10,393 research outputs found

    A positive SeHCAT test results in fewer subsequent investigations in patients with chronic diarrhoea.

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    Chronic diarrhoea is a common condition, resulting from a number of different disorders. Bile acid diarrhoea, occurring in about a third of these patients, is often undiagnosed. We hypothesised that a positive diagnosis of bile acid diarrhoea would reduce the need for subsequent investigations for alternative diagnoses. METHODS: Patients previously recruited to a study of chronic diarrhoea who had selenium homocholic acid taurine (SeHCAT) testing and subsequent follow-up at our institution were identified. In a retrospective analysis, the numbers of defined investigations undertaken from the first 3 months after SeHCAT in the following 5 years were compared. RESULTS: 90 patients were identified with primary bile acid diarrhoea (SeHCAT retention 15%, n=54). Follow-up had been performed on 29 and 39 subjects, respectively, with no differences in previous investigations or the last contact date. In the follow-up period, the proportions of these patients who had undergone endoscopic procedures (gastroscopy, colonoscopy and sigmoidoscopy) were the same. However, there was a higher proportion of patients in the SeHCAT-negative group who had other investigations, including imaging, physiological tests and blood tests (p=0.037). The use of cross-sectional imaging was significantly higher in this group (p=0.015) with greater proportions having CT (0.44 vs 0.10) and MRI (0.26 vs 0.07). Ultrasound use and the number of blood tests were higher in the SeHCAT-negative group whereas the SeHCAT-positive group attended more clinic appointments (p=0.013). CONCLUSION: A positive diagnosis of bile acid diarrhoea, made by a SeHCAT test, resulted in reduced use of diagnostic investigations over the subsequent 5 years

    Stochastic expectation propagation

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    Expectation propagation (EP) is a deterministic approximation algorithm that is often used to perform approximate Bayesian parameter learning. EP approximates the full intractable posterior distribution through a set of local approximations that are iteratively refined for each datapoint. EP can offer analytic and computational advantages over other approximations, such as Variational Inference (VI), and is the method of choice for a number of models. The local nature of EP appears to make it an ideal candidate for performing Bayesian learning on large models in large-scale dataset settings. However, EP has a crucial limitation in this context: the number of approximating factors needs to increase with the number of data-points, N, which often entails a prohibitively large memory overhead. This paper presents an extension to EP, called stochastic expectation propagation (SEP), that maintains a global posterior approximation (like VI) but updates it in a local way (like EP). Experiments on a number of canonical learning problems using synthetic and real-world datasets indicate that SEP performs almost as well as full EP, but reduces the memory consumption by a factor of NN. SEP is therefore ideally suited to performing approximate Bayesian learning in the large model, large dataset setting

    Targeted β-Phase Formation in Poly(fluorene)-Ureasil Grafted Organic-Inorganic Hybrids

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    © 2017 American Chemical Society. The development of synthetic strategies to control the molecular organization (and inherently linked optoelectronic properties) of conjugated polymers is critical for the development of efficient light-emitting devices. Here, we report a facile route using sol-gel chemistry to promote the formation of the β-phase through the covalent-grafting of poly[(9,9-dioctylfluorene)-co-(9,9-bis(8-hydroxyoctyl)fluorene)] (PFO-OH) to poly(oxyalkylene)/siloxane hybrids known as ureasils, due to the urea linkages binding the organic and inorganic components. Although grafting occurs within the siliceous domains, the degree of branching of the organic backbone determines the packing of the PFO-OH chains within the ureasil framework. Moreover, photoluminescence studies indicate that physical confinement also plays a key role in promoting the evolution of the β-phase of PFO-OH as the sol-gel transition proceeds. Spectroscopic and structural analyses reveal that dibranched ureasils promote linear packing of the PFO-OH chains, while tribranched ureasils exhibit a more open, distorted structure that restricts the packing efficacy and reduces the number of covalent anchorages. These results indicate that the organic-inorganic hybrid structure induces distinct levels of β-phase formation and that covalent grafting is a versatile approach to design novel poly(fluorene) hybrid materials with tailored optical properties

    Seeing through the Effects of Crustal Assimilation to Assess the Source Composition beneath the Southern Lesser Antilles Arc

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    Assessing the impact of crustal assimilation on the composition of oceanic arc lavas is important if source composition is to be correctly interpreted. This is particularly the case in the Lesser Antilles where lavas encompass a very large range in radiogenic isotope compositions. Here we present new 176Hf/177Hf and trace element data for a suite of samples from St Lucia in the southern Lesser Antilles arc where assimilation of sediments located within the arc crust has been shown to influence significantly Sr–Nd–Pb isotope compositions. We show that a high rate of assimilation (r = 0·8) of sediment is responsible for the co-variation of Th/Th*, La/Sm, 87Sr/86Sr, 206/207/208Pb/204Pb, 143Nd/144Nd and 176Hf/177Hf towards extreme ‘continental’ compositions. Lavas that escaped sediment assimilation have a typical oceanic arc signature and provide the best indication of mantle source characteristics beneath St Lucia. They display similar Ba/Th, La/Sm and Nd isotopic compositions to lavas further north in the arc, but with slightly more radiogenic Sr and Pb. Addition of less than 2% of local bulk subducting sediment, or less than 3·5% of sediment partial melt or fluid, to the mantle wedge can explain these compositions; these estimates are similar to those previously proposed for the northern arc. After correction for the effects of sediment assimilation, the St Lucia lavas have only slightly more radiogenic Pb and Sr isotope signatures compared with the northern islands; this can be attributed to differences in the isotopic composition of the local subducting sediment rather than to greater sediment input, as has been previously proposed. Comparison of St Lucia with the other southern Lesser Antilles islands suggests that similar mantle source compositions exist beneath Martinique, St Vincent and perhaps Bequia, whereas a more ‘continental’ source might characterize Ile de Caille, Kick ’em Jenny and Grenada

