354 research outputs found

    Task Residual Functional Connectivity in Language and Attention Networks

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    The present study compared network specificity between task-residual and resting state data types. Task-residual data capitalizes on the remaining variance after the mean task-related signal is removed from the time series. This study also examined how inter- and intrahemispheric connectivity (bilateral homologous regions and regions contained within the same hemisphere, respectively) within the language and attention networks change as a result of age. Task-residual functional connectivity evidenced stronger laterality of the language and attention connections and thus greater network specificity than resting state functional connectivity of the same connections. Using task-residual data may be optimal for characterizing the synchronized fluctuations between regions of discrete networks. Furthermore, alterations in intrahemispheric functional connectivity can be observed as early as middle age within the domain-general attention domain

    Creating Opportunities in Mobility: An Analysis of Trikes and Mobile Businesses Currently Available in Vietnam and the Philippines

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    Whirlwind Wheelchair International is dedicated to improving the lives of people with disabilities in the developing world, while also promoting sustainable local economic development in the process, with a good wheelchair. A “good wheelchair” must be safe, durable, locally repairable, and highly useable for the rider, which means it must fit the local terrain and environment. WWI aims for every person in the world who needs a high quality wheelchair to obtain one, leading to maximum personal independence and integration into society. Their RoughRider wheelchair is used by 25,000 riders traveling over terrains that only the best of wheelchairs can cross, from muddy village paths to rough, pot-holed urban streets

    Dissection du rôle fondamental de l'hyperglycémie sur la morphogenèse rénale

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    Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

    Angiotensin II Type II Receptor Deficiency Accelerates the Development of Nephropathy in Type I Diabetes via Oxidative Stress and ACE2

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    Since the functional role(s) of angiotensin II (Ang II) type II receptor (AT2R) in type I diabetes is unknown, we hypothesized that AT2R is involved in decreasing the effects of type I diabetes on the kidneys. We induced diabetes with low-dose streptozotocin (STZ) in both AT2R knockout (AT2RKO) and wild-type (WT) male mice aged 12 weeks and followed them for 4 weeks. Three subgroups nondiabetic, diabetic, and insulin-treated diabetic (Rx insulin implant) were studied. Systolic blood pressure (SBP), physiological parameters, glomerular filtration rate (GFR), renal morphology, gene expression, and apoptosis were assessed. After 4 weeks of diabetes, compared to WT controls, AT2RKO mice clearly developed features of early diabetic nephropathy (DN), such as renal hypertrophy, tubular apoptosis, and progressive extracellular matrix (ECM) protein accumulation as well as increased GFR. AT2RKO mice presented hypertension unaffected by diabetes. Renal oxidative stress (measured as heme oxygenase 1 (HO-1) gene expression and reactive oxygen species (ROS) generation) and intrarenal renin angiotensin system components, such as angiotensinogen (Agt), AT1R, and angiotensin-converting enzyme (ACE) gene expression, were augmented whereas angiotensin-converting enzyme2 (ACE2) gene expression was decreased in renal proximal tubules (RPTs) of AT2RKO mice. The renal changes noted above were significantly enhanced in diabetic AT2RKO mice but partially attenuated in insulin-treated diabetic WT and AT2RKO mice. In conclusion, AT2R deficiency accelerates the development of DN, which appears to be mediated, at least in part, via heightened oxidative stress and ACE/ACE2 ratio in RPTs

    Corticostriatal and dopaminergic response to beer flavor with both fMRI and [11C]raclopride Positron Emission Tomography

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    Background Cue-evoked drug seeking behavior likely depends on interactions between frontal activity and ventral striatal (VST) dopamine transmission. Using [11C]raclopride (RAC) positron emission tomography (PET), we previously demonstrated that beer flavor (absent intoxication) elicited VST dopamine (DA) release in beer drinkers, inferred by RAC displacement. Here, a subset of subjects from this previous RAC-PET study underwent a similar paradigm during functional magnetic resonance imaging (fMRI) to test how orbitofrontal cortex (OFC) and VST BOLD responses to beer flavor are related to VST DA release and motivation to drink. Methods Male beer drinkers (n=28, age=24±2, drinks/week=16±10) from our previous PET study participated in a similar fMRI paradigm wherein subjects tasted their most frequently consumed brand of beer and Gatorade® (appetitive control). We tested for correlations between blood oxygenation level dependent (BOLD) activation in fMRI and VST DA responses in PET, and drinking-related variables. Results Compared to Gatorade, beer flavor increased wanting and desire to drink, and induced BOLD responses in bilateral OFC and right VST. Wanting and desire to drink correlated with both right VST and medial OFC BOLD activation to beer flavor. Like the BOLD findings, beer flavor (relative to Gatorade) again induced right VST DA release in this fMRI subject subset, but there was no correlation between DA release and the magnitude of BOLD responses in frontal regions of interest. Conclusions Both imaging modalities showed a right lateralized VST response (BOLD and DA release) to a drug-paired conditioned stimulus, whereas fMRI BOLD responses in the VST and medial OFC also reflected wanting and desire to drink. The data suggest the possibility that responses to drug-paired cues may be rightward biased in the VST (at least in right-handed males), and that VST and OFC responses in this gustatory paradigm reflect stimulus wanting

    Evaluating decontamination and prevention techniques by establishing standardized broad-range microbial testing platforms

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    To find efficient decontamination techniques and preventive measures that create solutions for the future of human travel via public transportation, we established standardized experimental testing platforms that enable us to test the effectiveness of countermeasures against microbial contaminations. Additionally, we characterise the antimicrobial effects of, for example, active copper and copper alloy surfaces, which were topographically modified via Ultrashort Pulsed Direct Laser Interference Patterning (USP-DLIP). The experimental set-up includes a standardized bacterial bioaerosol including abundant microbes found in indoor air as well as an array of multi-drug-resistant bacteria (enterococci) and microbiological sterilization indicators like fungal spores (following the DIN EN 16868 standards). In our research, we e.g., aerosolize authentic bacterial bioaerosols (active or inactive form) and treat them with a given decontamination technique. In laboratory settings, as well as train and airplane cabin mock-ups, and real-life scenarios, we combine flow dynamic, material, and microbiome research

    Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)

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    Electronic medical record (EMR) offers promises for novel analytics. However, manual feature engineering from EMR is labor intensive because EMR is complex – it contains temporal, mixed-type and multimodal data packed in irregular episodes. We present a computational framework to harness EMR with minimal human supervision via restricted Boltzmann machine (RBM). The framework derives a new representation of medical objects by embedding them in a low-dimensional vector space. This new representation facilitates algebraic and statistical manipulations such as projection onto 2D plane (thereby offering intuitive visualization), object grouping (hence enabling automated phenotyping), and risk stratification. To enhance model interpretability, we introduced two constraints into model parameters: (a) nonnegative coefficients, and (b) structural smoothness. These result in a novel model called eNRBM (EMR-driven nonnegative RBM). We demonstrate the capability of the eNRBM on a cohort of 7578 mental health patients under suicide risk assessment. The derived representation not only shows clinically meaningful feature grouping but also facilitates short-term risk stratification. The F-scores, 0.21 for moderate-risk and 0.36 for high-risk, are significantly higher than those obtained by clinicians and competitive with the results obtained by support vector machines
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