Interaction of SCoV-2 NSP7 or NSP8 alone may cause constriction of the RNA entry channel in NSP12: Implications for novel RdRp inhibitor drug discovery (preprint)

RNA-dependent RNA polymerase (RdRP) is a critical component of the RNA virus life cycle, including SCoV-2. Among the Coronavirus-encoded proteins, non-structural protein 12 (NSP12) exhibits polymerase activity in collaboration with one unit of NSP7 and two units of NSP8, constituting the RdRp holoenzyme. While there is abundant information on SCoV-2 RdRp-mediated RNA replication, the influence of interplay among NSP12, NSP7, and NSP8 on template RNA binding and primer extension activity remains relatively unexplored and poorly understood. Here, we recreated a functional RdRp holoenzyme in vitro using recombinant SCoV-2 NSP12, NSP7, and NSP8, and established its functional activity. Subsequently, molecular interactions among the NSPs in the presence of a variety of templates and their effects on polymerase activity were studied, wherein we found that NSP12 alone exhibited notable polymerase activity that increased significantly in the presence of NSP7 and NSP8. However, this activity was completely shut down, and the template RNA primer complex was detached from NSP12 when one of the to cofactors was present. Through computational analysis, we found that the template RNA entry channel was more constricted in the presence of one of the two cofactors, which was relatively more constricted in the presence of NSP8 compared to that in the presence of NSP7. In conclusion, we report that NSP7 and NSP8 together synergise to enhance the activity of NSP12, but antagonise when present alone. Our findings have implications for novel drug development, and compounds that obstruct the binding of NSP7 or NSP8 to NSP12 can have lethal effects on viral RNA replication.

The Distribution of Fecal Contamination in an Urbanized Tropical Lake and Incidence of Acute Diarrheal Disease

Aquatic ecosystems of tropical countries are vulnerable to fecal contamination that could cause spikes in the incidences of acute diarrheal disease (ADD) and challenge public health management systems. Vembanad lake, situated along the southwest coast of India, was monitored for one year (2018-2019). Escherichia coli, an indicator of fecal contamination, was prevalent in the lake throughout the year. Multiple antibiotic resistance among more than 50% of the E. coli isolates adds urgency to the need to control this contamination. The high abundance of E. coli and incidence of ADD were recorded during the early phase of the southwest monsoon (June-July), prior to the once-in-a-century floods that affected the region in the later phase (August). The extent of inundation in the low-lying areas peaked in August, but E. coli in the water peaked in July, suggesting that contamination occurred even prior to extreme flooding. During the COVID-19-related lockdown in March-May 2021, fecal contamination in the lake and incidence of ADD reached minimum values. These results indicate the need for improving sewage treatment facilities and city planning in flood-prone areas to avoid the mixing of septic sewage with natural waters during extreme climate events or even during the normal monsoon.

A DIGITAL TWIN BASED APPROACH FOR ENSURING BUSINESS CONTINUITY PLAN AND SAFE RETURN TO WORKPLACE

Organizations are struggling to ensure business continuity without compromising on delivery excellence in the face of Covid19 pandemic related uncertainties. The uncertainty exists along multiple dimensions such as virus mutations, infectivity and severity of new mutants, efficacy of vaccines against new mutants, waning of vaccine induced immunity over time, and lockdown/opening-up policies effected by city authorities. Moreover, this uncertainty plays out in a non-uniform manner across nations, states, cities, and even within the cities thus leading to highly heterogeneous evolution of pandemic. While Work From Home (WFH) strategy has served well to meet ever-increasing business demands without compromising on individual health safety, there has been an undeniable reduction in social capital. With Covid19 pandemic showing definite waning trends, organizations are considering the possibility of safe transition from WFH to Work From Office (WFO) or a hybrid mode of operation. An effective strategy needs to score equally well on possibly interfering dimensions such as risk of infection, project delivery, and employee wellness. As large organizations will typically have a large number of offices spread across a geography, the problem of arriving at office-specific strategies becomes non-trivial. Moreover, the strategies need to adapt over time to changes that cannot be deduced upfront. This calls for an approach that is amenable to quick and easy adaptation. Our contribution in this regard is constructing a Digital Twin by leveraging various modelling techniques to realistically represent the above mentioned aspects of interest that can be subjected to what-if scenario analysis. We further demonstrate its efficacy using a case study from a large organization. © 2022 Society for Modeling & Simulation International (SCS)

