1,466 research outputs found

    Characterisation of cellulose pulps isolated from Miscanthus using a low-cost acidic ionic liquid

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    The ionoSolv pretreatment generates a cellulose pulp by extracting hemicellulose and lignin using low-cost ionic liquids. In this study, cellulose pulp was obtained from Miscanthus × giganteus using the protic ionic liquid triethylammonium hydrogen sulfate [N2220][HSO4] with 20% water as a co-solvent and characterised in detail for its material properties as a function of pretreatment severity. We measured the particle size distribution, porosity and crystallinity of the unbleached pulps and the molar weight distribution of the cellulose contained within. We report that the surface area increased and the size of the pulp particles decreased as ionoSolv processing progressed. While the native cellulose I structure was maintained, the average degree of polymerisation of the cellulose was reduced to a DPn of around 300, showing the cellulose polymers are shortened. We correlate the pulp properties with enzymatic saccharification yields, concluding that enzymatic saccharification of the cellulose after ionoSolv pretreatment is mainly enhanced by removing hemicellulose and lignin. We also observed that overtreatment deteriorated saccharification yield and that this coincides with cellulose fibrils becoming coated with pseudolignin redeposited from the ionic liquid solution, as demonstrated by FT-IR spectroscopy. Pseudolignin deposition increases the apparent lignin content, which is likely to increase chemical demand in bleaching, suggesting that both glucose release and material use benefit from a minimum lignin content. Overall, this study demonstrates that cellulose pulps isolated with ionoSolv processing are not only a promising intermediate for high-yield release of purified glucose for biorefining, but also have attractive properties for materials applications that require cellulose I fibrils

    Counting hard-to-count populations: the network scale-up method for public health

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    Estimating sizes of hidden or hard-to-reach populations is an important problem in public health. For example, estimates of the sizes of populations at highest risk for HIV and AIDS are needed for designing, evaluating and allocating funding for treatment and prevention programmes. A promising approach to size estimation, relatively new to public health, is the network scale-up method (NSUM), involving two steps: estimating the personal network size of the members of a random sample of a total population and, with this information, estimating the number of members of a hidden subpopulation of the total population. We describe the method, including two approaches to estimating personal network sizes (summation and known population). We discuss the strengths and weaknesses of each approach and provide examples of international applications of the NSUM in public health. We conclude with recommendations for future research and evaluation

    Macroeconomic policy interaction: State dependency and implications for financial stability in UK: A systemic review

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    The association between economic and financial stabilities and influence of macroeconomic policies on the financial sector creates scope of active policy role in financial stability. As a contribution to the existing body of knowledge, this study has analysed the implications of macroeconomic policy interaction/coordination for financial stability, proxied by financial assets, i.e. equity and bonds price oscillation. The critical review and analysis of the existing literature on the subject suggests that there is also ample evidence of interdependence between monetary and fiscal policies and this interrelation necessitates coordination between them for the sake of financial stability. There is also a case for analysing the symmetry of financial markets responses to macroeconomic policy interaction. On methodological and empirical grounds, it is vital to test the robustness of policy recommendations to overcome the limitation of a single empirical approach (Jeffrey–Lindley’s paradox). Hence, the Frequentist and Bayesian approaches should be used in commentary manner. The policy interaction and optimal policy combination should also be analysed in the context of institutional design and major financial events to gain insight into the implications of policy interaction in the periods of stable economic and financial environments as well as period of financial and economic distress

    Medicos, poultice wallahs and comrades in service: masculinity and military medicine in Britain during the First World War

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    The subject of British military medicine during the First World War has long been a fruitful one for historians of gender. From the bodily inspection of recruits and conscripts through the expanding roles of women as medical care providers to the physical and emotional aftermath of conflict experienced by men suffering from war-related wounds and illness, the medical history of the war has shed important light on how the war shaped British masculinities and femininities as cultural, subjective and embodied identities. Much of this literature has, however, focused on the gendered identities of female nurses and sick and wounded servicemen. Increasingly, however, more complex understandings of the ways in which medical caregiving in wartime shaped the gender identities of male caregivers are starting to emerge. This article explores some of these emerging understandings of the masculinity of male medical caregivers, and their relationship to the wider literature around the complex and sometimes contradictory relationship between warfare and medicine. It examines the ways in which the masculine identity of male medical caregivers from the ranks of the Royal Army Medical Corps, namely stretcher bearers and medical orderlies, was perceived and represented both by the men themselves and those they cared for. In doing so it argues that total war played a crucial role in shaping social and cultural perceptions of caregiving as a gendered practice. It also identifies particular tensions between continuity and change in social understandings of medical care as a gendered practice which would continue to shape twentieth-century British society in the war’s aftermath

    International Federation of Clinical Neurophysiology (IFCN) – EEG research workgroup: Recommendations on frequency and topographic analysis of resting state EEG rhythms. Part 1: Applications in clinical research studies

