ABSTRACT
SARS-like coronaviruses, including SARS-CoV and SARS-CoV-2, encode spike proteins that bind human ACE2 protein on the cell surface to enter target cells and cause infection. The efficiency of virus entry depends on ACE2 sequence and expression levels in target cells. A small fraction of humans encodes variants of ACE2, thus altering the biochemical properties at the protein interaction interface. All humans possess cells with vastly differing amounts of ACE2 on the cell surface, ranging from cell types with high expression in the gut and lungs to lower expression in the liver and pancreas. Mastering our understanding of spike-ACE2 interaction and infection requires experiments precisely perturbing both variables. Thus, we developed a synthetic cell engineering approach compatible with high throughput assays for pseudo-typed virus infection. Our assay system is capable of assessing both variables individually and in combination. We adapted an engineered HEK293T DNA recombinase landing pad cell line capable of expressing transgenic ACE2 sequences at highly precise levels. Infection with lentiviruses pseudotyped with the spikes of SARS-like coronaviruses revealed that high ACE2 abundance could mask the effects of impaired binding thereby making it challenging to know the role of affinity altering mutations during infection. We limited the ACE2 abundance on the cell surface by expressing transgenic ACE2 behind a suboptimal Kozak sequence, thereby altering its protein translation rate. This allowed us to understand how ACE2 sequence could impact its interaction with coronavirus spike proteins as two human ACE2 variants at the binding interface, K31D and D355N, exhibited reduced infection. Our experiments suggested that we need to better understand how ACE2 expression determines the susceptibility of cells for SARS-like coronavirus binding and infection. We thus created an ACE2 Kozak library consisting of ~4,096 Kozak variants, each conferring a different ACE2 protein translation rate thus resulting in a range of ACE2 steady-state abundances. Combining fluorescence-activated cell sorting and high-throughput DNA sequencing (FACS-seq) revealed the library to span two orders of magnitude of ACE2 abundance. Challenging this library of cells with spike pseudotyped lentiviruses revealed how ACE2 abundance correlated with infection rate. The library-based experiments yielded a dynamic range wider than traditional single sample infection assay, likely more representative of infection dynamics in vivo. Now that we have characterized the impacts of ACE2 abundance on infectivity in engineered cells, our next goal is to expand the comparison to physiologically relevant cells with endogenously expressed proteins. Modulating protein abundance levels will be key to creating maximally informative functional assays for any protein in cell-based assays, and we have laid the groundwork for being able to simultaneously test the impacts of protein abundance and sequence in combination for proteins involved in diverse cellular processes. This research was supported by a National Institute of Health (NIH) grant GM142886 (KAM).Copyright © 2023 The American Society for Biochemistry and Molecular Biology, Inc.
ABSTRACT
Global supply chains (SCs) have been severely impacted by the COVID-19 pandemic on several levels. For example, SCs suffered from panic buying-related instabilities and multiple disruptions of supply, demand, and capacity during the pandemic. This study developed an agent-based model (ABM) to predict the effects of panic buying-related instabilities in SCs and offered strategies to improve them. The ABM model includes a simulation and optimization model of a typical SC of an essential product manufacturer (i.e., toilet paper SC) for the analysis of scenarios and strategies to observe improvements in SCs. Among the four strategies identified, the findings suggest boosting production capacity to the maximum and ensuring optimal reorder points, order sizes, and trucks helped the essential product manufacturers reduce panic buying-related instabilities in their SCs. Copyright (C) 2022 The Authors.
