501 research outputs found

    Accounting for Redundancy when Integrating Gene Interaction Databases

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    During the last years gene interaction networks are increasingly being used for the assessment and interpretation of biological measurements. Knowledge of the interaction partners of an unknown protein allows scientists to understand the complex relationships between genetic products, helps to reveal unknown biological functions and pathways, and get a more detailed picture of an organism's complexity. Being able to measure all protein interactions under all relevant conditions is virtually impossible. Hence, computational methods integrating different datasets for predicting gene interactions are needed. However, when integrating different sources one has to account for the fact that some parts of the information may be redundant, which may lead to an overestimation of the true likelihood of an interaction. Our method integrates information derived from three different databases (Bioverse, HiMAP and STRING) for predicting human gene interactions. A Bayesian approach was implemented in order to integrate the different data sources on a common quantitative scale. An important assumption of the Bayesian integration is independence of the input data (features). Our study shows that the conditional dependency cannot be ignored when combining gene interaction databases that rely on partially overlapping input data. In addition, we show how the correlation structure between the databases can be detected and we propose a linear model to correct for this bias. Benchmarking the results against two independent reference data sets shows that the integrated model outperforms the individual datasets. Our method provides an intuitive strategy for weighting the different features while accounting for their conditional dependencies

    Short-term effects of repetitive transcranial magnetic stimulation on sleep bruxism:a pilot study

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    The purpose of this study was to investigate the effects of repetitive transcranial magnetic stimulation (rTMS) on patients with sleep bruxism (SB). Twelve patients with SB were included in an open, single-intervention pilot study. rTMS at 1 Hz and an intensity of 80% of the active motor threshold was applied to the ‘hot spot' of the masseter muscle representation at the primary motor cortex bilaterally for 20 min per side each day for 5 consecutive days. The jaw-closing muscle electromyographic (EMG) activity during sleep was recorded with a portable EMG recorder at baseline, during rTMS treatment and at follow-up for 5 days. In addition, patients scored their jaw-closing muscle soreness on a 0–10 numerical rating scale (NRS). Data were analysed with analysis of variance. The intensity of the EMG activity was suppressed during and after rTMS compared to the baseline (P = 0.04; P = 0.02, respectively). The NRS score of soreness decreased significantly during and after rTMS compared with baseline (P < 0.01). These findings indicated a significant inhibition of jaw-closing muscle activity during sleep along with a decrease of muscle soreness. This pilot study raises the possibility of therapeutic benefits from rTMS in patients with bruxism and calls for further and more controlled studies

    Tensor based multichannel reconstruction for breast tumours identification from DCE-MRIs

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    A new methodology based on tensor algebra that uses a higher order singular value decomposition to perform three-dimensional voxel reconstruction from a series of temporal images obtained using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is proposed. Principal component analysis (PCA) is used to robustly extract the spatial and temporal image features and simultaneously de-noise the datasets. Tumour segmentation on enhanced scaled (ES) images performed using a fuzzy C-means (FCM) cluster algorithm is compared with that achieved using the proposed tensorial framework. The proposed algorithm explores the correlations between spatial and temporal features in the tumours. The multi-channel reconstruction enables improved breast tumour identification through enhanced de-noising and improved intensity consistency. The reconstructed tumours have clear and continuous boundaries; furthermore the reconstruction shows better voxel clustering in tumour regions of interest. A more homogenous intensity distribution is also observed, enabling improved image contrast between tumours and background, especially in places where fatty tissue is imaged. The fidelity of reconstruction is further evaluated on the basis of five new qualitative metrics. Results confirm the superiority of the tensorial approach. The proposed reconstruction metrics should also find future applications in the assessment of other reconstruction algorithms

    Validation of food store environment secondary data source and the role of neighborhood deprivation in Appalachia, Kentucky

