1,238 research outputs found

    Unexpected cell type-dependent effects of autophagy on polyglutamine aggregation revealed by natural genetic variation in C. elegans.

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    BACKGROUND: Monogenic protein aggregation diseases, in addition to cell selectivity, exhibit clinical variation in the age of onset and progression, driven in part by inter-individual genetic variation. While natural genetic variants may pinpoint plastic networks amenable to intervention, the mechanisms by which they impact individual susceptibility to proteotoxicity are still largely unknown. RESULTS: We have previously shown that natural variation modifies polyglutamine (polyQ) aggregation phenotypes in C. elegans muscle cells. Here, we find that a genomic locus from C. elegans wild isolate DR1350 causes two genetically separable aggregation phenotypes, without changing the basal activity of muscle proteostasis pathways known to affect polyQ aggregation. We find that the increased aggregation phenotype was due to regulatory variants in the gene encoding a conserved autophagy protein ATG-5. The atg-5 gene itself conferred dosage-dependent enhancement of aggregation, with the DR1350-derived allele behaving as hypermorph. Surprisingly, increased aggregation in animals carrying the modifier locus was accompanied by enhanced autophagy activation in response to activating treatment. Because autophagy is expected to clear, not increase, protein aggregates, we activated autophagy in three different polyQ models and found a striking tissue-dependent effect: activation of autophagy decreased polyQ aggregation in neurons and intestine, but increased it in the muscle cells. CONCLUSIONS: Our data show that cryptic natural variants in genes encoding proteostasis components, although not causing detectable phenotypes in wild-type individuals, can have profound effects on aggregation-prone proteins. Clinical applications of autophagy activators for aggregation diseases may need to consider the unexpected divergent effects of autophagy in different cell types

    Development of visualization facility at the GIS and Remote Sensing Core Lab, University of Nevada, Las Vegas

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    Visualization using advanced computational and graphic equipment has become a standard way of present day research. Availability of low cost and fast processing units, high resolution displays with graphic processing units, and specialized software has brought complex visualization capabilities to an office desktop. Nevertheless, when dealing with large datasets such as, global climate, geospatial, and social data the office desktop falls short and calls for a centralized visualization facility with high end computing and graphics equipment. Visualization Facility at GIS and Remote Sensing Core Lab would be a useful and important addition to the UNLV IT infrastructure. It would provide multiple audio and video facilities for facilitating research, decision support, and collaboration. The video system would consist of a wide screen display capable to 3D and picture in picture visualization; and a tiled display wall. The audio system would consist of microphones and speakers. The backend management system will provide capability to route data from multiple sources to the video and audio systems. The sources would include local sources as well as remote sources from video teleconferencing. UNLV Visualization Facility would provide an integration of visualization tools and expertise to provide researchers, decision makers, and policy makers with turn-key solutions to everyday visualization needs. This facility would be to provide the UNLV researchers ability to visualize concepts and data on a multi-screen/multi-projection system with the option to interactively study behaviors of models, data, and systems

    Noncardiac inpatient has acute hypertension: Treat or not?

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    Deputy Editor: Anne Mounsey, MD (Department of Family Medicine, University of North Carolina)A retrospective study found more harm than benefit from treating elevated blood pressure in hospitalized noncardiac patients.Robert C. Marshall, MD, MPH, MISM, FAAFP, FAMIA; Derrick J. Thiel, MD; Haroon Samar, MD, MPH (Madigan Army Medical Center). Deputy Editor: Anne Mounsey, MD (Department of Family Medicine, University of North Carolina)Includes bibliographical reference

    Estimation of Survival Rates of Female Breast Cancer Patients in Meerut City, India

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    There is no data available on cancer incidence pattern in Meerut City. This is the first report on breast cancer incidence in females among Meerut urban population during the period of 2008-09, which gives the first hand information on breast cancer incidence in females. The data for this report has been collected by us. The sources for cancer registration are the tertiary care government hospital and two private cancer referral centers in the region. A total of 285 breast cancer cases were registered during the period from 1st January, 2008 to 31st December, 2009. Complete data was analyzed by using SPSS Statistical Software version 17. Complete to Follow Up (CFU) patients survival rate were estimated by Actuarial Method (ACM) and Lost to Follow Up (LFU) patients survival rate were estimated by Lost Adjusted Survival Rate (LAR) Method.  The patients were followed up for more than three years. The overall survival rate in age group 40-49 (51%, OR=0.69, CI=0.35-01.32) was higher than that seen in other age groups were comparatively lower than other registries situated in India. Survival rate against Hindu patients (23%, OR=1.78, CI=0.93-3.27) was higher than Muslim patients and it was statistically significant. Patients with tumor size 2cm had a better survival rate (65%, OR=2.22, CI=1.22-3.98) and it was statistically significant (p=.008)

    Dynamic Subspace Estimation with Grassmannian Geodesics

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    Dynamic subspace estimation, or subspace tracking, is a fundamental problem in statistical signal processing and machine learning. This paper considers a geodesic model for time-varying subspaces. The natural objective function for this model is non-convex. We propose a novel algorithm for minimizing this objective and estimating the parameters of the model from data with Grassmannian-constrained optimization. We show that with this algorithm, the objective is monotonically non-increasing. We demonstrate the performance of this model and our algorithm on synthetic data, video data, and dynamic fMRI data

    A systematic review of the unique prospective association of negative affect symptoms and adolescent substance use controlling for externalizing symptoms.

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    This systematic review examines whether negative affect symptoms (i.e., anxiety, depression, and internalizing symptoms more broadly) predict subsequent adolescent substance use after controlling for co-occurring externalizing symptoms. Following PRISMA procedures, we identified 61 studies that tested the association of interest. Findings varied depending on the type of negative affect symptom and to some extent on the substance use outcome. The most consistent associations were evident for depressive symptoms, particularly as predictors of substance use composite scores. No clear association between anxiety and substance use or between internalizing symptoms and substance use was evident, and indeed these associations were as often negative as positive. Mixed findings regarding the depression-substance use association, however, also call for greater attention to potential moderating factors that may help define who, when, and in what context depression serves as an important risk factor for later substance use above and beyond risk associated with externalizing symptoms

    Supplementary feeding with either ready-to-use fortified spread or corn-soy blend in wasted adults starting antiretroviral therapy in Malawi: randomised, investigator blinded, controlled trial

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    Objective To investigate the effect of two different food supplements on body mass index (BMI) in wasted Malawian adults with HIV who were starting antiretroviral therapy
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