Prevalence of axial spondyloarthritis in patients with acute anterior uveitis: A cross-sectional study utilising MRI

Objective: Acute anterior uveitis (AAU) is the most common extra-articular manifestation of axial spondyloarthritis (axSpA). In this study, patients presenting with AAU were evaluated clinically and with MRI in order to estimate the prevalence of axSpA. Methods: Consecutive patients presenting to a university teaching hospital between February 2014 and March 2015 with AAU were invited to participate. Those with a history of chronic back pain (CBP) beginning <45 years were evaluated clinically and with MRI of thoracolumbar spine and sacroiliac joints. Results: Of 366 patients with AAU, 57 had a pre-existing diagnosis of axSpA; 77 others fulfilled the study eligibility criteria and 73 (95%) completed the study. Seventeen patients (23.3%) were diagnosed with axSpA by an experienced rheumatologist; of these, eight were human leucocyte antigen-B27 negative. Including those with a previous diagnosis, this equates to a minimum axSpA prevalence of 20.2%; one-quarter of patients were previously undiagnosed. Conclusion: This is the first study to actively search for the presence of axSpA in unselected patients presenting with AAU utilising MRI as an essential part of the assessment. There is a significant burden of undiagnosed axSpA in patients with AAU, but there does not appear to be a simple mechanism for screening. We recommend that ophthalmologists refer all patients with AAU with CBP, onset <45 years, to rheumatology for further evaluation

Spreading speeds for plant populations in landscapes with low environmental variation

Characterising the spread of biological populations is crucial in responding to both biological invasions and the shifting of habitat under climate change. Spreading speeds can be studied through mathematical models such as the discrete-time integro-difference equation (IDE) framework. The usual approach in implementing IDE models has been to ignore spatial variation in the demographic and dispersal parameters and to assume that these are spatially homogeneous. On the other hand, real landscapes are rarely spatially uniform with environmental variation being very important in determining biological spread. This raises the question of under what circumstances spatial structure need not be modelled explicitly. Recent work has shown that spatial variation can be ignored for the specific case where the scale of landscape variation is much smaller than the spreading population׳s dispersal scale. We consider more general types of landscape, where the spatial scales of environmental variation are arbitrarily large, but the maximum change in environmental parameters is relatively small. We find that the difference between the wave-speeds of populations spreading in a spatially structured periodic landscape and its homogenisation is, in general, proportional to ϵ2, where ϵ governs the degree of environmental variation. For stochastically generated landscapes we numerically demonstrate that the error decays faster than ϵ. In both cases, this means that for sufficiently small ϵ, the homogeneous approximation is better than might be expected. Hence, in many situations, the precise details of the landscape can be ignored in favour of spatially homogeneous parameters. This means that field ecologists can use the homogeneous IDE as a relatively simple modelling tool – in terms of both measuring parameter values and doing the modelling itself. However, as ϵ increases, this homogeneous approximation loses its accuracy. The change in wave-speed due to the extrinsic (landscape) variation can be positive or negative, which is in contrast to the reduction in wave-speed caused by intrinsic stochasticity. To deal with the loss of accuracy as ϵ increases, we formulate a second-order approximation to the wave-speed for periodic landscapes and compare both approximations against the results of numerical simulation and show that they are both accurate for the range of landscapes considered

Speeding up the simulation of population spread models

1. Simulating spatially explicit population models to predict population spread allows environmental managers to make better-informed decisions. Accurate simulation requires high spatial resolution, which, using existing techniques, can require prohibitively large amounts of computational resources (RAM, CPU, etc). 2. We developed and implemented a novel algorithm for the simulation of integro-difference equations (IDEs) modelling population spread, including stage structure, which uses adaptive mesh refinement. 3. We measured the accuracy of the adaptive algorithm by comparing the results of simulations using the adaptive and a standard non-adaptive algorithm. The relative error of the population's spatial extent was low (<0·05) for a range of parameter values. Comparing efficiency, we found that our algorithm used up to 10 times less CPU time and RAM than the non-adaptive algorithm. 4. Our approach provides large improvements in efficiency without significant loss of accuracy, so it enables faster simulation of IDEs and simulation at scales and at resolutions that have not been previously feasible. As an example, we simulate the spread of a hypothetical species over the UK at a resolution of 25 m. We provide our implementation of the algorithm as a user-friendly executable application

