373 research outputs found

    The transcriptional response of Caenorhabditis elegans to ivermectin exposure identifies novel genes involved in the response to reduced food intake

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    We have examined the transcriptional response of Caenorhabditis elegans following exposure to the anthelmintic drug ivermectin (IVM) using whole genome microarrays and real-time QPCR. Our original aim was to identify candidate molecules involved in IVM metabolism and/or excretion. For this reason the IVM tolerant strain, DA1316, was used to minimise transcriptomic changes related to the phenotype of drug exposure. However, unlike equivalent work with benzimidazole drugs, very few of the induced genes were members of xenobiotic metabolising enzyme families. Instead, the transcriptional response was dominated by genes associated with fat mobilization and fatty acid metabolism including catalase, esterase, and fatty acid CoA synthetase genes. This is consistent with the reduction in pharyngeal pumping, and consequential reduction in food intake, upon exposure of DA1316 worms to IVM. Genes with the highest fold change in response to IVM exposure, cyp-37B1, mtl-1 and scl-2, were comparably up-regulated in response to short–term food withdrawal (4 hr) independent of IVM exposure, and GFP reporter constructs confirm their expression in tissues associated with fat storage (intestine and hypodermis). These experiments have serendipitously identified novel genes involved in an early response of C. elegans to reduced food intake and may provide insight into similar processes in higher organisms

    In silico approach to screen compounds active against parasitic nematodes of major socio-economic importance

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    Infections due to parasitic nematodes are common causes of morbidity and fatality around the world especially in developing nations. At present however, there are only three major classes of drugs for treating human nematode infections. Additionally the scientific knowledge on the mechanism of action and the reason for the resistance to these drugs is poorly understood. Commercial incentives to design drugs that are endemic to developing countries are limited therefore, virtual screening in academic settings can play a vital role is discovering novel drugs useful against neglected diseases. In this study we propose to build robust machine learning model to classify and screen compounds active against parasitic nematodes.A set of compounds active against parasitic nematodes were collated from various literature sources including PubChem while the inactive set was derived from DrugBank database. The support vector machine (SVM) algorithm was used for model development, and stratified ten-fold cross validation was used to evaluate the performance of each classifier. The best results were obtained using the radial basis function kernel. The SVM method achieved an accuracy of 81.79% on an independent test set. Using the model developed above, we were able to indentify novel compounds with potential anthelmintic activity.In this study, we successfully present the SVM approach for predicting compounds active against parasitic nematodes which suggests the effectiveness of computational approaches for antiparasitic drug discovery. Although, the accuracy obtained is lower than the previously reported in a similar study but we believe that our model is more robust because we intentionally employed stringent criteria to select inactive dataset thus making it difficult for the model to classify compounds. The method presents an alternative approach to the existing traditional methods and may be useful for predicting hitherto novel anthelmintic compounds.12 page(s

    Long-Term climate change commitment and reversibility: An EMIC intercomparison

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    This is the final version of the article. Available from the American Meteorological Society via the DOI in this record.This paper summarizes the results of an intercomparison project with Earth System Models of Intermediate Complexity (EMICs) undertaken in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). The focus is on long-term climate projections designed to 1) quantify the climate change commitment of different radiative forcing trajectories and 2) explore the extent to which climate change is reversible on human time scales. All commitment simulations follow the four representative concentration pathways (RCPs) and their extensions to year 2300. MostEMICs simulate substantial surface air temperature and thermosteric sea level rise commitment following stabilization of the atmospheric composition at year-2300 levels. The meridional overturning circulation (MOC) is weakened temporarily and recovers to near-preindustrial values in most models for RCPs 2.6-6.0. The MOC weakening is more persistent for RCP8.5. Elimination of anthropogenic CO2 emissions after 2300 results in slowly decreasing atmospheric CO2 concentrations. At year 3000 atmospheric CO2 is still at more than half its year-2300 level in all EMICs forRCPs 4.5-8.5. Surface air temperature remains constant or decreases slightly and thermosteric sea level rise continues for centuries after elimination ofCO2 emissions in allEMICs.Restoration of atmosphericCO2 fromRCPto preindustrial levels over 100-1000 years requires large artificial removal of CO2 from the atmosphere and does not result in the simultaneous return to preindustrial climate conditions, as surface air temperature and sea level response exhibit a substantial time lag relative to atmospheric CO2. © 2013 American Meteorological Society.KZ and AJW acknowledge support from the National Science and Engineering Research Council (NSERC) Discovery Grant Program. AJW acknowledges support from NSERC's G8 Research Councils Initiative on Multilateral Research Funding Program. AVE and IIM were supported by the President of Russia Grant 5467.2012.5, by the Russian Foundation for Basic Research, and by the programs of the Russian Academy of Sciences. EC, TF, HG, and GPB acknowledge support from the Belgian Federal Science Policy Office. FJ, RS, and MS acknowledge support by the Swiss National Science Foundation and by the European Project CARBOCHANGE (Grant 264879), which received funding from the European Commission's Seventh Framework Programme (FP7/2007–2013). PBH and NRE acknowledge support from EU FP7 Grant ERMITAGE 265170