The Distribution of Fecal Contamination in an Urbanized Tropical Lake and Incidence of Acute Diarrheal Disease

Aquatic ecosystems of tropical countries are vulnerable to fecal contamination that could cause spikes in the incidences of acute diarrheal disease (ADD) and challenge public health management systems. Vembanad lake, situated along the southwest coast of India, was monitored for one year (2018-2019). Escherichia coli, an indicator of fecal contamination, was prevalent in the lake throughout the year. Multiple antibiotic resistance among more than 50% of the E. coli isolates adds urgency to the need to control this contamination. The high abundance of E. coli and incidence of ADD were recorded during the early phase of the southwest monsoon (June-July), prior to the once-in-a-century floods that affected the region in the later phase (August). The extent of inundation in the low-lying areas peaked in August, but E. coli in the water peaked in July, suggesting that contamination occurred even prior to extreme flooding. During the COVID-19-related lockdown in March-May 2021, fecal contamination in the lake and incidence of ADD reached minimum values. These results indicate the need for improving sewage treatment facilities and city planning in flood-prone areas to avoid the mixing of septic sewage with natural waters during extreme climate events or even during the normal monsoon. © 2023 American Chemical Society.

Explainable Diagnosis, Lesion Segmentation and Quantification of COVID-19 Infection from CT Images Using Convolutional Neural Networks

The health crisis caused by the COVID-19 pandemic has led to unprecedented research efforts to build AI solutions that can assist healthcare systems. In this work, we propose a novel CNN-based system that detects COVID-19 infection and other pneumonia from CT scans, segments COVID-specific lesions, namely Ground Glass Opacities (GGO) and Consolidations (CL), and computes the percentage of lungs that have been affected by COVID and provides an explanation of the basis in which the diagnosis has been made through the comparison of class activation maps pertaining to the diagnosis with the segmented lesions. This can assist healthcare setups in the rapid contactless screening of COVID-19 and assess the stage and severity of the disease, while also providing some level of transparency on the rationale behind the model's decisions. Based on the initial results of the interpretation of the model's decisions, all the non-lung areas from the CT images were removed using a contour detection-based region of interest (ROI) extraction approach. This was done to prevent the model from making decisions based on details in non-lung areas, which are clinically irrelevant for COVID diagnosis. This is the first work to utilize such a contour detection-based ROI extraction approach for medical images, based on our study. The model has achieved a mean F1 score of 0.87 for multi-label classification (COVID, Common Pneumonia & Normal) and a Dice Similarity Coefficient (DSC) of 0.8066 for lesion segmentation which has exceeded the DSC achieved by 6 out of 7 lesion segmentation models referenced in our study. © 2022 IEEE.

Neutrophil to lymphocyte ratio and C-protein level as markers to predict deterioration in stable COVID-19 patients

The new Corona virus disease (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-COV-2). It is a highly communicable infectious disease [1]. Clinical manifestations of COVID-19 vary from asymptomatic to ARDS leading to death, it is important to differentiate between severe and non-severe cases. Early warning signs can be identified by several laboratory tests which are often expensive, time taking. Neutrophil-lymphocyte ratio (NLR), Creactive protein (CRP) are two simple tests that can be used as markers for clinical outcome in COVID-19 patients. The aim and objectives of the study were to correlate patients clinical severity and CRP, NLR levels and to assess direct correlation between CRP levels and NLR. 101 patients who fulfilled the inclusion criteria were taken into the study. Patients are divided into mild, moderate severity based on WHO criteria and CBP, CRP were sent on the 6th/ 7th day of illness. Among the 101 patients, 93 were in mild group, 8 were in moderate group. The study group included subjects who aged between 18 years to 80 years of age. Plasma CRP levels were higher in moderate cases than in mild cases, and this difference was significant (p < 0.001). The mean NLR of moderate severity were significantly higher than those of mild cases (p-0.00003). Results showed that NLR was positively correlated with CRP levels.NLR and CRP are potential, reliable and easy-to-use predictors for deteriorating covid-19 infection. The integration of NLR and CRP may lead to improved predictions and help to triage patients at the time of hospital admission. [ FROM AUTHOR]

