Fibrosis in Atrial Fibrillation – Role of Reactive Species and MPO

Atrial fibrosis with enhanced turnover and deposition of matrix proteins leads to inhomogeneous atrial electrical conduction and gives rise to electrical reentry circuits resulting in atrial fibrillation. The multifactorial pathogenesis of atrial fibrosis involves resident cardiac cells as well as infiltrating leukocytes, both generating and sequestering matrix metalloproteinases (MMPs), a key enzyme family involved in fibrosis. A growing body of evidence points toward an important role of reactive oxygen species (ROS) in the release and activation of pro-MMPs and the stimulation of pro-fibrotic cascades. Myeloperoxidase (MPO), a bactericidal enzyme released from activated polymorphonuclear neutrophils (PMN) is not only associated with a variety of cardiovascular diseases, but has also been shown to be mechanistically linked to atrial fibrosis and fibrillation. MPO catalyzes the generation of reactive species like hypochlorous acid, which affect intracellular signaling cascades in various cells and advance activation of pro-MMPs and deposition of atrial collagen resulting in atrial arrhythmias. Thus, inflammatory mechanisms effectively promote atrial structural remodeling and importantly contribute to the initiation and perpetuation of atrial fibrillation

Pressing and Sintering of Titanium Aluminide Powder after Ball Milling in Silane-Doped Atmosphere

Due to the high specific surface area of titanium aluminide powders, significant and unavoidable surface oxidation takes place during processing. The resulting oxides disrupt the conventional powder metallurgical process route (pressing and sintering) by reducing the green strength and sintered properties. Oxide-free particle surfaces offer the potential to significantly increase particle bond strength and enable the processing of difficult-to-press material powders. In this work, the effect of milling titanium aluminide powder in a silane-doped atmosphere on the component properties after pressing and the subsequent sintering was investigated. Ball milling was used to break up the oxide layers and create bare metal surfaces on the particles. With the help of silane-doped inert gas, the oxygen partial pressure was greatly reduced during processing. It was investigated whether oxide-free surfaces could be produced and maintained by milling in silane-doped atmospheres. Furthermore, the resulting material properties after pressing and sintering were analysed using density measurements, hardness tests, EDX measurements, and micrographs. It was concluded that ball milling in a silane-doped atmosphere produces and maintains oxide-free particle surfaces. These oxide-free surfaces and smaller particle sizes improve the component properties after pressing and sintering

Hybrid Electric Propulsion Systems for Medium-Range Aircraft from a Maintenance Point of View

The use of a hybrid electric propulsion system for aircraft offers the potential to increase aircraft efficiency, reduce fuel consumption and thus reduce emissions. Design concepts, emission analysis and aircraft performance are being studied extensively. However, how future hybrid electric propulsion systems will change the maintenance, repair and overhaul (MRO) of an aircraft is also an important consideration. This paper examines the effects of hybridisation on a parallel hybrid electric propulsion system of a medium-range aircraft, the Airbus A320, powered by an IAE V2500 engine. The electric motor is powered by a battery and is used to assist the turbofan engine, mainly during the takeoff phase. The additional system components of the chosen hybrid electric propulsion system and their corresponding damage mechanisms are addressed from a maintenance point of view. Challenges for future maintenance are discussed and possible failure modes and failure possibilities are analysed. For this purpose, a Failure Mode and Effects Analysis and a Fault Tree Analysis will be carried out. The results of this analysis can be used to determine how the additional components need to be designed to maintain the overall safety of the propulsion system at the current level. This will also provide needs and ideas for a future design for maintenance

Data and systems for medication-related text classification and concept normalization from Twitter: insights from the Social Media Mining for Health (SMM4H)-2017 shared task

Objective: We executed the Social Media Mining for Health (SMM4H) 2017 shared tasks to enable the community-driven development and large-scale evaluation of automatic text processing methods for the classification and normalization of health-related text from social media. An additional objective was to publicly release manually annotated data.Materials and Methods: We organized 3 independent subtasks: automatic classification of self-reports of 1) adverse drug reactions (ADRs) and 2) medication consumption, from medication-mentioning tweets, and 3) normalization of ADR expressions. Training data consisted of 15 717 annotated tweets for (1), 10 260 for (2), and 6650 ADR phrases and identifiers for (3); and exhibited typical properties of social-media-based health-related texts. Systems were evaluated using 9961, 7513, and 2500 instances for the 3 subtasks, respectively. We evaluated performances of classes of methods and ensembles of system combinations following the shared tasks.Results: Among 55 system runs, the best system scores for the 3 subtasks were 0.435 (ADR class F1-score) for subtask-1, 0.693 (micro-averaged F1-score over two classes) for subtask-2, and 88.5% (accuracy) for subtask-3. Ensembles of system combinations obtained best scores of 0.476, 0.702, and 88.7%, outperforming individual systems.Discussion: Among individual systems, support vector machines and convolutional neural networks showed high performance. Performance gains achieved by ensembles of system combinations suggest that such strategies may be suitable for operational systems relying on difficult text classification tasks (eg, subtask-1).Conclusions: Data imbalance and lack of context remain challenges for natural language processing of social media text. Annotated data from the shared task have been made available as reference standards for future studies (http://dx.doi.org/10.17632/rxwfb3tysd.1).</div

