Andrographolide downregulates pro-inflammatory cytokines and free radical productions to prevent dopaminergic neuro-degeneration induced by lipopolysaccharide

Oxidative stress and inflammation triggers the production of free radicals and toxic pro-inflammatory cytokines leading to neurodegeneration. Down-regulation of oxidative stress and inflammatory mediators offers defence against development and progression of the disease. Andrographolide is the most abundant diterpene lactone isolated from the leaves of Andrographis paniculata. Despite the increasing literature studies on the anti-inflammatory effect of andrographolide, there is still paucity regarding its neuroprotective role as can be ascertained from the search of literature. The present study investigated the potential therapeutic role of andrographolide as a neuroprotective agent via in vitro model of lipopolysaccharide (LPS)-induced brain injury using microglial (BV2) and dopaminergic (N27) cells. Pre-treatment of andrographolide at non-cytotoxic concentration range (0.25-2.0 µM) of BV2 cells followed by LPS dose-dependently suppressed nitric oxide production, pro-inflammatory cytokines (TNF-α, IL-6) as well as attenuating intracellular reactive oxygen species (ROS) and thiobarbituric acid reactive substance (TBARS) compared to cells without andrographolide pretreatment. Further, conditioned media (CM) of the pretreatment had diminished toxicity towards dopaminergic neurons as compared to CM without pretreatment. Keywords: Andrographolide; Proinflammatory cytokines; oxidative stress; microglial; dopaminergic neurodegeneration

Bayesian 2-Stage Space-Time Mixture Modeling with Spatial Misalignment of the Exposure in Small Area Health Data

We develop a new Bayesian two-stage space-time mixture model to investigate the effects of air pollution on asthma. The two-stage mixture model proposed allows for the identification of temporal latent structure as well as the estimation of the effects of covariates on health outcomes. In the paper, we also consider spatial misalignment of exposure and health data. A simulation study is conducted to assess the performance of the 2-stage mixture model. We apply our statistical framework to a county-level ambulatory care asthma data set in the US state of Georgia for the years 1999-2008

Ambulatory teaching: Do approaches to learning predict the site and preceptor characteristics valued by clerks and residents in the ambulatory setting?

BACKGROUND: In a study to determine the site and preceptor characteristics most valued by clerks and residents in the ambulatory setting we wished to confirm whether these would support effective learning. The deep approach to learning is thought to be more effective for learning than surface approaches. In this study we determined how the approaches to learning of clerks and residents predicted the valued site and preceptor characteristics in the ambulatory setting. METHODS: Postal survey of all medical residents and clerks in training in Ontario determining the site and preceptor characteristics most valued in the ambulatory setting. Participants also completed the Workplace Learning questionnaire that includes 3 approaches to learning scales and 3 workplace climate scales. Multiple regression analysis was used to predict the preferred site and preceptor characteristics as the dependent variables by the average scores of the approaches to learning and perception of workplace climate scales as the independent variables. RESULTS: There were 1642 respondents, yielding a 47.3% response rate. Factor analysis revealed 7 preceptor characteristics and 6 site characteristics valued in the ambulatory setting. The Deep approach to learning scale predicted all of the learners' preferred preceptor characteristics (β = 0.076 to β = 0.234, p < .001). Valuing preceptor Direction was more strongly associated with the Surface Rational approach (β = .252, p < .001) and with the Surface Disorganized approach to learning (β = .154, p < 001) than with the Deep approach. The Deep approach to learning scale predicted valued site characteristics of Office Management, Patient Logistics, Objectives and Preceptor Interaction (p < .001). The Surface Rational approach to learning predicted valuing Learning Resources and Clinic Set-up (β = .09, p = .001; β = .197, p < .001). The Surface Disorganized approach to learning weakly negatively predicted Patient Logistics (β = -.082, p = .003) and positively the Learning Resources (β = .088, p = .003). Climate factors were not strongly predictive for any studied characteristics. Role Modeling and Patient Logistics were predicted by Supportive Receptive climate (β = .135, p < .001, β = .118, p < .001). CONCLUSION: Most site and preceptor characteristics valued by clerks and residents were predicted by their Deep approach to learning scores. Some characteristics reflecting the need for good organization and clear direction are predicted by learners' scores on less effective approaches to learning

