Competitive fitness and homologous recombination of SARS-CoV-2 variants of concern (preprint)

SARS-CoV-2 variants continue to emerge and cocirculate in humans and wild animals. The factors driving the emergence and replacement of novel variants and recombinants remain incompletely understood. Herein, we comprehensively characterized the competitive fitness of SARS-CoV-2 wild type (WT) and three variants of concern (VOCs), Alpha, Beta and Delta, by coinfection and serial passaging assays in different susceptible cells. Deep sequencing analyses revealed cell-specific competitive fitness: the Beta variant showed enhanced replication fitness during serial passage in Caco-2 cells, whereas the WT and Alpha variant showed elevated fitness in Vero E6 cells. Interestingly, a high level of neutralizing antibody sped up competition and completely reshaped the fitness advantages of different variants. More importantly, single clone purification identified a significant proportion of homologous recombinants that emerged during the passage history, and immune pressure reduced the frequency of recombination. Interestingly, a recombination hot region located between nucleotide sites 22995 and 28866 of the viral genomes could be identified in most of the detected recombinants. Our study not only profiled the variable competitive fitness of SARS-CoV-2 under different conditions, but also provided direct experimental evidence of homologous recombination between SARS-CoV-2 viruses, as well as a model for investigating SARS-CoV-2 recombination.

Retirement Expectations vs. Reality: Factors that Impact Retirement Decisions (preprint)

Using two data sets (Prudential Financial Wellness Survey, and Health and Retirement Study), this study demonstrates that although there is generally a natural upward trend for older (age 50+) Americans to progressively delay their expected retirement, this trend has no statistically significant relationship with the COVID-19 pandemic. The distribution of older Americans’ expected retirement ages is bimodal, often centered around two Social Security Benefit claiming ages – the early retirement age and full retirement age. However, their actual retirement ages are more likely to follow a left-skewed (retire earlier) distribution. The most significant factors influencing participants’ retirement decisions relative to expectations are health, wealth, age, marital status change, mortality expectations, education levels, disability, and major illness diagnosis. Focusing on these factors can help the retirement benefits community explore strategies to mitigate the negative consequences of gaps between retirement expectations and reality.

Analysis of COVID-19 Guideline Quality and Change of Recommendations: A Systematic Review

Background Hundreds of coronavirus disease 2019 (COVID-19) clinical practice guidelines (CPGs) and expert consensus statements have been developed and published since the outbreak of the epidemic. However, these CPGs are of widely variable quality. So, this review is aimed at systematically evaluating the methodological and reporting qualities of COVID-19 CPGs, exploring factors that may influence their quality, and analyzing the change of recommendations in CPGs with evidence published. Methods We searched five electronic databases and five websites from 1 January to 31 December 2020 to retrieve all COVID-19 CPGs. The assessment of the methodological and reporting qualities of CPGs was performed using the AGREE II instrument and RIGHT checklist. Recommendations and evidence used to make recommendations in the CPGs regarding some treatments for COVID-19 (remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir) were also systematically assessed. And the statistical inference was performed to identify factors associated with the quality of CPGs. Results We included a total of 92 COVID-19 CPGs developed by 19 countries. Overall, the RIGHT checklist reporting rate of COVID-19 CPGs was 33.0%, and the AGREE II domain score was 30.4%. The overall methodological and reporting qualities of COVID-19 CPGs gradually improved during the year 2020. Factors associated with high methodological and reporting qualities included the evidence-based development process, management of conflicts of interest, and use of established rating systems to assess the quality of evidence and strength of recommendations. The recommendations of only seven (7.6%) CPGs were informed by a systematic review of evidence, and these seven CPGs have relatively high methodological and reporting qualities, in which six of them fully meet the Institute of Medicine (IOM) criteria of guidelines. Besides, a rapid advice CPG developed by the World Health Organization (WHO) of the seven CPGs got the highest overall scores in methodological (72.8%) and reporting qualities (83.8%). Many CPGs covered the same clinical questions (it refers to the clinical questions on the effectiveness of treatments of remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir in COVID-19 patients) and were published by different countries or organizations. Although randomized controlled trials and systematic reviews on the effectiveness of treatments of remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir for patients with COVID-19 have been published, the recommendations on those treatments still varied greatly across COVID-19 CPGs published in different countries or regions, which may suggest that the CPGs do not make sufficient use of the latest evidence. Conclusions Both the methodological and reporting qualities of COVID-19 CPGs increased over time, but there is still room for further improvement. The lack of effective use of available evidence and management of conflicts of interest were the main reasons for the low quality of the CPGs. The use of formal rating systems for the quality of evidence and strength of recommendations may help to improve the quality of CPGs in the context of the COVID-19 pandemic. During the pandemic, we suggest developing a living guideline of which recommendations are supported by a systematic review for it can facilitate the timely translation of the latest research findings to clinical practice. We also suggest that CPG developers should register the guidelines in a registration platform at the beginning for it can reduce duplication development of guidelines on the same clinical question, increase the transparency of the development process, and promote cooperation among guideline developers all over the world. Since the International Practice Guideline Registry Platform has been created, developers could register guidelines prospectively and internationally on this platform.