Development of a wind gust model to estimate gust speeds and their return periods

Spatially dense observations of gust speeds are necessary for various applications, but their availability is limited in space and time. This work presents an approach to help to overcome this problem. The main objective is the generation of synthetic wind gust velocities. With this aim, theoretical wind and gust distributions are estimated from 10 yr of hourly observations collected at 123 synoptic weather stations provided by the German Weather Service. As pre-processing, an exposure correction is applied on measurements of the mean wind velocity to reduce the influence of local urban and topographic effects. The wind gust model is built as a transfer function between distribution parameters of wind and gust velocities. The aim of this procedure is to estimate the parameters of gusts at stations where only wind speed data is available. These parameters can be used to generate synthetic gusts, which can improve the accuracy of return periods at test sites with a lack of observations. The second objective is to determine return periods much longer than the nominal length of the original time series by considering extreme value statistics. Estimates for both local maximum return periods and average return periods for single historical events are provided. The comparison of maximum and average return periods shows that even storms with short average return periods may lead to local wind gusts with return periods of several decades. Despite uncertainties caused by the short length of the observational records, the method leads to consistent results, enabling a wide range of possible applications

Covid-19 triage in the emergency department 2.0: how analytics and AI transform a human-made algorithm for the prediction of clinical pathways

The Covid-19 pandemic has pushed many hospitals to their capacity limits. Therefore, a triage of patients has been discussed controversially primarily through an ethical perspective. The term triage contains many aspects such as urgency of treatment, severity of the disease and pre-existing conditions, access to critical care, or the classification of patients regarding subsequent clinical pathways starting from the emergency department. The determination of the pathways is important not only for patient care, but also for capacity planning in hospitals. We examine the performance of a human-made triage algorithm for clinical pathways which is considered a guideline for emergency departments in Germany based on a large multicenter dataset with over 4,000 European Covid-19 patients from the LEOSS registry. We find an accuracy of 28 percent and approximately 15 percent sensitivity for the ward class. The results serve as a benchmark for our extensions including an additional category of palliative care as a new label, analytics, AI, XAI, and interactive techniques. We find significant potential of analytics and AI in Covid-19 triage regarding accuracy, sensitivity, and other performance metrics whilst our interactive human-AI algorithm shows superior performance with approximately 73 percent accuracy and up to 76 percent sensitivity. The results are independent of the data preparation process regarding the imputation of missing values or grouping of comorbidities. In addition, we find that the consideration of an additional label palliative care does not improve the results

Transcatheter Treatment (TAVI, MitraClip (R), Tricuspid Interventions) of Valvular Heart Disease in Heart Failure - Which Patients Have a Benefit Already Today?

Valvular heart disease is a critical contributor to morbidity and mortality particularly in patients with impaired left ventricular ejection fraction. With regard to severity of the underlying valvular disorder and additional comorbidities, treatment options for the majority of patients have long been limited to medical approaches only, and potential surgical interventions were widely associated with significantly increased perioperative risk. In recent years, transcatheter valve replacement and repair has become an important tool to treat this subset of patients. For patients with severe aortic stenosis and intermediate or high perioperative risk, transfemoral TAVI has shown better short-and midterm results as compared to conventional surgical valve replacement. Therefore TF-TAVI should be considered as primary treatment option for these patients. Percutaneous mitral valve repair with the MitraClip (R) has proven relief of symptoms in heart failure patients at advanced stages with suitable valve morphology at high risk for surgical treatment. For a short time, several interventional approaches to treat patients with severe tricuspid regurgitation and mainly symptoms of right heart failure have been successfully applied. Still, clinical experience in this field is limited as randomised trials in larger cohorts are not available at the time. However, there are promising interventional approaches to successfully treat patients with sustained symptoms of right heart failure despite optimal medical treatment and at high operative risk