The Histone Deacetylase Inhibitor Nicotinamide Exacerbates Neurodegeneration in the Lactacystin Rat Model of Parkinson's Disease

Histone hypoacetylation is associated with dopaminergic neurodegeneration in Parkinson's disease (PD), due to an imbalance in the activities of the enzymes responsible for histone (de)acetylation. Correction of this imbalance, with histone deacetylase (HDAC) inhibiting agents, could be neuroprotective. We therefore hypothesise that nicotinamide, being a selective inhibitor of HDAC class III as well as having modulatory effects on mitochondrial energy metabolism, would be neuroprotective in the lactacystin rat model of PD, which recapitulates the formation of neurotoxic accumulation of altered proteins within the substantia nigra to cause progressive dopaminergic cell death. Rats received nicotinamide for 28 days, starting 7 days after unilateral injection of the irreversible proteasome inhibitor, lactacystin, into the substantia nigra. Longitudinal motor behavioural testing and structural MRI were used to track changes in this model of PD, and assessment of nigrostriatal integrity, histone acetylation, and brain gene expression changes post-mortem used to quantify nicotinamide induced neuroprotection. Counterintuitively, nicotinamide dose-dependently exacerbated neurodegeneration of dopaminergic neurons, behavioural deficits, and structural brain changes in the lactacystin-lesioned rat. Nicotinamide treatment induced histone hyperacetylation and overexpression of numerous neurotrophic and anti-apoptotic factors in the brain, yet failed to result in neuroprotection, rather exacerbated dopaminergic pathology. These findings highlight the importance of inhibitor specificity within HDAC isoforms for therapeutic efficacy in PD, demonstrating the contrasting effects of HDAC class III inhibition upon cell survival in this animal model of the disease. This article is protected by copyright. All rights reserved

Bayesian Best-Arm Identification for Selecting Influenza Mitigation Strategies

Pandemic influenza has the epidemic potential to kill millions of people. While various preventive measures exist (i.a., vaccination and school closures), deciding on strategies that lead to their most effective and efficient use remains challenging. To this end, individual-based epidemiological models are essential to assist decision makers in determining the best strategy to curb epidemic spread. However, individual-based models are computationally intensive and it is therefore pivotal to identify the optimal strategy using a minimal amount of model evaluations. Additionally, as epidemiological modeling experiments need to be planned, a computational budget needs to be specified a priori. Consequently, we present a new sampling technique to optimize the evaluation of preventive strategies using fixed budget best-arm identification algorithms. We use epidemiological modeling theory to derive knowledge about the reward distribution which we exploit using Bayesian best-arm identification algorithms (i.e., Top-two Thompson sampling and BayesGap). We evaluate these algorithms in a realistic experimental setting and demonstrate that it is possible to identify the optimal strategy using only a limited number of model evaluations, i.e., 2-to-3 times faster compared to the uniform sampling method, the predominant technique used for epidemiological decision making in the literature. Finally, we contribute and evaluate a statistic for Top-two Thompson sampling to inform the decision makers about the confidence of an arm recommendation

Fully-automated μMRI morphometric phenotyping of the Tc1 mouse model of Down Syndrome

We describe a fully automated pipeline for the morphometric phenotyping of mouse brains from μMRI data, and show its application to the Tc1 mouse model of Down syndrome, to identify new morphological phenotypes in the brain of this first transchromosomic animal carrying human chromosome 21. We incorporate an accessible approach for simultaneously scanning multiple ex vivo brains, requiring only a 3D-printed brain holder, and novel image processing steps for their separation and orientation. We employ clinically established multi-atlas techniques-superior to single-atlas methods-together with publicly-available atlas databases for automatic skull-stripping and tissue segmentation, providing high-quality, subject-specific tissue maps. We follow these steps with group-wise registration, structural parcellation and both Voxel- and Tensor-Based Morphometry-advantageous for their ability to highlight morphological differences without the laborious delineation of regions of interest. We show the application of freely available open-source software developed for clinical MRI analysis to mouse brain data: NiftySeg for segmentation and NiftyReg for registration, and discuss atlases and parameters suitable for the preclinical paradigm. We used this pipeline to compare 29 Tc1 brains with 26 wild-type littermate controls, imaged ex vivo at 9.4T. We show an unexpected increase in Tc1 total intracranial volume and, controlling for this, local volume and grey matter density reductions in the Tc1 brain compared to the wild-types, most prominently in the cerebellum, in agreement with human DS and previous histological findings

A nonsmooth frictional contact formulation for multibody system dynamics

We present a new node-to-face frictional contact element for the simulation of the nonsmooth dynamics of systems composed of rigid and flexible bodies connected by kinematic joints. The equations of motion are integrated using a nonsmooth generalized-α time integration scheme and the frictional contact problem is formulated using a mixed approach, based on an augmented Lagrangian technique and a Coulomb friction law. The numerical results are independent of any user-defined penalty parameter for the normal or tangential component of the forces and, the bilateral and the unilateral constraints are exactly fulfilled both at position and velocity levels. Finally, the robustness and the performance of the proposed algorithm are demonstrated by solving several numerical examples of nonsmooth mechanical systems involving frictional contact.Fil: Galvez, Javier. Université de Liège; BélgicaFil: Cavalieri, Federico José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; ArgentinaFil: Cosimo, Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; Argentina. Université de Liège; BélgicaFil: Brüls, Olivier. Université de Liège; BélgicaFil: Cardona, Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; Argentin