Identify the natural and socio-economic influencing factors of the new coronavirus pneumonia（COVID-19） incidence rates in Chinese cities

This study explored the effects of both natural and socio-economic factors, such as city size and healthcare capacity, on the spreading of COVID-19 in China's urban population from January 1 to March 5, 2020. Several statistical models and machine learning methods were used to identify the key determinants of the incidence rate of COVID-19. Based on the interpretable machine learning framework, possible nonlinear relationships between incidences and key impact factors were explored. The results showed that the incidence rate of COVID-19 in cities was influenced by several factors simultaneously. Among the factors, the population inflow rate from Wuhan was the factor that showed the highest correlation coefficient（0.43）, followed by the population growth rate（0.38）. Population migration size, city size and healthcare capacity were the key influencing factors. Nonlinear relationships existed between the key influencing factors and incidence rates. To be specific, the inflow rate from Wuhan had a S-shaped relationship and reaches an asymptote after 2%;the population density had an approximately linear relationship;the per capita GDP showed an evident inverted U curve with the per capita GDP over 100,000 yuan as the inflection point. City development needs to pay more attention to population density control and economic growth in order to bring more health benefits.

Protection Duration of COVID-19 Vaccines: Waning Effectiveness and Future Perspective

The coronavirus disease 2019 (COVID-19) vaccines have very successfully decreased the disease risk as we know;some key information remains unknown due to the short development history and the lack of long-term follow-up studies in vaccinated populations. One of the unanswered issues is the protection duration conferred after COVID-19 vaccination, which appears to play a pivotal role in the future impact of pathogens and is critical to inform the public health response and policy decisions. Here, we review current information on the long-term effectiveness of different COVID-19 vaccines, persistence of immunogenicity, and gaps in knowledge. Meanwhile, we also discuss the influencing factors and future study prospects on this topic.

Joint Optimization Decision of Online Retailers’ Pricing and Live-Streaming Effort in the Postepidemic Era

The isolation requirements of the coronavirus epidemic and the intuitive display advantages of live-streaming have led to an increasing number of retailers shifting to social live-streaming platforms and e-commerce live-streaming platforms to promote and sell their products in real time. However, the provision of live-streaming services will also incur high live-streaming effort costs. In this paper, we develop two decision models for retailers to sell goods through a single online shop and both online shop and live-streaming room;we also present the optimal decisions of pricing and live-streaming efforts. Furthermore, we identify the profitability conditions for retailers to determine when to provide live-streaming services. In addition, we examine the impact of the provision of live-streaming services on the optimal price and live-streaming effort. We obtain three findings. First, there is a unique optimal decision on the price and live-streaming effort under certain conditions. Second, when the effect coefficient of the live-streaming room reaches a certain threshold, there are enough customers who enter the live-streaming room to watch and buy and it is profitable for retailers to provide live-streaming service. Finally, the optimal price and live-streaming effort increase with the increase in average return loss, the effect coefficient of live-streaming effort, and the extra return rate and decrease with the increase in the proportion of customers who choose to buy in the online shop and the price discount coefficient in the live-streaming room.

Broad neutralizing nanobody against SARS-CoV-2 engineered from pre-designed synthetic library (preprint)

SARS-CoV-2 infection is initiated with Spike glycoprotein binding to the receptor of human angiotensin converting enzyme 2 via its receptor binding domain. Blocking this interaction is considered as an effective approach to inhibit virus infection. Here we report the discovery of a neutralizing nanobody, VHH60, directly produced from a humanized synthetic nanobody library. VHH60 competes with human ACE2 to bind the receptor binding domain of the Spike protein with a KD of 2.56 nM, inhibits infections of both live SARS-CoV-2 and pseudotyped viruses harboring wildtype, escape mutations and prevailing variants at nanomolar level. VHH60 also suppresses SARS-CoV-2 infection and propagation 50-fold better and protects mice from death two times longer than that of control group after live virus inoculation on mice. VHH60 therefore is a powerful synthetic nanobody with a promising profile for disease control against COVID19.