A Digital Twin Based Approach For Ensuring Business Continuity Plan And Safe Return To Workplace

Organizations are struggling to ensure business continuity without compromising on delivery excellence in the face of Covid19 pandemic related uncertainties. The uncertainty exists along multiple dimensions such as virus mutations, infectivity and severity of new mutants, efficacy of vaccines against new mutants, waning of vaccine induced immunity over time, and lockdown / opening-up policies effected by city authorities. Moreover, this uncertainty plays out in a non-uniform manner across nations, states, cities, and even within the cities thus leading to highly heterogeneous evolution of pandemic. While Work From Home (WFH) strategy has served well to meet ever-increasing business demands without compromising on individual health safety, there has been an undeniable reduction in social capital. With Covid19 pandemic showing definite waning trends, organizations are considering the possibility of safe transition from WFH to Work From Office (WFO) or a hybrid mode of operation. An effective strategy needs to score equally well on possibly interfering dimensions such as risk of infection, project delivery, and employee wellness. As large organizations will typically have a large number of offices spread across a geography, the problem of arriving at office-specific strategies becomes non-trivial. Moreover, the strategies need to adapt over time to changes that cannot be deduced upfront. This calls for an approach that is amenable to quick and easy adaptation. Our contribution in this regard is constructing a Digital Twin by leveraging various modelling techniques to realistically represent the above mentioned aspects of interest that can be subjected to what-if scenario analysis. We further demonstrate its efficacy using a case study from a large organization. © 2022 SCS.

An ACE2 decoy can be administered by inhalation and potently targets omicron variants of SARS-CoV-2.

Monoclonal antibodies targeting the SARS-CoV-2 spike (S) neutralize infection and are efficacious for the treatment of COVID-19. However, SARS-CoV-2 variants, notably sublineages of B.1.1.529/omicron, have emerged that escape antibodies in clinical use. As an alternative, soluble decoy receptors based on the host entry receptor ACE2 broadly bind and block S from SARS-CoV-2 variants and related betacoronaviruses. The high-affinity and catalytically active decoy sACE22 .v2.4-IgG1 was previously shown to be effective against SARS-CoV-2 variants when administered intravenously. Here, inhalation of aerosolized sACE22 .v2.4-IgG1 increased survival and ameliorated lung injury in K18-hACE2 mice inoculated with P.1/gamma virus. Loss of catalytic activity reduced the decoy's therapeutic efficacy, which was further confirmed by intravenous administration, supporting dual mechanisms of action: direct blocking of S and turnover of ACE2 substrates associated with lung injury and inflammation. Furthermore, sACE22 .v2.4-IgG1 tightly binds and neutralizes BA.1, BA.2, and BA.4/BA.5 omicron and protects K18-hACE2 mice inoculated with a high dose of BA.1 omicron virus. Overall, the therapeutic potential of sACE22 .v2.4-IgG1 is demonstrated by the inhalation route and broad neutralization potency persists against highly divergent SARS-CoV-2 variants.

Detection of Face Mask: A Systematic Approach

The COVID-19 coronavirus pandemic is causing health crises around the world. According to the World Health Organization (WHO), wearing a face mask is an effective means of protection in public places. In most public gatherings such as shopping centers, theaters, parks, it is increasingly necessary to make sure that people in the crowd are wearing masks. Developing an artificial intelligence solution that determines regardless of whether an individual is wearing a cover and letting it in will be great help for the society. In this case, a simple face mask detection system is built using deep learning techniques such as machine learning and persuasive neural network. The model is built with machine learning and OpenCV libraries often used for real-time applications. This model can also be used to develop complete software that scans each person before going to a public meeting © 2022 IEEE.