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    Background Based on the need for better measurement of the retail food environment in rural settings and to examine how deprivation may be unique in rural settings, the aims of this study were: 1) to validate one commercially available data source with direct field observations of food retailers; and 2) to examine the association between modified neighborhood deprivation and the modified retail food environment score (mRFEI). Methods Secondary data were obtained from a commercial database, InfoUSA in 2011, on all retail food outlets for each census tract. In 2011, direct observation identifying all listed food retailers was conducted in 14 counties in Kentucky. Sensitivity and positive predictive values (PPV) were compared. Neighborhood deprivation index was derived from American Community Survey data. Multinomial regression was used to examine associations between neighborhood deprivation and the mRFEI score (indicator of retailers selling healthy foods such as low-fat foods and fruits and vegetables relative to retailers selling more energy dense foods). Results The sensitivity of the commercial database was high for traditional food retailers (grocery stores, supermarkets, convenience stores), with a range of 0.96-1.00, but lower for non-traditional food retailers; dollar stores (0.20) and Farmer’s Markets (0.50). For traditional food outlets, the PPV for smaller non-chain grocery stores was 38%, and large chain supermarkets was 87%. Compared to those with no stores in their neighborhoods, those with a supercenter [OR 0.50 (95% CI 0.27. 0.97)] or convenience store [OR 0.67 (95% CI 0.51, 0.89)] in their neighborhood have lower odds of living in a low deprivation neighborhood relative to a high deprivation neighborhood. Conclusion The secondary commercial database used in this study was insufficient to characterize the rural retail food environment. Our findings suggest that neighborhoods with high neighborhood deprivation are associated with having certain store types that may promote less healthy food options

    Discovery of potent, novel, non-toxic anti-malarial compounds via quantum modelling, virtual screening and in vitro experimental validation

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    <p>Abstract</p> <p>Background</p> <p>Developing resistance towards existing anti-malarial therapies emphasize the urgent need for new therapeutic options. Additionally, many malaria drugs in use today have high toxicity and low therapeutic indices. Gradient Biomodeling, LLC has developed a quantum-model search technology that uses quantum similarity and does not depend explicitly on chemical structure, as molecules are rigorously described in fundamental quantum attributes related to individual pharmacological properties. Therapeutic activity, as well as toxicity and other essential properties can be analysed and optimized simultaneously, independently of one another. Such methodology is suitable for a search of novel, non-toxic, active anti-malarial compounds.</p> <p>Methods</p> <p>A set of innovative algorithms is used for the fast calculation and interpretation of electron-density attributes of molecular structures at the quantum level for rapid discovery of prospective pharmaceuticals. Potency and efficacy, as well as additional physicochemical, metabolic, pharmacokinetic, safety, permeability and other properties were characterized by the procedure. Once quantum models are developed and experimentally validated, the methodology provides a straightforward implementation for lead discovery, compound optimizzation and <it>de novo </it>molecular design.</p> <p>Results</p> <p>Starting with a diverse training set of 26 well-known anti-malarial agents combined with 1730 moderately active and inactive molecules, novel compounds that have strong anti-malarial activity, low cytotoxicity and structural dissimilarity from the training set were discovered and experimentally validated. Twelve compounds were identified <it>in silico </it>and tested <it>in vitro</it>; eight of them showed anti-malarial activity (IC50 ≤ 10 μM), with six being very effective (IC50 ≤ 1 μM), and four exhibiting low nanomolar potency. The most active compounds were also tested for mammalian cytotoxicity and found to be non-toxic, with a therapeutic index of more than 6,900 for the most active compound.</p> <p>Conclusions</p> <p>Gradient's metric modelling approach and electron-density molecular representations can be powerful tools in the discovery and design of novel anti-malarial compounds. Since the quantum models are agnostic of the particular biological target, the technology can account for different mechanisms of action and be used for <it>de novo </it>design of small molecules with activity against not only the asexual phase of the malaria parasite, but also against the liver stage of the parasite development, which may lead to true causal prophylaxis.</p

    Connective Tissue Growth Factor Overexpression in Cardiomyocytes Promotes Cardiac Hypertrophy and Protection against Pressure Overload

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    Connective tissue growth factor (CTGF) is a secreted protein that is strongly induced in human and experimental heart failure. CTGF is said to be profibrotic; however, the precise function of CTGF is unclear. We generated transgenic mice and rats with cardiomyocyte-specific CTGF overexpression (CTGF-TG). To investigate CTGF as a fibrosis inducer, we performed morphological and gene expression analyses of CTGF-TG mice and rat hearts under basal conditions and after stimulation with angiotensin II (Ang II) or isoproterenol, respectively. Surprisingly, cardiac tissues of both models did not show increased fibrosis or enhanced gene expression of fibrotic markers. In contrast to controls, Ang II treated CTGF-TG mice displayed preserved cardiac function. However, CTGF-TG mice developed age-dependent cardiac dysfunction at the age of 7 months. CTGF related heart failure was associated with Akt and JNK activation, but not with the induction of natriuretic peptides. Furthermore, cardiomyocytes from CTGF-TG mice showed unaffected cellular contractility and an increased Ca2+ reuptake from sarcoplasmatic reticulum. In an ischemia/reperfusion model CTGF-TG hearts did not differ from controls

