1,790 research outputs found

    Mutant p53 cancers reprogram macrophages to tumor supporting macrophages via exosomal miR-1246

    Get PDF
    TP53 mutants (mutp53) are involved in the pathogenesis of most human cancers. Specific mutp53 proteins gain oncogenic functions (GOFs) distinct from the tumor suppressor activity of the wild-type protein. Tumor-associated macrophages (TAMs), a hallmark of solid tumors, are typically correlated with poor prognosis. Here, we report a non-cell-autonomous mechanism, whereby human mutp53 cancer cells reprogram macrophages to a tumor supportive and anti-inflammatory state. The colon cancer cells harboring GOF mutp53 selectively shed miR-1246-enriched exosomes. Uptake of these exosomes by neighboring macrophages triggers their miR-1246-dependent reprogramming into a cancerpromoting state. Mutp53-reprogammed TAMs favor anti-inflammatory immunosuppression with increased activity of TGF-β. These findings, associated with poor survival in colon cancer patients, strongly support a microenvironmental GOF role for mutp53 in actively engaging the immune system to promote cancer progression and metastasis

    Reasons for accepting or declining to participate in randomized clinical trials for cancer therapy

    Get PDF
    This paper reports on the reasons why patients agreed to or declined entry into randomized trials of cancer following discussions conducted by clinicians in both District General and University Hospitals. Two hundred and four patients completed a 16-item questionnaire following the consultation, of these 112 (55%) were women with breast cancer. Overall results showed that 147 (72.1%) patients accepted entry to a randomized clinical trial (RCT). The main reasons nominated for participating in a trial were that ‘others will benefit’ (23.1%) and ‘trust in the doctor’ (21.1%). One of the main reasons for declining trial entry was that patients were ‘worried about randomization’ (19.6%). There was a significantly higher acceptance rate for trials providing active treatment in every arm 98 (80.6%) compared with those trials with a no treatment arm 46 (60.5%), χ2test P = 0.003. The study outlines a number of factors that appear to influence a patient’s decision to accept or decline entry into an RCT of cancer therapy. An important factor is whether or not the trial offers active treatment in all arms of the study. Communication that promotes trust and confidence in the doctor is also a powerful motivating influence. © 2000 Cancer Research Campaig

    Assessment right atrial thrombus by real-time three dimensional transthoracic echocardiography in patient with dilated cardiomyopathy

    Get PDF
    We report a case of a 52-year-old patient with dilated cardiomyopathy who presented with worsening heart failure. Two-dimensional transthoracic echocardiography and real-time three dimensional transthoracic echocardiography showed severe dilated cardiac chambers, impaired ejection fraction and a mobile right atrial thrombus 2.6 × 1.0 cm in size, traversing the right atrial cavity during the whole cardiac cycle. After one week therapeutic anticoagulation, echocardiography confirmed no evidence of residual thrombus

    Coupling models of cattle and farms with models of badgers for predicting the dynamics of bovine tuberculosis (TB)

    Get PDF
    Bovine TB is a major problem for the agricultural industry in several countries. TB can be contracted and spread by species other than cattle and this can cause a problem for disease control. In the UK and Ireland, badgers are a recognised reservoir of infection and there has been substantial discussion about potential control strategies. We present a coupling of individual based models of bovine TB in badgers and cattle, which aims to capture the key details of the natural history of the disease and of both species at approximately county scale. The model is spatially explicit it follows a very large number of cattle and badgers on a different grid size for each species and includes also winter housing. We show that the model can replicate the reported dynamics of both cattle and badger populations as well as the increasing prevalence of the disease in cattle. Parameter space used as input in simulations was swept out using Latin hypercube sampling and sensitivity analysis to model outputs was conducted using mixed effect models. By exploring a large and computationally intensive parameter space we show that of the available control strategies it is the frequency of TB testing and whether or not winter housing is practised that have the most significant effects on the number of infected cattle, with the effect of winter housing becoming stronger as farm size increases. Whether badgers were culled or not explained about 5%, while the accuracy of the test employed to detect infected cattle explained less than 3% of the variance in the number of infected cattle

    Barriers and opportunities for evidence-based health service planning: the example of developing a Decision Analytic Model to plan services for sexually transmitted infections in the UK

    Get PDF
    Decision Analytic Models (DAMs) are established means of evidence-synthesis to differentiate between health interventions. They have mainly been used to inform clinical decisions and health technology assessment at the national level, yet could also inform local health service planning. For this, a DAM must take into account the needs of the local population, but also the needs of those planning its services. Drawing on our experiences from stakeholder consultations, where we presented the potential utility of a DAM for planning local health services for sexually transmitted infections (STIs) in the UK, and the evidence it could use to inform decisions regarding different combinations of service provision, in terms of their costs, cost-effectiveness, and public health outcomes, we discuss the barriers perceived by stakeholders to the use of DAMs to inform service planning for local populations, including (1) a tension between individual and population perspectives; (2) reductionism; and (3) a lack of transparency regarding models, their assumptions, and the motivations of those generating models

