Echocardiography service provision in New Zealand: capacity modelling the cardiac sonographer workforce

Aim: Regional disparity in both utilisation and the cardiac sonographer workforce has previously been identified. We sought to model the capacity of the cardiac sonographer workforce at a national and District Health Board level to better understand these regional differences. Method: In 2013, surveys were distributed to 18 hospitals who employ cardiac sonographers (return rate 100%). Questions related to cardiac sonographer demographics, echo utilisation and workflow. Actual clinical capacity was calculated from scan duration and annual scan volumes. New Zealand national actual capacity was compared to predicted capacity from three international models. Potential clinical capacity was calculated from the workforce size in fulltime equivalent (FTE) and clinical availability. Results: In New Zealand, scan duration and population-based clinical capacity varies between centres. The New Zealand capacity is similar to the UK 30:70 model, and consistently less than the US model for all scan types. There are marked regional differences in potential versus actual capacity, with 10/16 DHBs demonstrating excess potential capacity. Conclusion: There is regional disparity in the capacity of the cardiac sonographer workforce, which appears to be strongly related to scan duration. Workforce capacity modelling should be used with need and demand modelling to plan adequate levels of service provision

A solar powered handheld plasma source for microbial decontamination applications

A fully portable atmospheric pressure air plasma system is reported to be suitable for the microbial decontamination of both surfaces and liquids. The device operates in quiescent air, and includes an integrated battery which is charged from a solar cell and weighs less than 750 g, making it highly amenable for a wide variety of applications beyond the laboratory. Using particle imaging velocimetry to visualise air flows around the device, the geometric configuration of the plasma generating electrodes was enhanced to induce a gas flow on the order of 0.5 m s-1 directed towards a sample placed downstream, thus improving the transport of plasma generated reactive species to the sample. The microbial decontamination efficiency of the system was assessed using potable water samples inoculated with common waterborne organisms Escherichia coli and Pseudomonas fluorescens. The reduction in the number of microorganisms was found to be in the range of 2-8 log and was strongly dependent on the plasma generation conditions

The influence of clouds on radical concentrations: observations and modelling studies of HOx during the Hill Cap Cloud Thuringia (HCCT) campaign in 2010

The potential for chemistry occurring in cloud droplets to impact atmospheric composition has been known for some time. However, the lack of direct observations and uncertainty in the magnitude of these reactions led to this area being overlooked in most chemistry transport models. Here we present observations from Mt Schmücke, Germany, of the HO2 radical made alongside a suite of cloud measurements. HO2 concentrations were depleted in-cloud by up to 90% with the rate of heterogeneous loss of HO2 to clouds necessary to bring model and measurements into agreement, demonstrating a dependence on droplet surface area and pH. This provides the first observationally derived assessment for the uptake coefficient of HO2 to cloud droplets and was found to be in good agreement with theoretically derived parameterisations. Global model simulations, including this cloud uptake, showed impacts on the oxidising capacity of the troposphere that depended critically on whether the HO2 uptake leads to production of H2O2 or H2O

Fundamental oxidation processes in the remote marine atmosphere investigated using the NO–NO₂–O₃ photostationary state

The photostationary state (PSS) equilibrium between NO and NO₂ is reached within minutes in the atmosphere and can be described by the PSS parameter, φ. Deviations from expected values of φ have previously been used to infer missing oxidants in diverse locations, from highly polluted regions to the extremely clean conditions observed in the remote marine boundary layer (MBL), and have been interpreted as missing understanding of fundamental photochemistry. Here, contrary to these previous observations, we observe good agreement between PSS-derived NO₂ ([NO₂]PSS ext.), calculated from measured NO, O₃, and jNO₂ and photochemical box model predictions of peroxy radicals (RO₂ and Hv), and observed NO₂ ([NO₂]Obs.) in extremely clean air containing low levels of CO ( 100 ppbV), we observed higher levels of NO₂ than inferred from the PSS, with [NO₂]Obs.  [NO₂]PSS ext. of 1.12–1.68 (25th–75th percentile), implying underestimation of RO₂ radicals by 18.5–104 pptV. Potential NO₂measurement artefacts have to be carefully considered when comparing PSS-derived NO₂ to observed NO₂, but we show that the NO₂ artefact required to explain the deviation would have to be ∼ 4 times greater than the maximum calculated from known interferences. If the additional RO2 radicals inferred from the PSS convert NO to NO₂ with a reaction rate equivalent to that of methyl peroxy radicals (CH₃O₂), then the calculated net ozone production rate (NOPR, ppbV h¯¹) including these additional oxidants is similar to the average change in O₃ observed, within estimated uncertainties, once halogen oxide chemistry is accounted for. This implies that such additional peroxy radicals cannot be excluded as a missing oxidant in clean marine air containing aged pollution and that modelled RO₂ concentrations are significantly underestimated under these conditions