A national pediatric otolaryngology fellowship virtual dissection course using 3D printed simulators.

OBJECTIVE: Our objective was to create and evaluate a novel virtual platform dissection course to complement pediatric otolaryngology fellowship training in the setting of the COVID-19 pandemic. METHODS: A four-station, four-simulator virtual course was delivered to pediatric otolaryngology fellows virtually using teleconferencing software. The four stations consisted of microtia ear carving, airway graft carving, cleft lip repair, and cleft palate repair. Fellows were asked to complete pre- and post-course surveys to evaluate their procedural confidence, expertise, and attitudes towards the course structure. RESULTS: Statistical analysis of pre-course survey data showed fellows agreed that simulators should play an important part in surgical training (4.59 (0.62)); would like more options for training with simulators (4.31 (0.88)); and would like the option of saving their simulators for later reference (4.41 (0.85)). Fellows found the surgical simulators used in the course to be valuable as potential training tools (3.96 (0.96)), as competency or evaluation tools (3.91 (0.98)), and as rehearsal tools (4.06 (0.93)). Analysis showed a statistically significant improvement in overall surgical confidence in performing all four procedures. CONCLUSION: This virtual surgical dissection course demonstrates 3D printed surgical simulators can be utilized to teach fellows advanced surgical techniques in a low-risk, virtual environment. Virtual platforms are a viable, highly-rated option for surgical training in the setting of restricted in-person meetings and as a mechanism to increase access for fellows by reducing costs and travel requirements during unrestricted periods.

Repurposing of FDA Approved Drugs Against SARS-CoV-2 Papain-Like Protease: Computational, Biochemical, and in vitro Studies.

The pandemic caused by SARS-CoV-2 (SCoV-2) has impacted the world in many ways and the virus continues to evolve and produce novel variants with the ability to cause frequent global outbreaks. Although the advent of the vaccines abated the global burden, they were not effective against all the variants of SCoV-2. This trend warrants shifting the focus on the development of small molecules targeting the crucial proteins of the viral replication machinery as effective therapeutic solutions. The PLpro is a crucial enzyme having multiple roles during the viral life cycle and is a well-established drug target. In this study, we identified 12 potential inhibitors of PLpro through virtual screening of the FDA-approved drug library. Docking and molecular dynamics simulation studies suggested that these molecules bind to the PLpro through multiple interactions. Further, IC50 values obtained from enzyme-inhibition assays affirm the stronger affinities of the identified molecules for the PLpro. Also, we demonstrated high structural conservation in the catalytic site of PLpro between SCoV-2 and Human Coronavirus 229E (HCoV-229E) through molecular modelling studies. Based on these similarities in PLpro structures and the resemblance in various signalling pathways for the two viruses, we propose that HCoV-229E is a suitable surrogate for SCoV-2 in drug-discovery studies. Validating our hypothesis, Mefloquine, which was effective against HCoV-229E, was found to be effective against SCoV-2 as well in cell-based assays. Overall, the present study demonstrated Mefloquine as a potential inhibitor of SCoV-2 PLpro and its antiviral activity against SCoV-2. Corroborating our findings, based on the in vitro virus inhibition assays, a recent study reported a prophylactic role for Mefloquine against SCoV-2. Accordingly, Mefloquine may further be investigated for its potential as a drug candidate for the treatment of COVID.