    Considering the role of cognitive control in expert performance

    Get PDF
    © 2014, Springer Science+Business Media Dordrecht. Dreyfus and Dreyfus’ (1986) influential phenomenological analysis of skill acquisition proposes that expert performance is guided by non-cognitive responses which are fast, effortless and apparently intuitive in nature. Although this model has been criticised (e.g., by Breivik Journal of Philosophy of Sport, 34, 116–134 2007, Journal of the Philosophy of Sport, 40, 85–106 2013; Eriksen 2010; Montero Inquiry:An interdisciplinary Journal of Philosophy, 53, 105–122 2010; Montero and Evans 2011) for over-emphasising the role that intuition plays in facilitating skilled performance, it does recognise that on occasions (e.g., when performance goes awry for some reason) a form of ‘detached deliberative rationality’ may be used by experts to improve their performance. However, Dreyfus and Dreyfus (1986) see no role for calculative problem solving or deliberation (i.e., drawing on rules or mental representations) when performance is going well. In the current paper, we draw on empirical evidence, insights from athletes, and phenomenological description to argue that ‘continuous improvement’ (i.e., the phenomenon whereby certain skilled performers appear to be capable of increasing their proficiency even though they are already experts; Toner and Moran 2014) among experts is mediated by cognitive (or executive) control in three distinct sporting situations (i.e., in training, during pre-performance routines, and while engaged in on-line skill execution). We conclude by arguing that Sutton et al. Journal of the British Society for Phenomenology, 42, 78–103 (2011) ‘applying intelligence to the reflexes’ (AIR) approach may help to elucidate the process by which expert performers achieve continuous improvement through analytical/mindful behaviour during training and competition

    Transport of Explosive Residue Surrogates in Saturated Porous Media

    Get PDF
    Department of Defense operational ranges may become contaminated by particles of explosives residues (ER) as a result of low-order detonations of munitions. The goal of this study was to determine the extent to which particles of ER could migrate through columns of sandy sediment, representing model aquifer materials. Transport experiments were conducted in saturated columns (2 × 20 cm) packed with different grain sizes of clean sand or glass beads. Fine particles (approximately 2 to 50 μm) of 2,6-dinitrotoluene (DNT) were used as a surrogate for ER. DNT particles were applied to the top 1 cm of sand or beads in the columns, and the columns were subsequently leached with artificial groundwater solutions. DNT migration occurred as both dissolved and particulate phases. Concentration differences between unfiltered and filtered samples indicate that particulate DNT accounted for up to 41% of the mass recovered in effluent samples. Proportionally, more particulate than dissolved DNT was recovered in effluent solutions from columns with larger grain sizes, while total concentrations of DNT in effluent were inversely related to grain size. Of the total DNT mass applied to the uppermost layer of the column, <3% was recovered in the effluent with the bulk remaining in the top 2 cm of the column. Our results suggest there is some potential for subsurface migration of ER particles and that most of the particles will be retained over relatively short transport distances

    Assessment of learning curves in complex surgical interventions: a consecutive case-series study

    Get PDF
    Background: Surgical interventions are complex, which complicates their rigorous assessment through randomised clinical trials. An important component of complexity relates to surgeon experience and the rate at which the required level of skill is achieved, known as the learning curve. There is considerable evidence that operator performance for surgical innovations will change with increasing experience. Such learning effects complicate evaluations; the start of the trial might be delayed, resulting in loss of surgeon equipoise or, if an assessment is undertaken before performance has stabilised, the true impact of the intervention may be distorted. Methods: Formal estimation of learning parameters is necessary to characterise the learning curve, model its evolution and adjust for its presence during assessment. Current methods are either descriptive or model the learning curve through three main features: the initial skill level, the learning rate and the final skill level achieved. We introduce a fourth characterising feature, the duration of the learning period, which provides an estimate of the point at which learning has stabilised. We propose a two-phase model to estimate formally all four learning curve features. Results: We demonstrate that the two-phase model can be used to estimate the end of the learning period by incorporating a parameter for estimating the duration of learning. This is achieved by breaking down the model into a phase describing the learning period and one describing cases after the final skill level is reached, with the break point representing the length of learning. We illustrate the method using cardiac surgery data. Conclusions: This modelling extension is useful as it provides a measure of the potential cost of learning an intervention and enables statisticians to accommodate cases undertaken during the learning phase and assess the intervention after the optimal skill level is reached. The limitations of the method and implications for the optimal timing of a definitive randomised controlled trial are also discussed
    corecore