Multi-sensor classification of tennis strokes

In this work, we investigate tennis stroke recognition using a single inertial measuring unit attached to a player’s forearm during a competitive match. This paper evaluates the best approach for stroke detection using either accelerometers, gyroscopes or magnetometers, which are embedded into the inertial measuring unit. This work concludes what is the optimal training data set for stroke classification and proves that classifiers can perform well when tested on players who were not used to train the classifier. This work provides a significant step forward for our overall goal, which is to develop next generation sports coaching tools using both inertial and visual sensors in an instrumented indoor sporting environment

APCR, factor V gene known and novel SNPs and adverse pregnancy outcomes in an Irish cohort of pregnant women

<p>Abstract</p> <p>Background</p> <p>Activated Protein C Resistance (APCR), a poor anticoagulant response of APC in haemostasis, is the commonest heritable thrombophilia. Adverse outcomes during pregnancy have been linked to APCR. This study determined the frequency of APCR, factor V gene known and novel SNPs and adverse outcomes in a group of pregnant women.</p> <p>Methods</p> <p>Blood samples collected from 907 pregnant women were tested using the Coatest^®Classic and Modified functional haematological tests to establish the frequency of APCR. PCR-Restriction Enzyme Analysis (PCR-REA), PCR-DNA probe hybridisation analysis and DNA sequencing were used for molecular screening of known mutations in the factor V gene in subjects determined to have APCR based on the Coatest^®Classic and/or Modified functional haematological tests. Glycosylase Mediated Polymorphism Detection (GMPD), a SNP screening technique and DNA sequencing, were used to identify SNPs in the factor V gene of 5 APCR subjects.</p> <p>Results</p> <p>Sixteen percent of the study group had an APCR phenotype. Factor V Leiden (FVL), FV Cambridge, and haplotype (H) R2 alleles were identified in this group. Thirty-three SNPs; 9 silent SNPs and 24 missense SNPs, of which 20 SNPs were novel, were identified in the 5 APCR subjects. Adverse pregnancy outcomes were found at a frequency of 35% in the group with APCR based on Classic Coatest^®test only and at 45% in the group with APCR based on the Modified Coatest^®test. Forty-eight percent of subjects with FVL had adverse outcomes while in the group of subjects with no FVL, adverse outcomes occurred at a frequency of 37%.</p> <p>Conclusions</p> <p>Known mutations and novel SNPs in the factor V gene were identified in the study cohort determined to have APCR in pregnancy. Further studies are required to investigate the contribution of these novel SNPs to the APCR phenotype. Adverse outcomes including early pregnancy loss (EPL), preeclampsia (PET) and intrauterine growth restriction (IGUR) were not significantly more frequent in subjects with APCR compared to normal pregnant women however Pregnancy induced hypertension (PIH) was found to be associated with FVL in our study group.</p

Powers of 10: seeking ‘sweet spots’ for rapid climate and sustainability actions between individual and global scales

Achieving the goals of the Paris Agreement and related sustainability initiatives will require halving of global greenhouse gas emissions each decade from now on through to 2050, when net zero emissions should be achieved. To reach such significant reductions requires a rapid and strategic scaling of existing and emerging technologies and practices, coupled with economic and social transformations and novel governance solutions. Here we present a new ‘Powers of 10’ (P10) logarithmic framework and demonstrate its potential as a practical tool for decision makers and change agents at multiple scales to inform and catalyze engagement and actions, complementing and adding nuance to existing frameworks. P10 assists in identifying the suitable cohorts and cohort ranges for rapidly deploying climate and sustainability actions between a single individual and the globally projected ∼ 10 billion persons by 2050. Applying a robust dataset of climate solutions from Project Drawdown’s Plausible scenario that could cumulatively reduce greenhouse gas emissions by 1051 gigatons (Gt) against a reference scenario (2190 Gt) between 2020 and 2050, we seek to identify a ‘sweet spot’ where these climate and sustainability actions are suitably scaled. We suggest that prioritizing the analyzed climate actions between community and urban scales, where global and local converge, can help catalyze and enhance individual, household and local practices, and support national and international policies and finances for rapid sustainability transformations

Angiogenic oligosaccharides of hyaluronan induce multiple signaling pathways affecting vascular endothelial cell mitogenic and wound healing responses