SPREAD PREDICTION OF COVID-19 IN ANDHRA PRADESH BASED ON ENVIRONMENTAL CHEMISTRY

COVID-19 had already spread throughout the world, and the novel coronavirus continues to pose a threat to the majority of countries. The current study uses the Susceptible-Exposed-Infectious-Recovered idea to assess the effects of social and economic factors, particularly the use of a medical mask, on the spread of COVID-19 in Andhra Pradesh. The influence of environmental parameters such as temperature and relative humidity on the number of COVID-19 cases per day is also investigated using numerical methods such as the Response surface methodology model. We provide the results of the curfew lockdown started by the Government of Andhra Pradesh for COVID-19, as compared to a total lockdown scenario. As a result of the irresponsibility and crowded gatherings, the number of cases increases, stretching the mitigation period of the second wave COVID-19 spread, prolonging the curve's straightening. The Susceptible-Exposed-Infectious-Recovered model's predictions have been put to the test in a number of real-world scenarios. The fast spread of second-wave COVID-19 cases in Indian cities is similarly connected to temperature, as indicated by the well function of higher temperatures in breaking the lipid layer of coronavirus, but is severely inhibited by the critical component of social distancing, leading to uncertainty. As a result, it's critical to incorporate environmental factors into epidemiological models like Susceptible-Exposed-Infectious-Recovered, as well as methodically design managed laboratory tests and modeling experiments to catch conclusive findings, assisting decision-makers and investors in developing comprehensive action plans to combat COVID-19's second wave. © 2022, Rasayan Journal of Chemistry, c/o Dr. Pratima Sharma. All rights reserved.

COVID-19-associated rhino-orbital mucormycosis (CAROM)—a case report

Background: There has been a rapid rise in the number of COVID-19-associated rhino-orbital mucormycosis (CAROM) cases especially in South Asian countries, to an extent that it has been considered an epidemic among the COVID-19 patients in India. As of May 13, 2021, 101 CAROM cases have been reported, of which 82 cases were from India and 19 from the rest of the world. On the other hand, pulmonary mucormycosis associated with COVID-19 has a much lesser reported incidence of only 7% of the total COVID-19-associated mucormycosis cases (Singh AK, Singh R, Joshi SR, Misra A, Diab Metab Syndr: Clin Res Rev, 2021). This case report attempts to familiarize the health care professionals and radiologists with the imaging findings that should alarm for follow-up and treatment in the lines of CAROM. Case presentation: Rhino-orbital mucormycosis (ROM) is a manifestation of mucormycosis that is thought to be acquired by inhalation of fungal spores into the paranasal sinuses. Here, we describe a 55-year-old male, post COVID-19 status with long standing diabetes who received steroids and ventilator therapy for the management of the viral infection. Post discharge from the COVID-19 isolation ICU, the patient complained of grayish discharge from the right nostril and was readmitted to the hospital for the nasal discharge. After thorough radiological and pathological investigation, the patient was diagnosed with CAROM and managed. Conclusion: Uncontrolled diabetes and imprudent use of steroids are both contributing factors in the increased number of CAROM cases. Our report emphasizes on the radiological aspect of CAROM and reinforces the importance of follow-up imaging in post COVID-19 infection cases with a strong suspicion of opportunistic infections.

Greater Covid-19 Severity and Mortality in Hospitalized Patients in Second (Delta Variant) Wave Compared to the First: Single Centre Prospective Study in India (preprint)

