145 research outputs found

    Measuring microRNAs: Comparisons of microarray and quantitative PCR measurements, and of different total RNA prep methods

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    <p>Abstract</p> <p>Background</p> <p>Determining the expression levels of microRNAs (miRNAs) is of great interest to researchers in many areas of biology, given the significant roles these molecules play in cellular regulation. Two common methods for measuring miRNAs in a total RNA sample are microarrays and quantitative RT-PCR (qPCR). To understand the results of studies that use these two different techniques to measure miRNAs, it is important to understand how well the results of these two analysis methods correlate. Since both methods use total RNA as a starting material, it is also critical to understand how measurement of miRNAs might be affected by the particular method of total RNA preparation used.</p> <p>Results</p> <p>We measured the expression of 470 human miRNAs in nine human tissues using Agilent microarrays, and compared these results to qPCR profiles of 61 miRNAs in the same tissues. Most expressed miRNAs (53/60) correlated well (R > 0.9) between the two methods. Using spiked-in synthetic miRNAs, we further examined the two miRNAs with the lowest correlations, and found the differences cannot be attributed to differential sensitivity of the two methods. We also tested three widely-used total RNA sample prep methods using miRNA microarrays. We found that while almost all miRNA levels correspond between the three methods, there were a few miRNAs whose levels consistently differed between the different prep techniques when measured by microarray analysis. These differences were corroborated by qPCR measurements.</p> <p>Conclusion</p> <p>The correlations between Agilent miRNA microarray results and qPCR results are generally excellent, as are the correlations between different total RNA prep methods. However, there are a few miRNAs whose levels do not correlate between the microarray and qPCR measurements, or between different sample prep methods. Researchers should therefore take care when comparing results obtained using different analysis or sample preparation methods.</p

    Interactions between state pension and long-term care reforms: an overview

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    In April 2016 major reforms to state pensions and long-term care will be implemented in Great Britain and England respectively. Their combined effects have received little attention despite interactions between the two systems. The long-term effects of both sets of reforms will depend on how details of the systems are set in the intervening years, and on how policies in other parts of the welfare system evolve. We will investigate the long-term impacts of alternative ways in which current pensions and long-term care financing reforms may evolve over the next 40 years to ensure that that there is widespread appreciation of the implications of any changes which may have significant long-term effects

    Care and State Pension Reform - Interactions between state and pension long-term care reforms: a summary of findings

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    In April 2016 major reforms to state pensions were implemented in Great Britain. Reforms to the English long-term care financing system were also to be introduced in 2016 but have been postponed until 2020. The state pension reforms replace the existing two-tier state pension system with a single tier pension set just above the minimum income guaranteed through means-tested benefits. It affects only people reaching State Pension age from April 2016. The long-term care reforms introduce a cap on lifetime liability for care costs. To reach the cap, people will need to have eligible care needs for a considerable period, typically at least three years. The primary objective of the state pension reforms is to provide a clearer foundation for private pension saving and reduce reliance on means-tested benefits in retirement by setting the level of the new State Pension (nSP) above the level of the minimum income guaranteed by the means-tested benefit Pension Credit. The long-term care reforms introduce a lifetime limit on individual liability for care costs to provide protection against the risk that care costs could use up nearly all of an individual’s savings. The long-term effects of both sets of reforms will depend on how details of the systems are set in the intervening years, and in particular how components of the systems are adjusted each year – ‘uprated’ – for inflation. This report summarises the findings from a research project which aims to promote informed debate on how the reforms could evolve, highlighting the interactions between the two systems. Amongst other things, the study has analysed the impact of the reforms to 2030 under uprating assumptions consistent with current policy and under alternative uprating assumptions. A separate more detailed Technical Report of the analysis is available

    Robust interlaboratory reproducibility of a gene expression signature measurement consistent with the needs of a new generation of diagnostic tools

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    The increasing use of DNA microarrays in biomedical research, toxicogenomics, pharmaceutical development, and diagnostics has focused attention on the reproducibility and reliability of microarray measurements. While the reproducibility of microarray gene expression measurements has been the subject of several recent reports, there is still a need for systematic investigation into what factors most contribute to variability of measured expression levels observed among different laboratories and different experimenters.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

    Extended Coagulation Profiling in Isolated Traumatic Brain Injury:A CENTER-TBI Analysis

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    Background: Trauma-induced coagulopathy in traumatic brain injury (TBI) remains associated with high rates of complications, unfavorable outcomes, and mortality. The underlying mechanisms are largely unknown. Embedded in the prospective multinational Collaborative European Neurotrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study, coagulation profiles beyond standard conventional coagulation assays were assessed in patients with isolated TBI within the very early hours of injury. Methods: Results from blood samples (citrate/EDTA) obtained on hospital admission were matched with clinical and routine laboratory data of patients with TBI captured in the CENTER-TBI central database. To minimize confounding factors, patients with strictly isolated TBI (iTBI) (n = 88) were selected and stratified for coagulopathy by routine international normalized ratio (INR): (1) INR &lt; 1.2 and (2) INR ≥ 1.2. An INR &gt; 1.2 has been well adopted over time as a threshold to define trauma-related coagulopathy in general trauma populations. The following parameters were evaluated: quick’s value, activated partial thromboplastin time, fibrinogen, thrombin time, antithrombin, coagulation factor activity of factors V, VIII, IX, and XIII, protein C and S, plasminogen, D-dimer, fibrinolysis-regulating parameters (thrombin activatable fibrinolysis inhibitor, plasminogen activator inhibitor 1, antiplasmin), thrombin generation, and fibrin monomers. Results: Patients with iTBI with INR ≥ 1.2 (n = 16) had a high incidence of progressive intracranial hemorrhage associated with increased mortality and unfavorable outcome compared with patients with INR &lt; 1.2 (n = 72). Activity of coagulation factors V, VIII, IX, and XIII dropped on average by 15–20% between the groups whereas protein C and S levels dropped by 20%. With an elevated INR, thrombin generation decreased, as reflected by lower peak height and endogenous thrombin potential (ETP), whereas the amount of fibrin monomers increased. Plasminogen activity significantly decreased from 89% in patients with INR &lt; 1.2 to 76% in patients with INR ≥ 1.2. Moreover, D-dimer levels significantly increased from a mean of 943 mg/L in patients with INR &lt; 1.2 to 1,301 mg/L in patients with INR ≥ 1.2. Conclusions: This more in-depth analysis beyond routine conventional coagulation assays suggests a counterbalanced regulation of coagulation and fibrinolysis in patients with iTBI with hemostatic abnormalities. We observed distinct patterns involving key pathways of the highly complex and dynamic coagulation system that offer windows of opportunity for further research. Whether the changes observed on factor levels may be relevant and explain the worse outcome or the more severe brain injuries by themselves remains speculative.</p

    The global methane budget 2000–2017

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    Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4 yr−1 larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4 yr−1 larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4 yr−1, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget, < 30∘ N) compared to mid-latitudes (∼ 30 %, 30–60∘ N) and high northern latitudes (∼ 4 %, 60–90∘ N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters. Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4 yr−1 lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH4 yr−1 by 8 Tg CH4 yr−1, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning
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