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    In 1999, the International Federation of Clinical Neurophysiology (IFCN) published “IFCN Guidelines for topographic and frequency analysis of EEGs and EPs” (Nuwer et al., 1999). Here a Workgroup of IFCN experts presents unanimous recommendations on the following procedures relevant for the topographic and frequency analysis of resting state EEGs (rsEEGs) in clinical research defined as neurophysiological experimental studies carried out in neurological and psychiatric patients: (1) recording of rsEEGs (environmental conditions and instructions to participants; montage of the EEG electrodes; recording settings); (2) digital storage of rsEEG and control data; (3) computerized visualization of rsEEGs and control data (identification of artifacts and neuropathological rsEEG waveforms); (4) extraction of “synchronization” features based on frequency analysis (band-pass filtering and computation of rsEEG amplitude/power density spectrum); (5) extraction of “connectivity” features based on frequency analysis (linear and nonlinear measures); (6) extraction of “topographic” features (topographic mapping; cortical source mapping; estimation of scalp current density and dura surface potential; cortical connectivity mapping), and (7) statistical analysis and neurophysiological interpretation of those rsEEG features. As core outcomes, the IFCN Workgroup endorsed the use of the most promising “synchronization” and “connectivity” features for clinical research, carefully considering the limitations discussed in this paper. The Workgroup also encourages more experimental (i.e. simulation studies) and clinical research within international initiatives (i.e., shared software platforms and databases) facing the open controversies about electrode montages and linear vs. nonlinear and electrode vs. source levels of those analyses

    E2F1 and KIAA0191 expression predicts breast cancer patient survival

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    <p>Abstract</p> <p>Background</p> <p>Gene expression profiling of human breast tumors has uncovered several molecular signatures that can divide breast cancer patients into good and poor outcome groups. However, these signatures typically comprise many genes (~50-100), and the prognostic tests associated with identifying these signatures in patient tumor specimens require complicated methods, which are not routinely available in most hospital pathology laboratories, thus limiting their use. Hence, there is a need for more practical methods to predict patient survival.</p> <p>Methods</p> <p>We modified a feature selection algorithm and used survival analysis to derive a 2-gene signature that accurately predicts breast cancer patient survival.</p> <p>Results</p> <p>We developed a tree based decision method that segregated patients into various risk groups using <it>KIAA0191 </it>expression in the context of <it>E2F1 </it>expression levels. This approach led to highly accurate survival predictions in a large cohort of breast cancer patients using only a 2-gene signature.</p> <p>Conclusions</p> <p>Our observations suggest a possible relationship between <it>E2F1 </it>and <it>KIAA0191 </it>expression that is relevant to the pathogenesis of breast cancer. Furthermore, our findings raise the prospect that the practicality of patient prognosis methods may be improved by reducing the number of genes required for analysis. Indeed, our <it>E2F1/KIAA0191 </it>2-gene signature would be highly amenable for an immunohistochemistry based test, which is commonly used in hospital laboratories.</p

    Report 13: Estimating the number of infections and the impact of non-pharmaceutical interventions on COVID-19 in 11 European countries

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    Following the emergence of a novel coronavirus (SARS-CoV-2) and its spread outside of China, Europe is now experiencing large epidemics. In response, many European countries have implemented unprecedented non-pharmaceutical interventions including case isolation, the closure of schools and universities, banning of mass gatherings and/or public events, and most recently, widescale social distancing including local and national lockdowns. In this report, we use a semi-mechanistic Bayesian hierarchical model to attempt to infer the impact of these interventions across 11 European countries. Our methods assume that changes in the reproductive number – a measure of transmission - are an immediate response to these interventions being implemented rather than broader gradual changes in behaviour. Our model estimates these changes by calculating backwards from the deaths observed over time to estimate transmission that occurred several weeks prior, allowing for the time lag between infection and death. One of the key assumptions of the model is that each intervention has the same effect on the reproduction number across countries and over time. This allows us to leverage a greater amount of data across Europe to estimate these effects. It also means that our results are driven strongly by the data from countries with more advanced epidemics, and earlier interventions, such as Italy and Spain. We find that the slowing growth in daily reported deaths in Italy is consistent with a significant impact of interventions implemented several weeks earlier. In Italy, we estimate that the effective reproduction number, Rt, dropped to close to 1 around the time of lockdown (11th March), although with a high level of uncertainty. Overall, we estimate that countries have managed to reduce their reproduction number. Our estimates have wide credible intervals and contain 1 for countries that have implemented all interventions considered in our analysis. This means that the reproduction number may be above or below this value. With current interventions remaining in place to at least the end of March, we estimate that interventions across all 11 countries will have averted 59,000 deaths up to 31 March [95% credible interval 21,000-120,000]. Many more deaths will be averted through ensuring that interventions remain in place until transmission drops to low levels. We estimate that, across all 11 countries between 7 and 43 million individuals have been infected with SARS-CoV-2 up to 28th March, representing between 1.88% and 11.43% of the population. The proportion of the population infected to date – the attack rate - is estimated to be highest in Spain followed by Italy and lowest in Germany and Norway, reflecting the relative stages of the epidemics. Given the lag of 2-3 weeks between when transmission changes occur and when their impact can be observed in trends in mortality, for most of the countries considered here it remains too early to be certain that recent interventions have been effective. If interventions in countries at earlier stages of their epidemic, such as Germany or the UK, are more or less effective than they were in the countries with advanced epidemics, on which our estimates are largely based, or if interventions have improved or worsened over time, then our estimates of the reproduction number and deaths averted would change accordingly. It is therefore critical that the current interventions remain in place and trends in cases and deaths are closely monitored in the coming days and weeks to provide reassurance that transmission of SARS-Cov-2 is slowing
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