Background & ObjectiveCovid-19 pandemic has led to multiple waves secondary to mutations in SARS-CoV-2 and emergence of variants of concern (VOC). Clinical characteristics of delta (B.1.617.2) VOC are not well reported. To compare demographic, clinical and laboratory features and outcomes in the second Covid-19 wave in India (delta VOC) with the previous wave we performed a registry-based study. MethodsSuccessive SARS-CoV-2 reverse transcriptase-polymerase chain reaction (RT-PCR) confirmed Covid-19 patients presenting to our Advanced Covid Care hospital were prospectively recruited. In the first phase (wave) from March-December 2020, 1395 of 7476 (18.7%) suspected patients tested positive and 863 (61.89%) hospitalized, while in second wave from January-July 2021 out of 1641 confirmed cases out of 8680 (19.4%) suspected 388 (23.6%) were hospitalized. Details of clinical and laboratory features at admission to hospital, management and outcomes in the two waves have been compared. ResultsIn both cohorts, majority were men and 20% less than 40 years. Prevalence of hypertension, diabetes and cardiovascular diseases was more than 20%. Second wave patients had similar pre-hospitalization symptom duration but had significantly greater cough, fever and shortness of breath and lower SpO2 at presentation with greater lymphopenia, C-reactive proteins, interleukin-6, ferritin, lactic dehydrogenase and transaminases. In the second vs first wave patients, requirement of supplementary oxygen (47.9% vs 34.3%), prone positioning (89.2 vs 38.6%), high flow nasal oxygen(15.7 vs 9.1%), non-invasive ventilation (14.4 vs 9.5%), invasive ventilation (16.2 vs 9.5%), steroids (94.1 vs 85.9%), remdesivir (91.2 vs 76.0%) and anticoagulants (94.3 vs 76.0%) was greater (p<0.001). Median (IQR) length of stay [8 (6-10) vs 7 (5-10) days] as well as ICU stay [9 (5-13) vs 6 (2-10) days] was more in second wave (p<0.001). In-hospital deaths occurred in 173 patients (13.9%) and were significantly more in the second wave, 75 (19.3%), compared to the first, 98 (11.5%); unadjusted odds ratio (95% CI) 1.84 (1.32-2.55) which did not change significantly with adjustment for age and sex (2.03, 1.44-2.86), and age, sex and comorbidities (2.09, 1.47-2.95). Greater disease severity at presentation was associated with mortality in both the waves. ConclusionsCovid-19 patients hospitalized during the second wave of the epidemic (delta variant) had more severe disease with greater dyspnea, hypoxia, hematological and biochemical abnormalities compared to first wave patients. They had greater length of stay in intensive care unit, oxygen requirement, non-invasive and invasive ventilatory support. The in-hospital mortality in the second wave was double of the first.

Possible Insights into the Use of Silver Nanoparticles in Targeting SARS-CoV-2 (COVID-19)

Aim: The aims of this review are to assess the anti-viral and targeting strategies using nano materials and the possibility of using Silver nanoparticles for combating the SARS-CoV-2. Background: The novel Coronavirus (SARS-CoV-2) has become a global pandemic and has spread rapidly worldwide. Researchers have successfully identified the molecular structure of the novel coronavirus however significant success has not yet been observed with the therapies currently in clinical trials and exhaustive studies are yet to be carried out in the long road to discovery of a vaccine or a possible cure. Another hurdle associated with the discovery of a cure is the mutation of this virus which may occur at any point in time. Hypothesis: Previous studies have identified a wide number of strains of Coronaviruses with differences in virulent properties. Silver nanoparticles have been used extensively in anti-viral research with promising results in-vitro. However, it has not yet been tested for the same in clinical subjects. It has also been tested on two variants of coronavirus in-vitro with significant data to understand the pathogenesis and which may be implemented in further research possibly in other variants of coronavirus. Another interesting targeting approach would be to test the effect of Silver Nanoparticles on TNF-alpha as well as Interleukins in SARS-CoV-2 patients. Conclusion: Sufficient evidence is required for its therapeutic potential and it still has to go a long way in SARS-CoV-2 research.

Fibonacci transform algorithm for encryption and decryption of covid images

Picture encryption is a powerful strategy to ensure pictures or recordings by moving them into unrecognizable formats for various security purposes. In this paper, Fibonacci Algorithm for Covid pictures encryption and Discrete wavelet change based Orthogonal Frequency Division Multiplexing for transmission and gathering is proposed. This paper presents execution of Fibonacci Algorithm for picture encryption and Discrete wavelet change based Orthogonal Frequency Division Multiplexing handset utilizing Discrete wavelet transform using Field Programmable Gate Array. © 2021 Karadeniz Technical University. All rights reserved.

An engineered decoy receptor for SARS-CoV-2 broadly binds protein S sequence variants.