ABSTRACT
COVID - 19 has changed the way of management education. Blended Learning (BL) has become an integral part of management education and the way ahead in our new normal. Sustainable management education is coalescing around 2030 agenda and the Sustainable Development Goals (SDGs) as introduced in new mission statement UN PRME's (2016). As the pandemic developed, academia needs to be trained in new forms of operation to meet SDGs (Goal 4) of quality education which can be done through sustainable management education in the context of MBA programs.. The study employs Community of Inquiry (CoI) paradigm to ascertain the effectiveness of BL;the study also brings about the co-dependency of the elements of CoI framework. Numerous research propositions are addressed during the study. The study also reflects on the perception of MBA educators and their behavioral intention towards BL. This research provides a comprehensive review of the best practices for designing academic programs in management education using of BL. © The Electrochemical Society
ABSTRACT
Coronavirus Disease 2019 (COVID-19) is declared as pandemic on 11 March 2020 by World Health Organization (WHO). There are apparent dissimilarities in incidence and mortality of COVID-19 cases in different parts of world. Developing countries in Asia and Africa with fragile health system are showing lower incidence and mortality compared to developed countries with superior health system in Europe and America. Most countries in Asia and Africa have national Bacillus Calmette-Guerin (BCG) vaccination programme, while Europe and America do not have such programme or have ceased it. At present, there is no known Food and Drug Administration (FDA)-approved treatment available for COVID-19 disease. There is no vaccine available currently to prevent COVID-19 disease. As mathematical modelling is ideal for predicting the rate of disease transmission as well as evaluating efficacy of possible public health prevention measures, we have created a mathematical model with seven compartments to understand nationwide BCG vaccine recommendation on COVID-19 transmission, severity and mortality. We have computed two basic reproduction numbers, one at vaccine-free equilibrium point and other at non-vaccine-free equilibrium point, and carried out local stability, sensitivity and numerical analysis. Our result showed that individuals with BCG vaccinations have lower risk of getting COVID-19 infection, shorter hospital stays and increased rate of recovery. Furthermore, countries with long-standing universal BCG vaccination policies have reduced incidence, mortality and severity of COVID-19. Further research will focus on exploring the immediate benefits of vaccination to healthcare workers and patients as well as benefits of BCG re-vaccination. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Background: COVID-19, the disease caused by SARS CoV2, causes severe respiratory disease, and rarely multisystem inflammatory syndrome, in some pediatric patients. Little is known about the disease course among patients with pediatric-onset multiple sclerosis. Objectives: To describe the demographic and clinical characteristics of a subgroup of pediatric-onset multiple sclerosis (POMS) patients infected with SARS CoV2. Methods: The Network of Pediatric Multiple Sclerosis Centers (NPMSC), a consortium of 10 US pediatric multiple sclerosis (MS) centers contributes clinical information about POMS patients and demyelinating disorders to a centralized database, the Pediatric Demyelinating Disease Database (PeMSDD), to facilitate research for this rare disorder. In addition to collecting clinical data on clinical course, comorbidities, disease modifying therapy use, and functional status, the NPMSC developed a screening questionnaire to administer to patients during standard of care visits to further evaluate their COVID- 19 status. Additionally POMS patients with confirmed or highly suspected COVID-19, will be assessed for risk factors including smoking use, recent glucocorticoid use, comorbidities;clinical presentation, including symptoms, radiological and laboratory data;COVID-19 treatments and outcomes. POMS patients will also complete the COViMS (COVID-19 Infections in MS & Related Diseases) database, a joint effort of the US National MS Society and the Consortium of MS Centers to capture information on outcomes of people with MS and other central nervous system (CNS) demyelinating diseases (Neuromyelitis Optica Spectrum Disease, or MOG antibody disease) who have developed COVID- 19. Together with data collected from the PeMSDD, we will present comprehensive data on the POMS patient experience with COVID- 19 and compare it to POMS patients without known or suspected COVID-19. Results: Data collection continues. Results available by the meeting due date will describe the demographics, risk factors, treatments and outcomes of POMS with COVID-19. Conclusions: will be drawn pending results of data analysis. We anticipate reporting on demographic data, risk factors, outcomes and any associations with disease modifying therapy.
ABSTRACT
Due to the current COVID-19 (SARS-CoV-2) outbreak, supply chains have been severely disrupted in long term globally. In this paper, we present the results of a simulation study conducted on a case of the global supply chain. We have discussed the impact of COVID19 on the supply chains by citing some recent examples in the retail sector in Australia. We demonstrate the use of simulation modelling to quickly and reliably model and analyze supply chain disruptions through the use of anyLogistix simulation software. In this paper, we have simulated a case of an Australian hardware retail supply chain that has a global supply network. We have investigated the impact of COVID19 disruptions on the supply chain performance. Our results highlighted the importance of waiting order cancellation strategy in the recovery period for reducing supply chain costs and maintaining service level. We also discussed the negative effect of distance between supplier and customer on the resiliency of delivery systems. This initial work was a proof of concept to simulate COVID19 disruptions on a retail supply chain. © 2020 IEEE.