Management of the arrhythmic manifestations of cardiac sarcoidosis

Cardiac sarcoidosis (CS) is characterised by a high burden of arrhythmic manifestations and cardiac electrophysiologists play an important role in both the diagnosis and management of this challenging condition. CS is characterised by the formation of noncaseating granulomas within the myocardium, which can subsequently lead to fibrosis. Clinical presentations of CS are varied and depend on the location and extent of granulomas. Patients may present with atrioventricular block, ventricular arrhythmias, sudden cardiac death or heart failure. CS is being increasing diagnosed through use of advanced cardiac imaging, however endomyocardial biopsy is often still required to confirm the diagnosis. Due to the low sensitivity of fluoroscopy-guided right ventricular biopsies, three-dimensional electro-anatomical mapping and electrogram-guided biopsies are being investigated as a means to improve diagnostic yield. Cardiac implantable electronic devices are often required in the management of CS, either for pacing or for primary or secondary prevention of ventricular arrhythmias. Catheter ablation for ventricular arrythmias may also be required, although this is often associated with high recurrence rates due to the challenging nature of the arrhythmogenic substrate. This review will explore the underlying mechanisms of the arrhythmic manifestations of CS, provide an overview of current clinical practice guidelines, and examine the important role that cardiac electrophysiologists play in managing patients with CS

Stability improvement of an efficient graphene nanoribbon field-effect transistor-based sram design

The development of the nanoelectronics semiconductor devices leads to the shrinking of transistors channel into nanometer dimension. However, there are obstacles that appear with downscaling of the transistors primarily various short-channel effects. Graphene nanoribbon field-effect transistor (GNRFET) is an emerging technology that can potentially solve the issues of the conventional planar MOSFET imposed by quantum mechanical (QM) effects. GNRFET can also be used as static random-access memory (SRAM) circuit design due to its remarkable electronic properties. For high-speed operation, SRAM cells are more reliable and faster to be effectively utilized as memory cache. The transistor sizing constraint affects conventional 6T SRAM in a trade-off in access and write stability. This paper investigates on the stability performance in retention, access, and write mode of 15 nm GNRFET-based 6T and 8T SRAM cells with that of 16 nm FinFET and 16 nm MOSFET. The design and simulation of the SRAM model are simulated in synopsys HSPICE. GNRFET, FinFET, and MOSFET 8T SRAM cells give better performance in static noise margin (SNM) and power consumption than 6T SRAM cells. The simulation results reveal that the GNRFET, FinFET, and MOSFET-based 8T SRAM cells improved access static noise margin considerably by 58.1%, 28%, and 20.5%, respectively, as well as average power consumption significantly by 97.27%, 99.05%, and 83.3%, respectively, to the GNRFET, FinFET, and MOSFET-based 6T SRAM design. © 2020 Mathan Natarajamoorthy et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Production, optimization and characterisation of chitosanase of Bacillus sp. and its applications in nanotechnology

Chitosanases is a class of enzymes which hydrolyse chitosan, a natural biopolymer consisting of d-glucosamine in various degrees. In this study, chitosanase producing Bacillus sp. was isolated from soil sample. Chitosanase production was optimized using response surface methodology and the produced chitosanase was characterized. The crude enzyme was found to possess antibacterial and antifungal activity. Chitosanase enzyme was used for trimming chitosan based polymeric nanoparticles produced using sodium trimetaphosphate chelator. Chitosanase enzyme was also utilized for synthesis of silver nanoparticles which were then characterized by UV–Vis, FTIR, SEM, TEM and AFM. The produced nanoparticles were checked for antibacterial and antifungal activity

Differential Evolution Based IDWNN Controller for Fault Ride-Through of Grid-Connected Doubly Fed Induction Wind Generators

The key objective of wind turbine development is to ensure that output power is continuously increased. It is authenticated that wind turbines (WTs) supply the necessary reactive power to the grid at the time of fault and after fault to aid the flowing grid voltage. At this juncture, this paper introduces a novel heuristic based controller module employing differential evolution and neural network architecture to improve the low-voltage ride-through rate of grid-connected wind turbines, which are connected along with doubly fed induction generators (DFIGs). The traditional crowbar-based systems were basically applied to secure the rotor-side converter during the occurrence of grid faults. This traditional controller is found not to satisfy the desired requirement, since DFIG during the connection of crowbar acts like a squirrel cage module and absorbs the reactive power from the grid. This limitation is taken care of in this paper by introducing heuristic controllers that remove the usage of crowbar and ensure that wind turbines supply necessary reactive power to the grid during faults. The controller is designed in this paper to enhance the DFIG converter during the grid fault and this controller takes care of the ride-through fault without employing any other hardware modules. The paper introduces a double wavelet neural network controller which is appropriately tuned employing differential evolution. To validate the proposed controller module, a case study of wind farm with 1.5 MW wind turbines connected to a 25 kV distribution system exporting power to a 120 kV grid through a 30 km 25 kV feeder is carried out by simulation

