The Atrial FibriLlatiOn (FLOW-AF) Registry in the Middle East and North Africa: Patient Characteristics, Treatment Patterns and Outcomes.

INTRODUCTION: Limited data on atrial fibrillation (AF) are available from the Middle East and North Africa region (MENA). The aim of the FLOW-AF registry was to evaluate the characteristics, treatment patterns, and clinical and economic outcomes of patients with newly diagnosed non-valvular atrial fibrillation (NVAF) in MENA. METHODS: This multi-center, prospective, observational study (the FLOW-AF registry) enrolled patients newly diagnosed with NVAF across Egypt, Lebanon, Kingdom of Saudi Arabia, and United Arab Emirates. The data collection occurred at enrollment (baseline) and after 6- and 12-months (follow-up). Baseline data included demographics, AF characteristics, medical history, and anti-thrombotic treatment patterns. Clinical events, healthcare resource utilization, and direct costs were collected at follow-up. RESULTS: The study enrolled a total of 1418 patients (52.7% males and 47.3% females). The mean age of the patients was 64.5 years and 90.6% were white. The mean (standard deviation) CHA2DS2-VASc and HAS-BLED risk scores were 2.7 (1.6) and 1.6 (1.2), respectively. Non-vitamin K antagonist oral anticoagulants, antiplatelet therapy, and vitamin K antagonists were prescribed to 65.8%, 16.4%, and 12.9% patients, respectively. During follow-up, the following rates of clinical outcomes were observed: bleeding events (1.7%), transient ischemic attack (1.7%), all-cause mortality (1.7%), stroke (0.6%), myocardial infarction (0.2%), and systemic embolism (0.08%). CONCLUSIONS: This MENA patient population was younger and had lower mean baseline CHA2DS2-VASc and HAS-BLED scores. The rates of clinical outcomes over 1-year in this study were low. Longer follow-up is required to comprehensively assess clinical outcomes in this patient population.

Self-adaptive Bioinspired Hummingbird-wing Stimulated Triboelectric Nanogenerators.

Bio-inspired technologies have remarkable potential for energy harvesting from clean and sustainable energy sources. Inspired by the hummingbird-wing structure, we propose a shape-adaptive, lightweight triboelectric nanogenerator (TENG) designed to exploit the unique flutter mechanics of the hummingbird for small-scale wind energy harvesting. The flutter is confined between two surfaces for contact electrification upon oscillation. We investigate the flutter mechanics on multiple contact surfaces with several free-standing and lightweight electrification designs. The flutter driven-TENGs are deposited on simplified wing designs to match the electrical performance with variations in wind speed. The hummingbird TENG (H-TENG) device weighed 10 g, making it one of the lightest TENG harvesters in the literature. With a six TENG network, the hybrid design attained a 1.5 W m-2 peak electrical output at 7.5 m/s wind speed with an approximately linear increase in charge rate with the increased number of TENG harvesters. We demonstrate the ability of the H-TENG networks to operate Internet of Things (IoT) devices from sustainable and renewable energy sources.

An automated system for high-throughput generation and optimization of microdroplets.

Microdroplets have been widely used in various biomedical applications. During droplet generation, parameters are manually adjusted to achieve the desired size of droplets. This process is tedious and time-consuming. In this paper, we present a fully automated system for controlling the size of droplets to optimize droplet generation parameters in a microfluidic flow-focusing device. The developed system employed a novel image processing program to measure the diameter of droplets from recorded video clips and correspondingly adjust the flow rates of syringe pumps to obtain the required diameter of droplets. The system was tested to generate phosphate-buffered saline and 8% polyethylene (glycol) diacrylate prepolymer droplets and regulate its diameters at various flow rates. Experimental results demonstrated that the difference between droplet diameters from the image processing and manual measurement is not statistically significant and the results are consistent over five repetitions. Taking the advantages of the accurate image processing method, the size of the droplets can be optimized in a precise and robust manner via automatically adjusting flow rates by the feedback control. The system was used to acquire quantitative data to examine the effects of viscosity and flow rates. Droplet-based experiments can be greatly facilitated by the automatic droplet generation and optimization system. Moreover, the system is able to provide quantitative data for the modelling and application of droplets with various conditions in a high-throughput way.