithm is developed and compared to the energy based one revealing that the seniority minimising orbital set performs well. Given a well-chosen orbital basis, it is shown that the newly developed DOCI based wave functions are especially suitable for the computationally efficient description of static correlation and to lesser extent dynamic correlation.Fil: Van Raemdonck, Mario. Ghent University; BélgicaFil: Alcoba, Diego Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Poelmans, Ward. Ghent University; BélgicaFil: De Baerdemacker, Stijn. Ghent University; BélgicaFil: Torre, Alicia. Universidad del País Vasco; EspañaFil: Lain, Luis. Universidad del País Vasco; EspañaFil: Massaccesi, Gustavo Ernesto. Universidad de Barcelona. Facultad de Física. Departamento de Física Fomental; EspañaFil: Van Neck, D.. Ghent University; BélgicaFil: Bultinck, P.. Ghent University; Bélgic

Insulinopathies of the brain? Genetic overlap between somatic insulin-related and neuropsychiatric disorders

The prevalence of somatic insulinopathies, like metabolic syndrome (MetS), obesity, and type 2 diabetes mellitus (T2DM), is higher in Alzheimer’s disease (AD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD). Dysregulation of insulin signalling has been implicated in these neuropsychiatric disorders, and shared genetic factors might partly underlie this observed multimorbidity. We investigated the genetic overlap between AD, ASD, and OCD with MetS, obesity, and T2DM by estimating pairwise global genetic correlations using the summary statistics of the largest available genome-wide association studies for these phenotypes. Having tested these hypotheses, other potential brain “insulinopathies” were also explored by estimating the genetic relationship of six additional neuropsychiatric disorders with nine insulin-related diseases/traits. Stratified covariance analyses were then performed to investigate the contribution of insulin-related gene sets. Significant negative genetic correlations were found between OCD and MetS (rg = −0.315, p = 3.9 × 10−8), OCD and obesity (rg = −0.379, p = 3.4 × 10−5), and OCD and T2DM (rg = −0.172, p = 3 × 10−4). Significant genetic correlations with insulin-related phenotypes were also found for anorexia nervosa (AN), attention-deficit/hyperactivity disorder (ADHD), major depressive disorder, and schizophrenia (p &lt; 6.17 × 10−4). Stratified analyses showed negative genetic covariances between AD, ASD, OCD, ADHD, AN, bipolar disorder, schizophrenia and somatic insulinopathies through gene sets related to insulin signalling and insulin receptor recycling, and positive genetic covariances between AN and T2DM, as well as ADHD and MetS through gene sets related to insulin processing/secretion (p &lt; 2.06 × 10−4). Overall, our findings suggest the existence of two clusters of neuropsychiatric disorders, in which the genetics of insulin-related diseases/traits may exert divergent pleiotropic effects. These results represent a starting point for a new research line on “insulinopathies” of the brain

Business process variant analysis based on mutual fingerprints of event logs

Comparing business process variants using event logs is a common use case in process mining. Existing techniques for process variant analysis detect statistically-significant differences between variants at the level of individual entities (such as process activities) and their relationships (e.g. directly-follows relations between activities). This may lead to a proliferation of differences due to the low level of granularity in which such differences are captured. This paper presents a novel approach to detect statistically-significant differences between variants at the level of entire process traces (i.e. sequences of directly-follows relations). The cornerstone of this approach is a technique to learn a directly-follows graph called mutual fingerprint from the event logs of the two variants. A mutual fingerprint is a lossless encoding of a set of traces and their duration using discrete wavelet transformation. This structure facilitates the understanding of statistical differences along the control-flow and performance dimensions. The approach has been evaluated using real-life event logs against two baselines. The results show that at a trace level, the baselines cannot always reveal the differences discovered by our approach, or can detect spurious differences.This research is partly funded by the Australian Research Council (DP180102839) and Spanish funds MINECO and FEDER (TIN2017-86727-C2-1-R).Peer ReviewedPostprint (author's final draft

