Lessons learned from SARS-CoV and MERS-CoV : FDA-approved Abelson tyrosine-protein kinase 2 inhibitors may help us combat SARS-CoV-2

SARS-CoV-2 is a newly emerging infectious disease, which originated from Wuhan in the Hubei province of China in late December 2019 [1]. Since then, it has rapidly spread all over the world, and at the time of writing this letter, WHO statistics show more than 1,696,588 cases and 105,952 deaths confirmed across the world [2]. Although there is no specific therapy for SARS-CoV-2 infection [3], combination therapy with antiviral and anti-inflammatory drugs accompanied by supportive treatment have been used for SARS-CoV-2 patients [4]. The combination of well-known HIV protease inhibitors, such as ritonavir with lopinavir, has also been a common approach to treat SARS-CoV-2. Insufficient outcome in severe cases is, however, one of the main challenges associated with the current antiviral-based therapy for SARS-CoV-2 [5]. In view of the long period required for novel drug discovery and the desperate need for a prompt response to this pandemic infection, one must resort to repurposing FDA-approved drugs. In this direction, our experience with other close members of coronaviruses such as SARS and MERS has taught us that repurposing the current drugs is a reasonable strategy. Abelson tyrosine-protein kinase 2 (Abl2), the imatinib target, was required for efficient SARS-CoV and MERS-CoV replication in vitro [6]. Coleman et al. have shown that the imatinib target Abl2 is indispensable for efficient replication of SARS-CoV and MERS-CoV in vitro

Low fingertip temperature rebound measured by digital thermal monitoring strongly correlates with the presence and extent of coronary artery disease diagnosed by 64-slice multi-detector computed tomography

Previous studies showed strong correlations between low fingertip temperature rebound measured by digital thermal monitoring (DTM) during a 5 min arm-cuff induced reactive hyperemia and both the Framingham Risk Score (FRS), and coronary artery calcification (CAC) in asymptomatic populations. This study evaluates the correlation between DTM and coronary artery disease (CAD) measured by CT angiography (CTA) in symptomatic patients. It also investigates the correlation between CTA and a new index of neurovascular reactivity measured by DTM. 129 patients, age 63 ± 9 years, 68% male, underwent DTM, CAC and CTA. Adjusted DTM indices in the occluded arm were calculated: temperature rebound: aTR and area under the temperature curve aTMP-AUC. DTM neurovascular reactivity (NVR) index was measured based on increased fingertip temperature in the non-occluded arm. Obstructive CAD was defined as ≥50% luminal stenosis, and normal as no stenosis and CAC = 0. Baseline fingertip temperature was not different across the groups. However, all DTM indices of vascular and neurovascular reactivity significantly decreased from normal to non-obstructive to obstructive CAD [(aTR 1.77 ± 1.18 to 1.24 ± 1.14 to 0.94 ± 0.92) (P = 0.009), (aTMP-AUC: 355.6 ± 242.4 to 277.4 ± 182.4 to 184.4 ± 171.2) (P = 0.001), (NVR: 161.5 ± 147.4 to 77.6 ± 88.2 to 48.8 ± 63.8) (P = 0.015)]. After adjusting for risk factors, the odds ratio for obstructive CAD compared to normal in the lowest versus two upper tertiles of FRS, aTR, aTMP-AUC, and NVR were 2.41 (1.02–5.93), P = 0.05, 8.67 (2.6–9.4), P = 0.001, 11.62 (5.1–28.7), P = 0.001, and 3.58 (1.09–11.69), P = 0.01, respectively. DTM indices and FRS combined resulted in a ROC curve area of 0.88 for the prediction of obstructive CAD. In patients suspected of CAD, low fingertip temperature rebound measured by DTM significantly predicted CTA-diagnosed obstructive disease

Directed qualitative content analysis: the description and elaboration of its underpinning methods and data analysis process

Author's accepted version (post-print).Qualitative content analysis consists of conventional, directed and summative approaches for data analysis. They are used for provision of descriptive knowledge and understandings of the phenomenon under study. However, the method underpinning directed qualitative content analysis is insufficiently delineated in international literature. This paper aims to describe and integrate the process of data analysis in directed qualitative content analysis. Various international databases were used to retrieve articles related to directed qualitative content analysis. A review of literature led to the integration and elaboration of a stepwise method of data analysis for directed qualitative content analysis. The proposed 16-step method of data analysis in this paper is a detailed description of analytical steps to be taken in directed qualitative content analysis that covers the current gap of knowledge in international literature regarding the practical process of qualitative data analysis. An example of “the resuscitation team members' motivation for cardiopulmonary resuscitation” based on Victor Vroom's expectancy theory is also presented. The directed qualitative content analysis method proposed in this paper is a reliable, transparent, and comprehensive method for qualitative researchers. It can increase the rigour of qualitative data analysis, make the comparison of the findings of different studies possible and yield practical results.acceptedVersio

