336 research outputs found

    Sirt1 Regulates Insulin Secretion by Repressing UCP2 in Pancreatic β Cells

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    Sir2 and insulin/IGF-1 are the major pathways that impinge upon aging in lower organisms. In Caenorhabditis elegans a possible genetic link between Sir2 and the insulin/IGF-1 pathway has been reported. Here we investigate such a link in mammals. We show that Sirt1 positively regulates insulin secretion in pancreatic β cells. Sirt1 represses the uncoupling protein (UCP) gene UCP2 by binding directly to the UCP2 promoter. In β cell lines in which Sirt1 is reduced by SiRNA, UCP2 levels are elevated and insulin secretion is blunted. The up-regulation of UCP2 is associated with a failure of cells to increase ATP levels after glucose stimulation. Knockdown of UCP2 restores the ability to secrete insulin in cells with reduced Sirt1, showing that UCP2 causes the defect in glucose-stimulated insulin secretion. Food deprivation induces UCP2 in mouse pancreas, which may occur via a reduction in NAD (a derivative of niacin) levels in the pancreas and down-regulation of Sirt1. Sirt1 knockout mice display constitutively high UCP2 expression. Our findings show that Sirt1 regulates UCP2 in β cells to affect insulin secretion

    'Ready to hit the ground running': alumni and employer accounts of a unique part-time distance learning pre-registration nurse education programme

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    Background This study explored the impact of The Open University’s (OU) pre-registration nursing programme on students’ employability, career progression and its contribution to developing the nursing workforce across the United Kingdom. Designed for healthcare support workers who are sponsored by their employers, the programme is the only part-time supported open/distance learning programme in the UK leading to registration as a nurse. The international literature reveals that relatively little is known about the impact of previous experience as a healthcare support worker on the experience of transition, employability skills and career progression. Objectives To identify alumni and employer views of the perceived impact of the programme on employability, career progression and workforce development. Design/Method A qualitative design using telephone interviews which were digitally recorded, transcribed verbatim prior to content analysis to identify recurrent themes. Settings Three geographical areas across the UK. Participants Alumni (n=17) and employers (n=7). Inclusion criterion for alumni was a minimum of two years post-qualifying experience. Inclusion criteria for employers were those that had responsibility for sponsoring students on the programme and employing them as newly qualified nurses. Results Four overarching themes were identified: Transition, Expectations, Learning for and in practice, and Flexibility. Conclusions Alumni and employers were of the view that the programme equipped them well to meet the competencies and expectations of being a newly qualified nurse. It provided employers with a flexible route to growing their own workforce and alumni the opportunity to achieve their ambition of becoming a qualified nurse when other more conventional routes would not have been open to them. Some of them had already demonstrated career progression. Generalising results requires caution due to the small, self-selecting sample but findings suggest that a widening participation model of pre-registration nurse education for employed healthcare support workers more than adequately prepares them for the realities of professional practice

    Greedy and linear ensembles of machine learning methods outperform single approaches for QSPR regression problems

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    The application of Machine Learning to cheminformatics is a large and active field of research, but there exist few papers which discuss whether ensembles of different Machine Learning methods can improve upon the performance of their component methodologies. Here we investigated a variety of methods, including kernel-based, tree, linear, neural networks, and both greedy and linear ensemble methods. These were all tested against a standardised methodology for regression with data relevant to the pharmaceutical development process. Thinvestigation focused on QSPR problems within drug-like chemical space. We aimed to investigate which methods perform best, and how the ‘wisdom of crowds’ principle can be applied to ensemble predictors. It was found that no single method performs best for all problems, but that a dynamic, well-structured ensemble predictor would perform very well across the board, usually providing an improvement in performance over the best single method. Its use of weighting factors allows the greedy ensemble to acquire a bigger contribution from the better performing models, and this helps the greedy ensemble generally to outperform the simpler linear ensemble. Choice of data pre-processing methodology was found to be crucial to performance of each method too.PostprintPeer reviewe

    EFSA NDA Panel (EFSA Panel on Dietetic Products, Nutrition and Allergies), 2013 . Scientific opinion on Dietary Reference Values for fluoride

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    Following a request from the European Commission, the Panel on Dietetic Products, Nutrition and Allergies (NDA) derived Dietary Reference Values (DRVs) for fluoride, which are provided as Adequate Intake (AI) from all sources, including non-dietary sources. Fluoride is not an essential nutrient. Therefore, no Average Requirement for the performance of essential physiological functions can be defined. Nevertheless, the Panel considered that the setting of an AI is appropriate because of the beneficial effects of dietary fluoride on prevention of dental caries. The AI is based on epidemiological studies (performed before the 1970s) showing an inverse relationship between the fluoride concentration of water and caries prevalence. As the basis for defining the AI, estimates of mean fluoride intakes of children via diet and drinking water with fluoride concentrations at which the caries preventive effect approached its maximum whilst the risk of dental fluorosis approached its minimum were chosen. Except for one confirmatory longitudinal study in US children, more recent studies were not taken into account as they did not provide information on total dietary fluoride intake, were potentially confounded by the use of fluoride-containing dental hygiene products, and did not permit a conclusion to be drawn on a dose-response relationship between fluoride intake and caries risk. The AI of fluoride from all sources (including non-dietary sources) is 0.05 mg/kg body weight per day for both children and adults, including pregnant and lactating women. For pregnant and lactating women, the AI is based on the body weight before pregnancy and lactation. Reliable and representative data on the total fluoride intake of the European population are not available

    Diabetes is associated with risk of postoperative cognitive dysfunction: a meta-analysis