Identification of plasma proteins relating to brain neurodegeneration and vascular pathology in cognitively normal individuals

This project was funded by DPUK through MRC (grant no. MR/L023784/2) and the UK Medical Research Council Award to the University of Oxford (grant no. MC_PC_17215). L.S is funded by the Virtual Brain Cloud from European comission (grant no. H2020-SC1-DTH-2018-1). C.R.B is funded by National Institutes of Health (NIH) research grant R01AG054628. S.R.C is funded by National Institutes of Health (NIH) research grant (R01AG054628), Medical Research Council (MR/R024065/1), Age UK and Economic and Social Research Council. R.E.M. was supported by Alzheimer's Research UK major project grant ARUKPG2017B-10. C.H was supported by an MRC Human Genetics Unit programme grant “Quantitative traits in health and disease” (U.MC_UU_00007/10). H.C.W received funding from Wellcome Trust. J.W is funded by TauRx pharmaceuticals Ltd and received Educational grant from Biogen paid to Alzheimer Scotland/Brain Health Scotland. G.W received GRAMPIAN UNIVERSITY HOSPITALS NHS TRUST, Scottish Government—Chief Scientist Office, ROLAND SUTTON ACADEMIC TRUST, Medical Research Scotland, Sutton Academic Trust and ROLAND SUTTON ACADEMIC TRUST. J.M.W received Wellcome Trust Strategic Award, MRC UK Dementia Research Institute and MRC project grants, Fondation Leducq, Stroke Association, British Heart Foundation, Alzheimer Society, and the European Union H2020 PHC-03-15 SVDs@Target grant (666881). D.S received MRC (MR/S010351/1), MRC (MR/W002388/1) and MRC (MR/W002566/1). A.M is supported by the Wellcome Trust (104036/Z/14/Z, 216767/Z/19/Z, 220857/Z/20/Z) and UKRI MRC (MC_PC_17209, MR/S035818/1). This work is part of a project that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 847776. In addition, A.M has received grant support from The Sackler Trust, outside of the work presented. N.B received grant to institution from GSK as part of GSK/Oxford FxG initiative. A.N.H received John Black Charitable Fund-Rosetrees, H2020 funding from European Comission-Project Virtual Brain Cloud, AI for the Discovery of new therapies in Parkinson's (A2926), Rising Start Initiative—stage 2, Brain-Gut Microbiome (Call: PAR-18-296; Award ID: 1U19AG063744-01), Gut-liver-brain biochemical axis in Alzheimer's disease (5RF1AG057452-01), Virtual Brain Cloud (Call: H2020-SC1-DTH- 2018-1; Grant agreement ID: 826421). Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates (CZD/16/6) and the Scottish Funding Council (HR03006) and is currently supported by the Wellcome Trust (216767/Z/19/Z). Genotyping of the GS:SFHS samples was carried out by the Genetics Core Laboratory at the Edinburgh Clinical Research Facility, University of Edinburgh, Scotland and was funded by the Medical Research Council UK and the Wellcome Trust (Wellcome Trust Strategic Award “STratifying Resilience and Depression Longitudinally” [STRADL] Reference 104036/Z/14/Z). We are grateful to all the families who took part; the general practitioners and the Scottish School of Primary Care for their help in recruiting them; and the whole Generation Scotland team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists, health-care assistants, and nurses.Peer reviewedPublisher PD

Environmental risk factors for dementia: a systematic review

Background - Dementia risk reduction is a major and growing public health priority. While certain modifiable risk factors for dementia have been identified, there remains a substantial proportion of unexplained risk. There is evidence that environmental risk factors may explain some of this risk. Thus, we present the first comprehensive systematic review of environmental risk factors for dementia. Methods - We searched the PubMed and Web of Science databases from their inception to January 2016, bibliographies of review articles, and articles related to publically available environmental data. Articles were included if they examined the association between an environmental risk factor and dementia. Studies with another outcome (for example, cognition), a physiological measure of the exposure, case studies, animal studies, and studies of nutrition were excluded. Data were extracted from individual studies which were, in turn, appraised for methodological quality. The strength and consistency of the overall evidence for each risk factor identified was assessed. Results - We screened 4784 studies and included 60 in the review. Risk factors were considered in six categories: air quality, toxic heavy metals, other metals, other trace elements, occupational-related exposures, and miscellaneous environmental factors. Few studies took a life course approach. There is at least moderate evidence implicating the following risk factors: air pollution; aluminium; silicon; selenium; pesticides; vitamin D deficiency; and electric and magnetic fields. Conclusions - Studies varied widely in size and quality and therefore we must be circumspect in our conclusions. Nevertheless, this extensive review suggests that future research could focus on a short list of environmental risk factors for dementia. Furthermore, further robust, longitudinal studies with repeated measures of environmental exposures are required to confirm these associations