    Efficacy of an Educational Material on Second Primary Cancer Screening Practice for Cancer Survivors: A Randomized Controlled Trial

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    <div><h3>Background</h3><p>Cancer surivors have limited knowledge about second primary cancer (SPC) screening and suboptimal rates of completion of screening practices for SPC. Our objective was to test the efficacy of an educational material on the knowledge, attitudes, and screening practices for SPC among cancer survivors.</p> <h3>Methods</h3><p>Randomized, controlled trial among 326 cancer survivors from 6 oncology care outpatient clinics in Korea. Patients were randomized to an intervention or an attention control group. The intervention was a photo-novel, culturally tailored to increase knowledge about SPC screening. Knowledge and attitudes regarding SPC screening were assessed two weeks after the intervention, and screening practices were assessed after one year.</p> <h3>Results</h3><p>At two weeks post-intervention, the average knowledge score was significantly higher in the intervention compared to the control group (0.81 vs. 0.75, P<0.01), with no significant difference in their attitude scores (2.64 vs. 2.57, P = 0.18). After 1 year of follow-up, the completion rate of all appropriate cancer screening was 47.2% in both intervention and control groups.</p> <h3>Conclusion</h3><p>While the educatinal material was effective for increasing knowledge of SPC screening, it did not promote cancer screening practice among cancer survivors. More effective interventions are needed to increase SPC screening rates in this population.</p> <h3>Trial Registration</h3><p>ClinicalTrial.gov <a href="http://clinicaltrials.gov/ct2/show/NCT00948337">NCT00948337</a></p> </div

    Increasing upper limb training intensity in chronic stroke using embodied virtual reality: a pilot study.

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    Technology-mediated neurorehabilitation is suggested to enhance training intensity and therefore functional gains. Here, we used a novel virtual reality (VR) system for task-specific upper extremity training after stroke. The system offers interactive exercises integrating motor priming techniques and embodied visuomotor feedback. In this pilot study, we examined (i) rehabilitation dose and training intensity, (ii) functional improvements, and (iii) safety and tolerance when exposed to intensive VR rehabilitation. Ten outpatient stroke survivors with chronic (&gt;6 months) upper extremity paresis participated in a ten-session VR-based upper limb rehabilitation program (2 sessions/week). All participants completed all sessions of the treatment. In total, they received a median of 403 min of upper limb therapy, with 290 min of effective training. Within that time, participants performed a median of 4713 goal-directed movements. Importantly, training intensity increased progressively across sessions from 13.2 to 17.3 movements per minute. Clinical measures show that despite being in the chronic phase, where recovery potential is thought to be limited, participants showed a median improvement rate of 5.3% in motor function (Fugl-Meyer Assessment for Upper Extremity; FMA-UE) post intervention compared to baseline, and of 15.4% at one-month follow-up. For three of them, this improvement was clinically significant. A significant improvement in shoulder active range of motion (AROM) was also observed at follow-up. Participants reported very low levels of pain, stress and fatigue following each session of training, indicating that the intensive VR intervention was well tolerated. No severe adverse events were reported. All participants expressed their interest in continuing the intervention at the hospital or even at home, suggesting high levels of adherence and motivation for the provided intervention. This pilot study showed how a dedicated VR system could deliver high rehabilitation doses and, importantly, intensive training in chronic stroke survivors. FMA-UE and AROM results suggest that task-specific VR training may be beneficial for further functional recovery both in the chronic stage of stroke. Longitudinal studies with higher doses and sample sizes are required to confirm the therapy effectiveness. This trial was retrospectively registered at ClinicalTrials.gov database (registration number NCT03094650 ) on 14 March 2017

    Imbalanced functional link between executive control network and reward network explain the online-game seeking behaviors in Internet gaming disorder

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    Literatures have shown that Internet gaming disorder (IGD) subjects show impaired executive control and enhanced reward sensitivities than healthy controls. However, how these two networks jointly affect the valuation process and drive IGD subjects' online-game-seeking behaviors remains unknown. Thirty-five IGD and 36 healthy controls underwent a resting-states scan in the MRI scanner. Functional connectivity (FC) was examined within control and reward network seeds regions, respectively. Nucleus accumbens (NAcc) was selected as the node to find the interactions between these two networks. IGD subjects show decreased FC in the executive control network and increased FC in the reward network when comparing with the healthy controls. When examining the correlations between the NAcc and the executive control/reward networks, the link between the NAcc - executive control network is negatively related with the link between NAcc - reward network. The changes (decrease/increase) in IGD subjects' brain synchrony in control/reward networks suggest the inefficient/overly processing within neural circuitry underlying these processes. The inverse proportion between control network and reward network in IGD suggest that impairments in executive control lead to inefficient inhibition of enhanced cravings to excessive online game playing. This might shed light on the mechanistic understanding of IGD
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