37 research outputs found

    Two dimensional turbulence in inviscid fluids or guiding center plasmas

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    Analytic theory for two-dimensional turbulent equilibria for the inviscid Navier-Stokes equations is examined mathematically. Application of the technique to electrostatic guiding center plasma is discussed. A good fit is demonstrated for the approach to a predicted energy per Fourier mode obtained from a two-temperature canonical ensemble. Negative as well as positive temperature regimes are explored. Fluctuations about the mean energy per mode also compare well with theory. In the regime of alpha less than zero, beta greater than zero, with the minimum value of alpha plus beta times k squared near zero, contour plots of the stream function reveal macroscopic vortex structures similar to those seen previously in discrete vortex simulations. Eulerian direct interaction equations, which can be used to follow the approach to inviscid equilibrium, are derived

    Novel non-invasive algorithm to identify the origins of re-entry and ectopic foci in the atria from 64-lead ECGs: A computational study.

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    Atrial tachy-arrhytmias, such as atrial fibrillation (AF), are characterised by irregular electrical activity in the atria, generally associated with erratic excitation underlain by re-entrant scroll waves, fibrillatory conduction of multiple wavelets or rapid focal activity. Epidemiological studies have shown an increase in AF prevalence in the developed world associated with an ageing society, highlighting the need for effective treatment options. Catheter ablation therapy, commonly used in the treatment of AF, requires spatial information on atrial electrical excitation. The standard 12-lead electrocardiogram (ECG) provides a method for non-invasive identification of the presence of arrhythmia, due to irregularity in the ECG signal associated with atrial activation compared to sinus rhythm, but has limitations in providing specific spatial information. There is therefore a pressing need to develop novel methods to identify and locate the origin of arrhythmic excitation. Invasive methods provide direct information on atrial activity, but may induce clinical complications. Non-invasive methods avoid such complications, but their development presents a greater challenge due to the non-direct nature of monitoring. Algorithms based on the ECG signals in multiple leads (e.g. a 64-lead vest) may provide a viable approach. In this study, we used a biophysically detailed model of the human atria and torso to investigate the correlation between the morphology of the ECG signals from a 64-lead vest and the location of the origin of rapid atrial excitation arising from rapid focal activity and/or re-entrant scroll waves. A focus-location algorithm was then constructed from this correlation. The algorithm had success rates of 93% and 76% for correctly identifying the origin of focal and re-entrant excitation with a spatial resolution of 40 mm, respectively. The general approach allows its application to any multi-lead ECG system. This represents a significant extension to our previously developed algorithms to predict the AF origins in association with focal activities

    Mathematical Modeling and Simulation of Ventricular Activation Sequences: Implications for Cardiac Resynchronization Therapy

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    Next to clinical and experimental research, mathematical modeling plays a crucial role in medicine. Biomedical research takes place on many different levels, from molecules to the whole organism. Due to the complexity of biological systems, the interactions between components are often difficult or impossible to understand without the help of mathematical models. Mathematical models of cardiac electrophysiology have made a tremendous progress since the first numerical ECG simulations in the 1960s. This paper briefly reviews the development of this field and discusses some example cases where models have helped us forward, emphasizing applications that are relevant for the study of heart failure and cardiac resynchronization therapy

    The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

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    INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

    Methotrexate loaded SAE coated coronary stents reduce neointimal hyperplasia in a porcine coronary model

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    Objective: To evaluate the effect of stent based methotrexate delivery on neointimal hyperplasia. Methods: Stainless steel coronary stents and biological polymer coated (SAE) stents were randomly implanted in coronary arteries of pigs with a stent to artery ratio of 1.1:1. The pigs were killed after five days (10 stents) or four weeks (20 stents). Second, stainless steel coronary stents were dip coated in a 10 mg/ml methotrexate–SAE polymer solution, resulting in a total load of 150 μg methotrexate/stent. SAE coated stents and methotrexate loaded stents were randomly implanted in porcine coronary arteries with a stent to artery ratio of 1.2:1 and followed up to four weeks. Results: SAE coated stents and bare stents elicited a similar tissue response at five days. At four weeks, neointimal hyperplasia induced by the coated stents was less pronounced than with the bare stents (1.32 (0.66) v 1.73 (0.93) mm(2), p > 0.05). In vitro drug release studies showed that 50% of the methotrexate was released in 24 hours, and all drug was released within four weeks. No impact on vascular smooth muscle cell proliferation or viability was observed in in vitro cell cultures. At four weeks the arteries with methotrexate loaded stents had decreased peristrut inflammation and neointimal hyperplasia (1.22 (0.34) v 2.25 (1.28) mm(2), p < 0.01). Conclusions: SAE coating had an excellent biocompatibility with vascular tissue. Stent based delivery of methotrexate in the SAE coating effectively reduced neointimal hyperplasia in a porcine coronary stent model, potentially due to reduced peristrut inflammation

    Comparison And Combination Of Statistical And Neural Network Algorithms For Remote-Sensing Image Classification

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    In recent years, the remote-sensing community has became very interested in applying neural networks to image classification and in comparing neural networks performances with the ones of classical statistical methods. These experimental comparisons pointed out that no single classification algorithm can be regarded as a &quot;panacea&quot;. The superiority of one algorithm over the other strongly depends on the selected data set and on the efforts devoted to the &quot;designing phases&quot; of algorithms. In this paper, we propose the use of &quot;ensembles&quot; of neural and statistical classification algorithms as an alternative approach based on the exploitation of the complementary characteristics of different classifiers. Classification results provided by image classifiers contained in these ensembles are &quot;merged&quot; according to statistical combination methods. Experimental results on a multisensor remotesensing data set point out that the use of classifiers ensembles can constitute a valid alternative to the..
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