Multi-Dimensional Reduction Clustering of Complex Carbohydrates Reveal Tissue Metabolism, Heterogeneity and Histopathology (preprint)

Formalin-fixed paraffin-embedded (FFPE) human tissues represent the world's largest collection of accessible clinical specimens with matched, well-annotated clinical course for disease progression. Currently, FFPE sections are limited to low throughput histo- and immunological assessments. Extracting largescale molecular information remains a major technological barrier to uncover the vast potential within FFPE specimens for translation and clinical research. Two critical but understudied facets of glucose metabolism are anabolic pathways for glycogen and N-linked glycan biosynthesis. Together, these complex carbohydrates represent bioenergetics, protein-structure function, and tissue architecture in human biology. Herein, we report the high-dimensional Metabolomics-Assisted Digital pathology Imaging (Madi) workflow that combines matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) with machine learning for the comprehensive assessment of tissue heterogeneity, histopathology, and metabolism in human FFPE sections. In normal human tissue sections, Madi accurately identifies anatomical regions within liver and the brain. In human lung diseases, Madi accurately predicts major lung pathologies such as honeycomb change, late-stage fibrosis, diffuse alveolar damage (DAD), and acute fibrinous and organizing pneumonia (AFOP) from idiopathic pulmonary fibrosis (IPF) and COVID-19 pneumonia specimens with precision. In depth pathway enrichment analyses reveal unique metabolic pathways are associated with distinct pathological regions, which highlight aberrant complex carbohydrate metabolism as a previously unknown molecular event associated with disease progression that could hold key to future therapeutic interventions.

A Transferable Deep Learning Approach to Fast Screen Potent Antiviral Drugs against SARS-CoV-2 (preprint)

The COVID-19 pandemic calls for rapid development of effective treatments. Although various drug repurpose approaches have been used to screen the FDA-approved drugs and drug candidates in clinical phases against SARS-CoV-2, the coronavirus that causes this disease, no magic bullets have been found until now. We used directed message passing neural network to first build a broad-spectrum anti-beta-coronavirus compound prediction model, which gave satisfactory predictions on newly reported active compounds against SARS-CoV-2. Then we applied transfer learning to fine-tune the model with the recently reported anti-SARS-CoV-2 compounds. The fine-tuned model was applied to screen a large compound library with 4.9 million drug-like molecules from ZINC15 database and recommended a list of potential anti-SARS-CoV-2 compounds for further experimental testing. As a proof-of-concept, we experimentally tested 7 high-scored compounds that also demonstrated good binding strength in docking study against the 3C-like protease of SARS-CoV-2 and found one novel compound that inhibited the enzyme with an IC50 of 37.0 M. Our model is highly efficient and can be used to screen large compound databases with billions or more compounds to accelerate the drug discovery process for the treatment of COVID-19.

Scutellaria baicalensis extract and baicalein inhibit replication of SARS-CoV-2 and its 3C-like protease in vitro (preprint)

COVID-19 has become a global pandemic that threatens millions of people worldwide. There is an urgent call for developing effective drugs against the virus (SARS-CoV-2) causing this disease. The main protease of SARS-CoV-2, 3C-like protease (3CLpro), is highly conserved across coronaviruses and is essential for the maturation process of viral polyprotein. Scutellariae radix (Huangqin in Chinese), the root of Scutellaria baicalensis has been widely used in traditional Chinese medicine to treat viral infection related symptoms. The extracts of S. baicalensis have exhibited broad spectrum antiviral activities. We studied the anti-SARS-CoV-2 activity of S. baicalensis and its ingredient compounds. We found that the ethanol extract of S. baicalensis inhibits SARS-CoV-2 3CLpro activity in vitro and the replication of SARS-CoV-2 in Vero cells with an EC50 of 0.74 g/ml. Among the major components of S. baicalensis, baicalein strongly inhibits SARS-CoV-2 3CLpro activity with an IC50 of 0.39 M. We further identified four baicalein analogue compounds from other herbs that inhibit SARS-CoV-2 3CLpro activity at microM concentration. Our study demonstrates that the extract of S. baicalensis has effective anti-SARS-CoV-2 activity and baicalein and analogue compounds are strong SARS-CoV-2 3CLpro inhibitors.