Integrated molecular landscape of Parkinson’s disease

Parkinson’s disease is caused by a complex interplay of genetic and environmental factors. Although a number of independent molecular pathways and processes have been associated with familial Parkinson’s disease, a common mechanism underlying especially sporadic Parkinson’s disease is still largely unknown. In order to gain further insight into the etiology of Parkinson’s disease, we here conducted genetic network and literature analyses to integrate the top-ranked findings from thirteen published genome-wide association studies of Parkinson’s disease (involving 13.094 cases and 47.148 controls) and other genes implicated in (familial) Parkinson’s disease, into a molecular interaction landscape. The molecular Parkinson’s disease landscape harbors four main biological processes—oxidative stress response, endosomal-lysosomal functioning, endoplasmic reticulum stress response, and immune response activation—that interact with each other and regulate dopaminergic neuron function and death, the pathological hallmark of Parkinson’s disease. Interestingly, lipids and lipoproteins are functionally involved in and influenced by all these processes, and affect dopaminergic neuron-specific signaling cascades. Furthermore, we validate the Parkinson’s disease -lipid relationship by genome-wide association studies data-based polygenic risk score analyses that indicate a shared genetic risk between lipid/lipoprotein traits and Parkinson’s disease. Taken together, our findings provide novel insights into the molecular pathways underlying the etiology of (sporadic) Parkinson’s disease and highlight a key role for lipids and lipoproteins in Parkinson’s disease pathogenesis, providing important clues for the development of disease-modifying treatments of Parkinson’s disease

Testosterone metabolism in Neomysis integer following exposure to benzo(a)pyrene

Author Posting. © Elsevier B.V., 2006. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Comparative Biochemistry and Physiology Part B: Biochemistry and Molecular Biology 144 (2006): 405-412, doi:10.1016/j.cbpb.2006.04.001.Cytochromes P450 (CYPs) are important enzymes involved in the regulation of hormone synthesis and in the detoxification and/or activation of xenobiotics. CYPs are found in virtually all organisms, from archae, and eubacteria to eukaryota. A number of endocrine disruptors are suspected of exerting their effects through disruption of normal CYP function. Consequently, alterations in steroid hormone metabolism through changes in CYP could provide an important tool to evaluate potential effects of endocrine disruptors. The aim of this study was to investigate the potential effects of the known CYP modulator, benzo(a)pyrene (B(a)P), on the testosterone metabolism in the invertebrate Neomysis integer (Crustacea; Mysidacea). N. integer were exposed for 96h to 0.43, 2.39, 28.83, 339.00 and 1682.86μg B(a)P L-1 and a solventcontrol, and subsequently their ability to metabolize testosterone was assessed. Identification and quantification of the produced phase I and phase II testosterone metabolites was performed using liquid chromatography coupled with multiple mass spectrometry (LC-MS2). Significant changes were observed in the overall ability of N. integer to metabolize testosterone when exposed to 2.39, 28.83, 339.00 and 1682.86μg B(a)P L-1 as compared to the control animals.This research was supported by a research grant of the Ghent University Research Fund (BOF, 011.072.02). Dr. Tim Verslycke was supported by a Postdoctoral Fellowship of the Belgian American Educational Foundation

NK/T cell ratios associate with interleukin-2 receptor alpha chain expression and shedding in multiple sclerosis

NK/T-cell ratios predict disease activity in relapsing remitting multiple sclerosis (RRMS). We investigated in 50 RRMS patients whether interleukin-2 receptor alpha-chain (IL-2Rα) expression and shedding associates with NK/T-cell balance, as suggested by daclizumab-trials in RRMS. A subsample (N = 31) was genotyped for IL2RA-associated MS risk SNPs. CD56bright NK-cell/IL-17A+CD4+ T-cell ratios correlated negatively with plasma and PBMC-culture supernatant sIL-2Rα-levels [R = -0.209; p = 0.038 and R = -0.254; p = 0.012, resp.], and with CD4+ T-cell CD25 MFI [R = -0.341; p = 0.001]. Carriers of the rs3118470 risk-allele showed higher sIL-2Rα-levels (P = 0.031) and a lower

Blurred lines: work, eldercare and HRM

peer-reviewedThe full text of this article will not be available in ULIR until the embargo expires on the 27/06/2020Increased levels of female labour market participation have impacted on the ability of families to provide care for elderly relatives in many industrialised societies. While work–family balance has received significant academic attention, less attention has focused specifically on individuals with eldercare responsibility, a cohort which accounts for a growing segment of the labour market internationally. Taking a qualitative research approach this paper uses work/family border theory to the constraints and facilitators to reconciling care and employment for employees working full-time in Ireland. The findings highlight the significant impact that eldercare provision has on employees with regard to day-to-day work commitments. We find that while general work–life balance policies exist within organisations, that the design and functionality of such policies are of limited value to elder caregivers. Furthermore, this paper highlights how the lack of formal HR policies around eldercare within organisations results in a reliance on supervisory discretion. We make some recommendations for organisational level strategies to address the needs of a growing number of caregivers.peer-reviewe

Does Reviewing Lead to Better Learning and Decision Making? Answers from a Randomized Stock Market Experiment

status: publishe