    How are compassion fatigue, burnout, and compassion satisfaction affected by quality of working life? Findings from a survey of mental health staff in Italy

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    BACKGROUND: Quality of working life includes elements such as autonomy, trust, ergonomics, participation, job complexity, and work-life balance. The overarching aim of this study was to investigate if and how quality of working life affects Compassion Fatigue, Burnout, and Compassion Satisfaction among mental health practitioners. METHODS: Staff working in three Italian Mental Health Departments completed the Professional Quality of Life Scale, measuring Compassion Fatigue, Burnout, and Compassion Satisfaction, and the Quality of Working Life Questionnaire. The latter was used to collect socio-demographics, occupational characteristics and 13 indicators of quality of working life. Multiple regressions controlling for other variables were undertaken to predict Compassion Fatigue, Burnout, and Compassion Satisfaction. RESULTS: Four hundred questionnaires were completed. In bivariate analyses, experiencing more ergonomic problems, perceiving risks for the future, a higher impact of work on life, and lower levels of trust and of perceived quality of meetings were associated with poorer outcomes. Multivariate analysis showed that (a) ergonomic problems and impact of work on life predicted higher levels of both Compassion Fatigue and Burnout; (b) impact of life on work was associated with Compassion Fatigue and lower levels of trust and perceiving more risks for the future with Burnout only; (c) perceived quality of meetings, need of training, and perceiving no risks for the future predicted higher levels of Compassion Satisfaction. CONCLUSIONS: In order to provide adequate mental health services, service providers need to give their employees adequate ergonomic conditions, giving special attention to time pressures. Building trustful relationships with management and within the teams is also crucial. Training and meetings are other important targets for potential improvement. Additionally, insecurity about the future should be addressed as it can affect both Burnout and Compassion Satisfaction. Finally, strategies to reduce possible work-life conflicts need to be considered

    Reducing Alaska Native paediatric oral health disparities: a systematic review of oral health interventions and a case study on multilevel strategies to reduce sugar-sweetened beverage intake

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    Background. Tooth decay is the most common paediatric disease and there is a serious paediatric tooth decay epidemic in Alaska Native communities. When untreated, tooth decay can lead to pain, infection, systemic health problems, hospitalisations and in rare cases death, as well as school absenteeism, poor grades and low quality-of-life. The extent to which population-based oral health interventions have been conducted in Alaska Native paediatric populations is unknown. Objective. To conduct a systematic review of oral health interventions aimed at Alaska Native children below age 18 and to present a case study and conceptual model on multilevel intervention strategies aimed at reducing sugar-sweetened beverage (SSB) intake among Alaska Native children. Design. Based on the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) Statement, the terms &#x201C;Alaska Native&#x201D;, &#x201C;children&#x201D; and &#x201C;oral health&#x201D; were used to search Medline, Embase, Web of Science, GoogleScholar and health foundation websites (1970&#x2013;2012) for relevant clinical trials and evaluation studies. Results. Eighty-five studies were found in Medline, Embase and Web of Science databases and there were 663 hits in GoogleScholar. A total of 9 publications were included in the qualitative review. These publications describe 3 interventions that focused on: reducing paediatric tooth decay by educating families and communities; providing dental chemotherapeutics to pregnant women; and training mid-level dental care providers. While these approaches have the potential to improve the oral health of Alaska Native children, there are unique challenges regarding intervention acceptability, reach and sustainability. A case study and conceptual model are presented on multilevel strategies to reduce SSB intake among Alaska Native children. Conclusions. Few oral health interventions have been tested within Alaska Native communities. Community-centred multilevel interventions are promising approaches to improve the oral and systemic health of Alaska Native children. Future investigators should evaluate the feasibility of implementing multilevel interventions and policies within Alaska Native communities as a way to reduce children&#x0027;s health disparities
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