    Deep Gaussian processes for regression using approximate expectation propagation

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    Deep Gaussian processes (DGPs) are multi-layer hierarchical generalisations of Gaussian processes (GPs) and are formally equivalent to neural networks with multiple, infinitely wide hidden layers. DGPs are nonparametric probabilistic models and as such are arguably more flexible, have a greater capacity to generalise, and provide better calibrated uncertainty estimates than alternative deep models. This paper develops a new approximate Bayesian learning scheme that enables DGPs to be applied to a range of medium to large scale regression problems for the first time. The new method uses an approximate Expectation Propagation procedure and a novel and efficient extension of the probabilistic backpropagation algorithm for learning. We evaluate the new method for non-linear regression on eleven real-world datasets, showing that it always outperforms GP regression and is almost always better than state-of-the-art deterministic and sampling-based approximate inference methods for Bayesian neural networks. As a by-product, this work provides a comprehensive analysis of six approximate Bayesian methods for training neural networks

    Forefoot pathology in rheumatoid arthritis identified with ultrasound may not localise to areas of highest pressure: cohort observations at baseline and twelve months

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    BackgroundPlantar pressures are commonly used as clinical measures, especially to determine optimum foot orthotic design. In rheumatoid arthritis (RA) high plantar foot pressures have been linked to metatarsophalangeal (MTP) joint radiological erosion scores. However, the sensitivity of foot pressure measurement to soft tissue pathology within the foot is unknown. The aim of this study was to observe plantar foot pressures and forefoot soft tissue pathology in patients who have RA.Methods A total of 114 patients with established RA (1987 ACR criteria) and 50 healthy volunteers were assessed at baseline. All RA participants returned for reassessment at twelve months. Interface foot-shoe plantar pressures were recorded using an F-Scan® system. The presence of forefoot soft tissue pathology was assessed using a DIASUS musculoskeletal ultrasound (US) system. Chi-square analyses and independent t-tests were used to determine statistical differences between baseline and twelve months. Pearson’s correlation coefficient was used to determine interrelationships between soft tissue pathology and foot pressures.ResultsAt baseline, RA patients had a significantly higher peak foot pressures compared to healthy participants and peak pressures were located in the medial aspect of the forefoot in both groups. In contrast, RA participants had US detectable soft tissue pathology in the lateral aspect of the forefoot. Analysis of person specific data suggests that there are considerable variations over time with more than half the RA cohort having unstable presence of US detectable forefoot soft tissue pathology. Findings also indicated that, over time, changes in US detectable soft tissue pathology are out of phase with changes in foot-shoe interface pressures both temporally and spatially.Conclusions We found that US detectable forefoot soft tissue pathology may be unrelated to peak forefoot pressures and suggest that patients with RA may biomechanically adapt to soft tissue forefoot pathology. In addition, we have observed that, in patients with RA, interface foot-shoe pressures and the presence of US detectable forefoot pathology may vary substantially over time. This has implications for clinical strategies that aim to offload peak plantar pressures

    Reinvestigating the Photoprotection Properties of a Mycosporine Amino Acid Motif

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    With the growing concern regarding commercially available ultraviolet (UV) filters damaging the environment, there is an urgent need to discover new UV filters. A family of molecules called mycosporines and mycosporine-like amino acids (referred to as MAAs collectively) are synthesized by cyanobacteria, fungi and algae and act as the natural UV filters for these organisms. Mycosporines are formed of a cyclohexenone core structure while mycosporine-like amino acids are formed of a cyclohexenimine core structure. To better understand the photoprotection properties of MAAs, we implement a bottom-up approach by first studying a simple analog of an MAA, 3-aminocyclohex-2-en-1-one (ACyO). Previous experimental studies on ACyO using transient electronic absorption spectroscopy (TEAS) suggest that upon photoexcitation, ACyO becomes trapped in the minimum of an S1 state, which persists for extended time delays (>2.5 ns). However, these studies were unable to establish the extent of electronic ground state recovery of ACyO within 2.5 ns due to experimental constraints. In the present studies, we have implemented transient vibrational absorption spectroscopy (as well as complementary TEAS) with Fourier transform infrared spectroscopy and density functional theory to establish the extent of electronic ground state recovery of ACyO within this time window. We show that by 1.8 ns, there is >75% electronic ground state recovery of ACyO, with the remaining percentage likely persisting in the electronic excited state. Long-term irradiation studies on ACyO have shown that a small percentage degrades after 2 h of irradiation, plausibly due to some of the aforementioned trapped ACyO going on to form a photoproduct. Collectively, these studies imply that a base building block of MAAs already displays characteristics of an effective UV filter

    Deterministic variational inference for robust Bayesian neural networks

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    Bayesian neural networks (BNNs) hold great promise as a flexible and principled solution to deal with uncertainty when learning from finite data. Among approaches to realize probabilistic inference in deep neural networks, variational Bayes (VB) is theoretically grounded, generally applicable, and computationally efficient. With wide recognition of potential advantages, why is it that variational Bayes has seen very limited practical use for BNNs in real applications? We argue that variational inference in neural networks is fragile: successful implementations require careful initialization and tuning of prior variances, as well as controlling the variance of Monte Carlo gradient estimates. We provide two innovations that aim to turn VB into a robust inference tool for Bayesian neural networks: first, we introduce a novel deterministic method to approximate moments in neural networks, eliminating gradient variance; second, we introduce a hierarchical prior for parameters and a novel Empirical Bayes procedure for automatically selecting prior variances. Combining these two innovations, the resulting method is highly efficient and robust. On the application of heteroscedastic regression we demonstrate good predictive performance over alternative approaches
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