A systematic review of associations between functional MRI activity and polygenic risk for schizophrenia and bipolar disorder

Genetic factors account for up to 80% of the liability for schizophrenia (SCZ) and bipolar disorder (BD). Genome-wide association studies have successfully identified several genes associated with increased risk for both disorders. This has allowed researchers to model the aggregate effect of genes associated with disease status and create a polygenic risk score (PGRS) for each individual. The interest in imaging genetics using PGRS has grown in recent years, with several studies now published. We have conducted a systematic review to examine the effects of PGRS of SCZ, BD and cross psychiatric disorders on brain function and connectivity using fMRI data. Results indicate that the effect of genetic load for SCZ and BD on brain function affects task-related recruitment, with frontal areas having a more prominent role, independent of task. Additionally, the results suggest that the polygenic architecture of psychotic disorders is not regionally confined but impacts on the task-dependent recruitment of multiple brain regions. Future imaging genetics studies with large samples, especially population studies, would be uniquely informative in mapping the spatial distribution of the genetic risk to psychiatric disorders on brain processes during various cognitive tasks and may lead to the discovery of biological pathways that could be crucial in mediating the link between genetic factors and alterations in brain networks

Ibrutinib for Relapsed / Refractory CLL: A UK and Ireland Analysis of Outcomes in 315 patients

In 2014, ibrutinib was made available for relapsed/refractory chronic lymphocytic leukaemia (CLL) patients. The UK CLL Forum collected data from UK/Ireland patients with a minimum of 1 year follow-up with pre-planned primary endpoints; the number of patients still on therapy at 1 year (Discontinuation Free Survival; DFS) and 1 year overall survival (OS). With a median 16 months follow-up, data on 315 patients demonstrated 1 year DFS of 73.7% and 1 year OS of 83.8%. Patients with better pre-treatment performance status (PS 0/1 vs 2+) had superior DFS (77.5% vs 61.3%;p14 days and had OS of 89.7%, while 26% of patients had dose reductions and 13% had temporary treatment breaks >14 days. We could not demonstrate a detrimental effect of dose reductions alone (1 year OS: 91.7%), but patients who had first year treatment breaks > 14 days, particularly permanent cessation of ibrutinib had both reduced 1 year OS (68.5%) and also a statistically significant excess mortality rate beyond one year. Although outcomes appear inferior to the RESONATE trial (1 year OS;90%: PFS;84%), this may partly reflect the inclusion of PS 2+ patients and that 17.5% of patients permanently discontinued ibrutinib due to an event other than disease progression

Facilitating arrhythmia simulation: the method of quantitative cellular automata modeling and parallel running

BACKGROUND: Many arrhythmias are triggered by abnormal electrical activity at the ionic channel and cell level, and then evolve spatio-temporally within the heart. To understand arrhythmias better and to diagnose them more precisely by their ECG waveforms, a whole-heart model is required to explore the association between the massively parallel activities at the channel/cell level and the integrative electrophysiological phenomena at organ level. METHODS: We have developed a method to build large-scale electrophysiological models by using extended cellular automata, and to run such models on a cluster of shared memory machines. We describe here the method, including the extension of a language-based cellular automaton to implement quantitative computing, the building of a whole-heart model with Visible Human Project data, the parallelization of the model on a cluster of shared memory computers with OpenMP and MPI hybrid programming, and a simulation algorithm that links cellular activity with the ECG. RESULTS: We demonstrate that electrical activities at channel, cell, and organ levels can be traced and captured conveniently in our extended cellular automaton system. Examples of some ECG waveforms simulated with a 2-D slice are given to support the ECG simulation algorithm. A performance evaluation of the 3-D model on a four-node cluster is also given. CONCLUSIONS: Quantitative multicellular modeling with extended cellular automata is a highly efficient and widely applicable method to weave experimental data at different levels into computational models. This process can be used to investigate complex and collective biological activities that can be described neither by their governing differentiation equations nor by discrete parallel computation. Transparent cluster computing is a convenient and effective method to make time-consuming simulation feasible. Arrhythmias, as a typical case, can be effectively simulated with the methods described