Hyaluronan (HA) is a large nonsulfated glycosaminoglycan and an important regulator of angiogenesis, in particular, the growth and migration of vascular endothelial cells. We have identified some of the key intermediates responsible for induction of mitogenesis and wound recovery. Treatment of bovine aortic endothelial cells with oligosaccharides of hyaluronan (o-HA) resulted in rapid tyrosine phosphorylation and plasma membrane translocation of phospholipase C1 (PLC1). Cytoplasmic loading with inhibitory antibodies to PLC1, G, and Gi/o/t/z inhibited activation of extracellular-regulated kinase 1/2 (ERK1/2). Treatment with the Gi/o inhibitor, pertussis toxin, reduced o-HA-induced PLC1 tyrosine phosphorylation, protein kinase C (PKC) and 1/2 membrane translocation, ERK1/2 activation, mitogenesis, and wound recovery, suggesting a mechanism for o-HA-induced angiogenesis through G-proteins, PLC1, and PKC. In particular, we demonstrated a possible role for PKC in mitogenesis and PKC1/2 in wound recovery. Using antisense oligonucleotides and the Ras farnesylation inhibitor FTI-277, we showed that o-HA-induced bovine aortic endothelial cell proliferation, wound recovery, and ERK1/2 activation were also partially dependent on Ras activation, and that o-HA-stimulated tyrosine phosphorylation of the adapter protein Shc, as well as its association with Sos1. Binding of Src to Shc was required for its activation and for Ras-dependent activation of ERK1/2, cell proliferation, and wound recovery. Neither Src nor Ras activation was inhibited by pertussis toxin, suggesting that their activation was independent of heterotrimeric G-proteins. However, the specific Src kinase inhibitor PP2 inhibited G subunit co-precipitation with PLC1, suggesting a possible role for Src in activation of PLC1 and interaction between two distinct o-HA-induced signaling pathways

A smart wireless inertial measurement unit system: simplifying & encouraging usage of WIMU technology

Wireless Inertial Measurement Units (WIMUs) combine motion sensing, processing & communications functionsin a single device. Data gathered using these sensors has the potential to be converted into high quality motion data. By outfitting a subject with multiple WIMUs full motion data can begathered. With a potential cost of ownership several orders of magnitude less than traditional camera based motion capture, WIMU systems have potential to be crucially important in supplementing or replacing traditional motion capture and opening up entirely new application areas and potential markets particularly in the rehabilitative, sports & at-home healthcarespaces. Currently WIMUs are underutilized in these areas. A major barrier to adoption is perceived complexity. Sample rates, sensor types & dynamic sensor ranges may need to be adjusted on multiple axes for each device depending on the scenario. As such we present an advanced WIMU in conjunction with a Smart WIMU system to simplify this aspect with 3 usage modes: Manual, Intelligent and Autonomous. Attendees will be able to compare the 3 different modes and see the effects of good andbad set-ups on the quality of data gathered in real time

A medical study on wireless inertial measurement technology as a tool for identifying patients at risk of death or imminent clinical deterioration

This paper provides a system description and preliminary results for an ongoing clinical study currently being carried out at the Mid-Western Regional Hospital, Nenagh, Ireland. The goal of the trial is to determine if wireless inertial measurement technology can be employed to identify elderly patients at risk of death or imminent clinical deterioration. The system measures cumulative movement and provides a score that will help provide a robust early warning to clinical staff of clinical deterioration. In addition the study examines some of the logistical barriers to the adoption of wearable wireless technology in front-line medical care

WIMU instrumentation of skeleton "ASSASSIN" trainer & sled

Skeleton is a high‐speed Winter Olympic sport performed on the same twisting, downhill ice tracks used for Bobsleigh & Luge. The single rider sprints and pushes their sled for 20‐30m on a level start section before loading and going through a twisting course of over 1km, at speeds up to 140km/h, experiencing up to 5g. In competition, the top athletes can be within a fraction of a second of each other. The initial short pushing period is believed to be critical to overall performance but it is not well understood. A collaborative project between University of Bath, UK Sport and Tyndall National Institute is instrumenting skeleton athletes, training equipment and test tracks with Tyndall’s Wireless Inertial Measurement Unit technology in order to investigate and improve understanding of this phase of a skeleton run. It is hoped this will lead to improved training regimes and better performance of such elite, Olympic level athletes. This work presents an initial look at the system as implemented and data recorded