Impaired decisional impulsivity in pathological videogamers

Abstract Background Pathological gaming is an emerging and poorly understood problem. Impulsivity is commonly impaired in disorders of behavioural and substance addiction, hence we sought to systematically investigate the different subtypes of decisional and motor impulsivity in a well-defined pathological gaming cohort. Methods Fifty-two pathological gaming subjects and age-, gender- and IQ-matched healthy volunteers were tested on decisional impulsivity (Information Sampling Task testing reflection impulsivity and delay discounting questionnaire testing impulsive choice), and motor impulsivity (Stop Signal Task testing motor response inhibition, and the premature responding task). We used stringent diagnostic criteria highlighting functional impairment. Results In the Information Sampling Task, pathological gaming participants sampled less evidence prior to making a decision and scored fewer points compared with healthy volunteers. Gaming severity was also negatively correlated with evidence gathered and positively correlated with sampling error and points acquired. In the delay discounting task, pathological gamers made more impulsive choices, preferring smaller immediate over larger delayed rewards. Pathological gamers made more premature responses related to comorbid nicotine use. Greater number of hours played also correlated with a Motivational Index. Greater frequency of role playing games was associated with impaired motor response inhibition and strategy games with faster Go reaction time. Conclusions We show that pathological gaming is associated with impaired decisional impulsivity with negative consequences in task performance. Decisional impulsivity may be a potential target in therapeutic management

Increased ventral striatal volume in college-aged binge drinkers

BACKGROUND Binge drinking is a serious public health issue associated with cognitive, physiological, and anatomical differences from healthy individuals. No studies, however, have reported subcortical grey matter differences in this population. To address this, we compared the grey matter volumes of college-age binge drinkers and healthy controls, focusing on the ventral striatum, hippocampus and amygdala. METHOD T1-weighted images of 19 binge drinkers and 19 healthy volunteers were analyzed using voxel-based morphometry. Structural data were also covaried with Alcohol Use Disorders Identification Test (AUDIT) scores. Cluster-extent threshold and small volume corrections were both used to analyze imaging data. RESULTS Binge drinkers had significantly larger ventral striatal grey matter volumes compared to controls. There were no between group differences in hippocampal or amygdalar volume. Ventral striatal, amygdalar, and hippocampal volumes were also negatively related to AUDIT scores across groups. CONCLUSIONS Our findings stand in contrast to the lower ventral striatal volume previously observed in more severe forms of alcohol use disorders, suggesting that college-age binge drinkers may represent a distinct population from those groups. These findings may instead represent early sequelae, compensatory effects of repeated binge and withdrawal, or an endophenotypic risk factor

Calibration of the charge and energy loss per unit length of the MicroBooNE liquid argon time projection chamber using muons and protons

We describe a method used to calibrate the position- and time-dependent response of the MicroBooNE liquid argon time projection chamber anode wires to ionization particle energy loss. The method makes use of crossing cosmic-ray muons to partially correct anode wire signals for multiple effects as a function of time and position, including cross-connected TPC wires, space charge effects, electron attachment to impurities, diffusion, and recombination. The overall energy scale is then determined using fully-contained beam-induced muons originating and stopping in the active region of the detector. Using this method, we obtain an absolute energy scale uncertainty of 2% in data. We use stopping protons to further refine the relation between the measured charge and the energy loss for highly-ionizing particles. This data-driven detector calibration improves both the measurement of total deposited energy and particle identification based on energy loss per unit length as a function of residual range. As an example, the proton selection efficiency is increased by 2% after detector calibration

Reconstruction and measurement of (100) MeV energy electromagnetic activity from π0 arrow γγ decays in the MicroBooNE LArTPC

We present results on the reconstruction of electromagnetic (EM) activity from photons produced in charged current νμ interactions with final state π0s. We employ a fully-automated reconstruction chain capable of identifying EM showers of (100) MeV energy, relying on a combination of traditional reconstruction techniques together with novel machine-learning approaches. These studies demonstrate good energy resolution, and good agreement between data and simulation, relying on the reconstructed invariant π0 mass and other photon distributions for validation. The reconstruction techniques developed are applied to a selection of νμ + Ar → μ + π0 + X candidate events to demonstrate the potential for calorimetric separation of photons from electrons and reconstruction of π0 kinematics

Aggregated a-synuclein and complex I deficiency: exploration of their relationship in differentiated neurons

α-Synuclein becomes misfolded and aggregated upon damage by various factors, for example, by reactive oxygen species. These aggregated forms have been proposed to have differential toxicities and their interaction with mitochondria may cause dysfunction within this organelle that contributes to the pathogenesis of Parkinson’s disease (PD). In particular, the association of α-synuclein with mitochondria occurs through interaction with mitochondrial complex I and importantly defects of this protein have been linked to the pathogenesis of PD. Therefore, we investigated the relationship between aggregated α-synuclein and mitochondrial dysfunction, and the consequences of this interaction on cell survival. To do this, we studied the effects of α-synuclein on cybrid cell lines harbouring mutations in either mitochondrial complex I or IV. We found that aggregated α-synuclein inhibited mitochondrial complex I in control and complex IV-deficient cells. However, when aggregated α-synuclein was applied to complex I-deficient cells, there was no additional inhibition of mitochondrial function or increase in cell death. This would suggest that as complex I-deficient cells have already adapted to their mitochondrial defect, the subsequent toxic effects of α-synuclein are reduced