The spike S of SARS-CoV-2 recognizes ACE2 on the host cell membrane to initiate entry. Soluble decoy receptors, in which the ACE2 ectodomain is engineered to block S with high affinity, potently neutralize infection and, because of close similarity with the natural receptor, hold out the promise of being broadly active against virus variants without opportunity for escape. Here, we directly test this hypothesis. We find that an engineered decoy receptor, sACE22v2.4, tightly binds S of SARS-associated viruses from humans and bats, despite the ACE2-binding surface being a region of high diversity. Saturation mutagenesis of the receptor-binding domain followed by in vitro selection, with wild-type ACE2 and the engineered decoy competing for binding sites, failed to find S mutants that discriminate in favor of the wild-type receptor. We conclude that resistance to engineered decoys will be rare and that decoys may be active against future outbreaks of SARS-associated betacoronaviruses.

Impact of lockdown during COVID-19 pandemic and its advantages

COVID-19, caused by novel coronavirus SARCoV2, is a contagious disease, emerged in the end of December 2019, at Wuhan seafood market, China. This disease is spiraling like a wildfire and rapidly spreading worldwide, overburdening the health system with newly infected cases. As of April 25, 2020, a total of 2,846,536 COVID-19-positive cases and 197,859 total deaths were reported across the globe. This epidemic has exponential growth characteristics in the absence of specific vaccine and treatment for COVID-19. Many countries across the world including India, the USA, China, Italy, and German are implementing the lockdown measures to control the COVID-19 pandemic and to maintain the infection at manageable levels. Keeping the prospectus of future such pandemics, we reviewed;what is lockdown and containment? Does it works? What are the advantages of lockdown and containment in cotrolling the spread of the virus?. The present review answers these questions and tries to spread light on the impact of lockdown. Our review concludes that the implementation of lockdown has forced many countries in flattening the epidemic curve and strengthening the health-care system and improves the environmental quality during the COVID-19 pandemic.

An engineered decoy receptor for SARS-CoV-2 broadly binds protein S sequence variants (preprint)

The spike S of SARS-CoV-2 recognizes ACE2 on the host cell membrane to initiate entry. Soluble decoy receptors, in which the ACE2 ectodomain is engineered to block S with high affinity, potently neutralize infection and, due to close similarity with the natural receptor, hold out the promise of being broadly active against virus variants without opportunity for escape. Here, we directly test this hypothesis. We find an engineered decoy receptor, sACE22.v2.4, tightly binds S of SARS-associated viruses from humans and bats, despite the ACE2-binding surface being a region of high diversity. Saturation mutagenesis of the receptor-binding domain followed by in vitro selection, with wild type ACE2 and the engineered decoy competing for binding sites, failed to find S mutants that discriminate in favor of the wild type receptor. We conclude that resistance to engineered decoys will be rare and that decoys may be active against future outbreaks of SARS-associated betacoronaviruses.

Stakeholders’ views regarding macro-environment impacts on commercial flight operations in South Africa

Background: Worldwide, the aviation industry facilitates the efficient movement of passengers and goods across borders to support economic access to various local, regional and international markets. As an indirect stimulus for other economies, the aviation industry is known for distinct economic competitiveness, low profit margins and vulnerability to macro-environment fluctuations. Although many studies have focused specifically on scheduled airline’s operations, this study of commercial flight operations in South Africa encompasses both airline operations and charter/on-demand operations. Objectives: The key research objective was to critically review stakeholders’ perceptions on the macro-environment’s influences on the flight operations subsector of South African aviation industry. Method: As research methodology to explore manifest and latent meaning in dialogue, qualitative content analysis was employed in this study. Data were collected through interviews with the stakeholders of South African aviation industry and analysed using qualitative content analysis. Results: This study revealed stakeholders’ views on the effects of political, economic, sociocultural, technological, legal and ecological (PESTLE) framework embedded in the macro-environment of commercial flight operations in South Africa. Conclusion: Although the macro-environment is uncontrollable by the industry, each of the PESTLE framework’s dimensions presents challenges as well as growth opportunities. Continuous monitoring and a comprehensive understanding of the probable impacts of the macro-environment are necessary to remain competitive.