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    BACKGROUND: Postoperative cognitive dysfunction (POCD) occurs frequently after surgery, particularly among older people. Diabetes, chronic hyperglycemia, and a history of hypoglycemia are related to cognitive impairment, but little is known about their roles in POCD. Here, we estimated their associations with risk of POCD on the basis of published epidemiological research. METHODS: The PubMed and Cochrane databases were searched for longitudinal studies of adults undergoing surgery with reporting of associations of diabetes status, glycemic levels, and/or a history of hypoglycemia with risk of POCD as relative risks or odds ratios. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) and Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines were followed. RESULTS: The search identified 246 publications of which 14 met inclusion criteria, reporting on a total of 2642 patients (mean age 64 y). Follow-up periods spanned 1 day to 5 years. Overall, patients with diabetes had a 1.26-fold higher risk of POCD compared with diabetes-free patients (95% CI, 1.12-1.42). A single study assessed glycemic control in patients with diabetes and identified a higher hemoglobin A1c (HbA1c) level as associated with higher POCD risk (relative risk per percent higher HbA1c, 2.0; 95% CI, 1.4-2.6). We did not find studies on glycemic levels in the nondiabetic range or on hypoglycemia as potential predictors of POCD. CONCLUSION: Patients with diabetes appear to have a higher risk of POCD compared with diabetes-free persons. Among patients with diabetes, POCD risk may further increase with poorer glycemic control as indexed by higher HbA1c. The roles of HbA1c levels among nondiabetic persons in POCD risk warrant further research

    Carbon benefits of wolfberry plantation on secondary saline land in Jingtai oasis, Gansu:A case study on application of the CBP model

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    The largest global source of anthropogenic CO2 emissions comes from the burning of fossil fuel and approximately 30% of total net emissions come from land use and land use change. Forestation and reforestation are regarded worldwide as effective options of sequestering carbon to mitigate climate change with relatively low costs compared with industrial greenhouse gas (GHG) emission reduction efforts. Cash trees with a steady augmentation in size are recognized as a multiple-beneficial solution to climate change in China. The reporting of C changes and GHG emissions for sustainable land management (SLM) practices such as afforestation is required for a variety of reasons, such as devising land management options and making policy. The Carbon Benefit Project (CBP) Simple Assessment Tool was employed to estimate changes in soil organic carbon (SOC) stocks and GHG emissions for wolfberry (Lycium barbarum L.) planting on secondary salinized land over a 10 year period (2004–2014) in the Jingtai oasis in Gansu with salinized barren land as baseline scenario. Results show that wolfberry plantation, an intensively managed ecosystem, served as a carbon sink with a large potential for climate change mitigation, a restorative practice for saline land and income stream generator for farmers in soil salinized regions in Gansu province. However, an increase in wolfberry production, driven by economic demands, would bring environmental pressures associated with the use of N fertilizer and irrigation. With an understanding of all of the components of an ecosystem and their interconnections using the Drivers-Pressures-State-Impact-Response (DPSIR) framework there comes a need for strategies to respond to them such as capacity building, judicious irrigation and institutional strengthening. Cost benefit analysis (CBA) suggests that wolfberry cultivation was economically profitable and socially beneficial and thus well-accepted locally in the context of carbon sequestration. This study has important implications for Gansu as it helps to understand the role cash trees can play in carbon emission reductions. Such information is necessary in devising management options for sustainable land management (SLM)

    Aggregator: a machine learning approach to identifying MEDLINE articles that derive from the same underlying clinical trial

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    Objective It is important to identify separate publications that report outcomes from the same underlying clinical trial, in order to avoid over-counting these as independent pieces of evidence. Methods We created positive and negative training sets (comprised of pairs of articles reporting on the same condition and intervention) that were, or were not, linked to the same clinicaltrials.gov trial registry number. Features were extracted from MEDLINE and PubMed metadata; pairwise similarity scores were modeled using logistic regression. Results Article pairs from the same trial were identified with high accuracy (F1 score = 0.843). We also created a clustering tool, Aggregator, that takes as input a PubMed user query for RCTs on a given topic, and returns article clusters predicted to arise from the same clinical trial. Discussion Although painstaking examination of full-text may be needed to be conclusive, metadata are surprisingly accurate in predicting when two articles derive from the same underlying clinical trial

    Bioconjugation Strategies for Microtoroidal Optical Resonators

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    The development of label-free biosensors with high sensitivity and specificity is of significant interest for medical diagnostics and environmental monitoring, where rapid and real-time detection of antigens, bacteria, viruses, etc., is necessary. Optical resonant devices, which have very high sensitivity resulting from their low optical loss, are uniquely suited to sensing applications. However, previous research efforts in this area have focused on the development of the sensor itself. While device sensitivity is an important feature of a sensor, specificity is an equally, if not more, important performance parameter. Therefore, it is crucial to develop a covalent surface functionalization process, which also maintains the device’s sensing capabilities or optical qualities. Here, we demonstrate a facile method to impart specificity to optical microcavities, without adversely impacting their optical performance. In this approach, we selectively functionalize the surface of the silica microtoroids with biotin, using amine-terminated silane coupling agents as linkers. The surface chemistry of these devices is demonstrated using X-ray photoelectron spectroscopy, and fluorescent and optical microscopy. The quality factors of the surface functionalized devices are also characterized to determine the impact of the chemistry methods on the device sensitivity. The resulting devices show uniform surface coverage, with no microstructural damage. This work represents one of the first examples of non-physisorption-based bioconjugation of microtoroidal optical resonators
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