Nutraceutical approaches to non-alcoholic fatty liver disease (NAFLD): A position paper from the International Lipid Expert Panel (ILEP)

Non-Alcoholic Fatty Liver Disease (NAFLD) is a common condition affecting around 10–25% of the general adult population, 15% of children, and even > 50% of individuals who have type 2 diabetes mellitus. It is a major cause of liver-related morbidity, and cardiovascular (CV) mortality is a common cause of death. In addition to being the initial step of irreversible alterations of the liver parenchyma causing cirrhosis, about 1/6 of those who develop NASH are at risk also developing CV disease (CVD). More recently the acronym MAFLD (Metabolic Associated Fatty Liver Disease) has been preferred by many European and US specialists, providing a clearer message on the metabolic etiology of the disease. The suggestions for the management of NAFLD are like those recommended by guidelines for CVD prevention. In this context, the general approach is to prescribe physical activity and dietary changes the effect weight loss. Lifestyle change in the NAFLD patient has been supplemented in some by the use of nutraceuticals, but the evidence based for these remains uncertain. The aim of this Position Paper was to summarize the clinical evidence relating to the effect of nutraceuticals on NAFLD-related parameters. Our reading of the data is that whilst many nutraceuticals have been studied in relation to NAFLD, none have sufficient evidence to recommend their routine use; robust trials are required to appropriately address efficacy and safety

Hybrid optimal online-overnight charging coordination of plug-in electric vehicles in smart grid

Optimal coordinated charging of plugged-in electric vehicles (PEVs) in smart grid (SG) can be beneficial for both consumers and utilities. This paper proposes a hybrid optimal online followed by overnight charging coordination of high and low priority PEVs using discrete particle swarm optimization (DPSO) that considers the benefits of both consumers and electric utilities. Objective functions are online minimization of total cost (associated with grid losses and energy generation) and overnight valley filling through minimization of the total load levels. The constraints include substation transformer loading, node voltage regulations and the requested final battery state of charge levels (SOCreq). The main challenge is optimal selection of the overnight starting time (toptimal-overnight,start) to guarantee charging of all vehicle batteries to the SOCreq levels before the requested plug-out times (treq) which is done by simultaneously solving the online and overnight objective functions. The online-overnight PEV coordination approach is implemented on a 449-node SG; results are compared for uncoordinated and coordinated battery charging as well as a modified strategy using cost minimizations for both online and overnight coordination. The impact of toptimal-overnight,start on performance of the proposed PEV coordination is investigated

Coordinated aggregated-based particle swarm optimisation algorithm for congestion management in restructured power market by placement and sizing of unified power flow controller

This study presents a particle swarm optimisation (PSO)-based algorithm to perform congestion management by proper placement and sizing of one unified power flow controller (UPFC) device in a market-based power system. The algorithm uses quadratic smooth curves for generators’ costs. A typical load duration curve (LDC) is used to improve the accuracy of the model by incorporating the impacts of load variation on the optimisation problem. The proposed approach makes use of the PSO algorithm to allocate the near-optimal GenCos as well as the optimal location and size of UPFC whereas the Newton– Raphson solution minimises the mismatch of the power flow equations. Simulation results (without/with the line flow constraints, before and after the compensation) are used to analyse the impact of UPFC on the congestion levels of the reliability test system (RTS) 24-bus test system. Simulation results by the proposed PSO algorithm are also compared with solutions obtained by the conventional sequential quadratic programming (SQP) approach

Optimal Particle Swarm Based Placement and Sizing of Static Synchronous Series Compensator to Maximize Social Welfare

Social welfare maximization in a double-sided auction market is performed by implementing an aggregation-based particle swarm optimization (CAPSO) algorithm for optimal placement and sizing of one Static Synchronous Series Compensator (SSSC) device. Dallied simulation results (without/with line flow constraints and without/with SSSC) are generated to demonstrate the impact of SSSC on the congestion levels of the modified IEEE 14-bus test system. The proposed CAPSO algorithm employs conventional quadratic smooth and augmented quadratic nonsmooth generator cost curves with sine components to improve the accurate of the model by incorporating the valve loading effects. CAPSO also employs quadratic smooth consumer benefit functions. The proposed approach relies on particle swarm optimization to capture the near-optimal GenCos and DisCos, as well as the location and rating of SSSC while the Newton based load flow solution minimizes the mismatch equations. Simulation results of the proposed CAPSO algorithm are compared to solutions obtained by sequential quadratic programming (SQP) and a recently implemented Fuzzy based genetic algorithm (Fuzzy-GA). The main contributions are inclusion of customer benefit in the congestion management objective function, consideration of nonsmooth generator characteristics and the utilization of a coordinated aggregation-based PSO for locating/sizing of SSSC