Profiling of MicroRNA expression in obese and diabetic-induced mice for biomarker discovery

MicroRNAs (miRNAs) are short (-22 nucleotides) regulatory RNAs involved in many fundamental biological processes. They are involved in post-transcriptional regulation of gene expression. Dysregulated expression of microRNAs has been associated with a variety of diseases, including obesity and diabetes. Obesity is a potential risk factor contributing to the development of type 2 diabetes. Meanwhile, diabetes is one of the most prevalent chronic diseases, affecting 6.4% of the world’s adult population. The aim of this study is to identify microRNAs that are differentially expressed in obese, diabetic and control C57BL/6 mice by using small RNA sequencing. Total RNAs were extracted from the serum of the target groups of animals. Next, the small RNAs were sequenced using the TruSeq small RNA Library Prep Kit in a MiSeq Illumina sequencer. A total of 52 up-regulated and 54 down-regulated miRNAs were identified based on the comparison of the log2 fold change of obese and diabetic (with normal mice as control; FC ≥ 2). The obese groups showed 22 up-regulated and 25 down-regulated microRNAs. Meanwhile, in the diabetic group, 32 microRNAs were up-regulated and 29 were down-regulated. This finding will help better understand the mechanism of metabolic disorders and may influence future approaches for the diagnosis and treatment of obesity and diabetes

Impact of hydrodynamic conditions on optimum power generation in dual stage pressure retarded osmosis using spiral-wound membrane

The Dual Stage Pressure Retarded Osmosis technique is considered for power generation. The influence of feed flow rates, hydraulic pressure, and pressure drop on mass transfer and solute diffusion in a full-scale membrane model was investigated for the first time to maximize power generation. Dead Sea-seawater, Dead Sea-reverse osmosis brine, reverse osmosis brine-wastewater, and seawater-wastewater salinity gradient resources were investigated for power generation. Results revealed a 71.07% increase in the specific power generation due to the dual-stage pressure retarded osmosis process optimization using Dead Sea-seawater salinity gradient resources. The increase in the specific power generation due to the dual-stage pressure retarded osmosis optimization was 108.8%, 63.18%, and 133.54%, respectively, for Dead Sea-reverse osmosis brine, reverse osmosis brine-wastewater, and seawater-wastewater salinity gradient resources. At optimum operating conditions, using the dual-stage pressure retarded osmosis process as an alternative to the single pressure retarded osmosis process achieved up to a 22% increase in the energy output. Interestingly, the hydraulic pressure at optimum operating conditions was slightly higher than the average osmotic pressure gradients in the dual-stage pressure retarded osmosis process. The study also revealed that power generation in the dual-stage pressure retarded osmosis process operating at constant mass transfer and solute resistivity parameters was overestimated by 2.8%

Surface-enhanced Raman spectral biomarkers correlate with Ankle Brachial Index and characterize leg muscle biochemical composition of patients with peripheral arterial disease

Peripheral arterial disease (PAD) is characterized by atherosclerotic blockages of the arteries supplying the lower extremities, which cause a progressive accumulation of ischemic injury to the skeletal muscles of the lower limbs. This injury includes altered metabolic processes, damaged organelles, and compromised bioenergetics in the affected muscles. The objective of this study was to explore the association of Raman spectral signatures of muscle biochemistry with the severity of atherosclerosis in the legs as determined by the Ankle Brachial Index (ABI) and clinical presentation. We collected muscle biopsies from the gastrocnemius (calf muscle) of five patients with clinically diagnosed claudication, five patients with clinically diagnosed critical limb ischemia (CLI), and five control patients who did not have PAD. A partial least squares regression (PLSR) model was able to predict patient ABI with a correlation coefficient of 0.99 during training and a correlation coefficient of 0.85 using a full cross-validation. When using the first three PLS factor scores in combination with linear discriminant analysis, the discriminant model was able to correctly classify the control, claudicating, and CLI patients with 100% accuracy, using a full cross-validation procedure. Raman spectroscopy is capable of detecting and measuring unique biochemical signatures of skeletal muscle. These signatures can discriminate control muscles from PAD muscles and correlate with the ABI and clinical presentation of the PAD patient. Raman spectroscopy provides novel spectral biomarkers that may complement existing methods for diagnosis and monitoring treatment of PAD patients