Work-related psychological health among clergywomen in Australia

Drawing on the classic model of balanced affect, the Francis Burnout Inventory conceptualises good work-related psychological health among clergy in terms of negative affect being balanced by positive affect. This paper sets out to explore the relationship between work-related psychological health and psychological type (as assessed by the Francis Psychological-Type Scales) among a sample of 212 Australian clergywomen who completed the National Church Life Survey Form L in 2006. The data supported the internal consistency reliability of the Francis Burnout Inventory and Francis Psychological-Type Scales and found that work-related psychological health was positively related to extraversion and sensing

Daily life stress and the cortisol awakening response : testing the anticipation hypothesis

Acknowledgments We thank Paul Stewart for his contribution to data collection and Dr Matthew Jones for programming the handheld computers. Author Contributions Conceived and designed the experiments: WS DJP. Performed the experiments: DJP. Analyzed the data: WS. Wrote the paper: WS DJP.Peer reviewedPublisher PD

Substantially thinner internal granular layer and reduced molecular layer surface in the cerebellum of the Tc1 mouse model of Down Syndrome - a comprehensive morphometric analysis with active staining contrast-enhanced MRI

Down Syndrome is a chromosomal disorder that affects the development of cerebellar cortical lobules. Impaired neurogenesis in the cerebellum varies among different types of neuronal cells and neuronal layers. In this study, we developed an imaging analysis framework that utilizes gadolinium-enhanced ex vivo mouse brain MRI. We extracted the middle Purkinje layer of the mouse cerebellar cortex, enabling the estimation of the volume, thickness, and surface area of the entire cerebellar cortex, the internal granular layer, and the molecular layer in the Tc1 mouse model of Down Syndrome. The morphometric analysis of our method revealed that a larger proportion of the cerebellar thinning in this model of Down Syndrome resided in the inner granule cell layer, while a larger proportion of the surface area shrinkage was in the molecular layer

Relationship between craving and personality in treatment-seeking women with substance-related disorders

BACKGROUND: Individual differences may impact susceptibility to addiction. The impact of personality features on drug craving, however, has not been studied, particularly in women. METHODS: Ninety-five treatment-seeking women with substance dependence, abstinent for at least 5 and no more than 21 days, were investigated regarding the correlation between personality factors and craving. Personality was assessed using the Temperament and Character Inventory (TCI), the NEO Personality Inventory Revised (NEO-PI-R), and the Barratt Impulsiveness Scale version 11 (BIS-11). Cravings were assessed through the Pennsylvania Craving Scale (PCS), and the Craving Questionnaire (CQ). Anxiety and depressive symptomatology were also recorded. RESULTS: Craving scores were positively correlated with depression and negatively correlated with number of days abstinent from substance use. Also, craving scores were positively associated with the novelty-seeking factor from the TCI and the total score on the BIS-11, and negatively associated with the conscientiousness and agreeableness facets of the NEO-PI-R. CONCLUSION: Findings suggest that personality features, particularly impulsiveness, can be important predictors of craving in women, which has important implications for treatment planning

Nanoethics, science communication, and a fourth model for public engagement

This paper develops a fourth model of public engagement with science, grounded in the principle of nurturing scientific agency through online participatory bioethics. It argues that social media is an effective device through which to enable such engagement, as it has the capacity to empower users and transforms audiences into co-producers of knowledge, rather than consumers of content, the value of which is recognised within the citizen science movement. Social media also fosters greater engagement with the political and legal implications of science, thus promoting the value of scientific citizenship through the acquisition of science capital. This argument is explored by considering the case of nanoscience and nanotechnology, as an exemplar for how emerging technologies may be handled by the scientific community and science policy makers, and as a technology that has defined a second era of science communication

Role of the mesoamygdaloid dopamine projection in emotional learning

Amygdala dopamine is crucially involved in the acquisition of Pavlovian associations, as measured via conditioned approach to the location of the unconditioned stimulus (US). However, learning begins before skeletomotor output, so this study assessed whether amygdala dopamine is also involved in earlier 'emotional' learning. A variant of the conditioned reinforcement (CR) procedure was validated where training was restricted to curtail the development of selective conditioned approach to the US location, and effects of amygdala dopamine manipulations before training or later CR testing assessed. Experiment 1a presented a light paired (CS+ group) or unpaired (CS- group) with a US. There were 1, 2 or 10 sessions, 4 trials per session. Then, the US was removed, and two novel levers presented. One lever (CR+) presented the light, and lever pressing was recorded. Experiment 1b also included a tone stimulus. Experiment 2 applied intra-amygdala R(+) 7-OH-DPAT (10 nmol/1.0 A mu l/side) before two training sessions (Experiment 2a) or a CR session (Experiment 2b). For Experiments 1a and 1b, the CS+ group preferred the CR+ lever across all sessions. Conditioned alcove approach during 1 or 2 training sessions or associated CR tests was low and nonspecific. In Experiment 2a, R(+) 7-OH-DPAT before training greatly diminished lever pressing during a subsequent CR test, preferentially on the CR+ lever. For Experiment 2b, R(+) 7-OH-DPAT infusions before the CR test also reduced lever pressing. Manipulations of amygdala dopamine impact the earliest stage of learning in which emotional reactions may be most prevalent