Potential of conserved antigenic sites in development of universal SARS-like coronavirus vaccines

Given pandemic risks of zoonotic SARS-CoV-2 variants and other SARS-like coronaviruses in the future, it is valuable to perform studies on conserved antigenic sites to design universal SARS-like coronavirus vaccines. By using antibodies obtained from convalescent COVID-19 patients, we succeeded in functional comparison of conserved antigenic sites at multiple aspects with each other, and even with SARS-CoV-2 unique antigenic sites, which promotes the cognition of process of humoral immune response to the conserved antigenic sites. The conserved antigenic sites between SARS-CoV-2 and SARS-CoV can effectively induce affinity maturation of cross-binding antibodies, finally resulting in broadly neutralizing antibodies against multiple variants of concern, which provides an important basis for universal vaccine design, however they are subdominant, putatively due to their lower accessibility relative to SARS-CoV-2 unique antigenic sites. Furthermore, we preliminarily design RBDs to improve the immunogenicity of these conserved antigenic sites. Our study focusing on conserved antigenic sites provides insights for promoting the development of universal SARS-like coronavirus vaccines, thereby enhancing our pandemic preparedness.

Could Social Bots' Sentiment Engagement Shape Humans' Sentiment on COVID-19 Vaccine Discussion on Twitter?

During the COVID-19 pandemic, social media has become an emerging platform for the public to find information, share opinions, and seek coping strategies. Vaccination, one of the most effective public health interventions to control the COVID-19 pandemic, has become the focus of public online discussions. Several studies have demonstrated that social bots actively involved in topic discussions on social media and expressed their sentiments and emotions, which affected human users. However, it is unclear whether social bots' sentiments affect human users' sentiments of COVID-19 vaccines. This study seeks to scrutinize whether the sentiments of social bots affect human users' sentiments of COVID-19 vaccines. The work identified social bots and built an innovative computational framework, i.e., the BERT-CNN sentiment analysis framework, to classify tweet sentiments at the three most discussed stages of COVID-19 vaccines on Twitter from December 2020 to August 2021, thus exploring the impacts of social bots on online vaccine sentiments of humans. Then, the Granger causality test was used to analyze whether there was a time-series causality between the sentiments of social bots and humans. The findings revealed that social bots can influence human sentiments about COVID-19 vaccines. Their ability to transmit the sentiments on social media, whether in the spread of positive or negative tweets, will have a corresponding impact on human sentiments.

Mind the feline coronavirus: comparison with SARS-CoV-2

Both feline coronavirus (FCoV) and SARS-CoV-2 are coronaviruses that infect cats and humans, respectively. However, cats have been shown to be susceptible to SARS-CoV-2, and FCoV also had been shown to infect human. To elucidate the relationship between FCoV and SARS-CoV-2, we highlight the main characteristics of the genome, the receptor usage, and the correlation of the receptor-binding domain (RBD) of spike proteins in FCoV and SARS-CoV-2. It is demonstrated that FCoV and SARS-CoV-2 are closely related to the main characteristics of the genome, receptor usage, and RBD of spike proteins with similar furin cleavage sites. In particular, the affinity of the conserved feline angiotensin-converting enzyme 2 (fACE2) receptor to the RBD of SARS-CoV-2 suggests that cats are susceptible to SARS-CoV-2. In addition, cross-species of coronaviruses between cats and humans or other domesticated animals are also discussed. This review sheds light on cats as potential intermediate hosts for SARS-CoV-2 transmission, and cross-species transmission or zoonotic infection of FCoV and SARS-CoV-2 between cats and humans was identified.

Calculus of Consent via MARL: Legitimating the Collaborative Governance Supplying Public Goods (preprint)

Public policies that supply public goods, especially those involve collaboration by limiting individual liberty, always give rise to controversies over governance legitimacy. Multi-Agent Reinforcement Learning (MARL) methods are appropriate for supporting the legitimacy of the public policies that supply public goods at the cost of individual interests. Among these policies, the inter-regional collaborative pandemic control is a prominent example, which has become much more important for an increasingly inter-connected world facing a global pandemic like COVID-19. Different patterns of collaborative strategies have been observed among different systems of regions, yet it lacks an analytical process to reason for the legitimacy of those strategies. In this paper, we use the inter-regional collaboration for pandemic control as an example to demonstrate the necessity of MARL in reasoning, and thereby legitimizing policies enforcing such inter-regional collaboration. Experimental results in an exemplary environment show that our MARL approach is able to demonstrate the effectiveness and necessity of restrictions on individual liberty for collaborative supply of public goods. Different optimal policies are learned by our MARL agents under different collaboration levels, which change in an interpretable pattern of collaboration that helps to balance the losses suffered by regions of different types, and consequently promotes the overall welfare. Meanwhile, policies learned with higher collaboration levels yield higher global rewards, which illustrates the benefit of, and thus provides a novel justification for the legitimacy of, promoting inter-regional collaboration. Therefore, our method shows the capability of MARL in computationally modeling and supporting the theory of calculus of consent, developed by Nobel Prize winner J. M. Buchanan.

The adenosine analogue prodrug ATV006 is orally bioavailable and has potent preclinical efficacy against SARS-CoV-2 and its variants (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the COVID-19 pandemic, is rapidly evolving. Due to the limited efficacy of vaccination in prevention of SARS-CoV-2 transmission and continuous emergence of variants of concern (VOC), including the currently most prevalent Delta variant, orally bioavailable and broadly efficacious antiviral drugs are urgently needed. Previously we showed that adenosine analogue 69-0 (also known as GS-441524), possesses potent anti-SARS-CoV-2 activity. Herein, we report that esterification of the 5-hydroxyl moieties of 69-0 markedly improved the antiviral potency. The 5-hydroxyl -isobutyryl prodrug, ATV006, showed excellent oral bioavailability in rats and cynomolgus monkeys and potent antiviral efficacy against different VOCs of SARS-CoV-2 in cell culture and three mouse models. Oral administration of ATV006 significantly reduced viral loads, alleviated lung damage and rescued mice from death in the K18-hACE2 mouse model challenged with the Delta variant. Moreover, ATV006 showed broad antiviral efficacy against different mammal-infecting coronaviruses. These indicate that ATV006 represents a promising oral drug candidate against SARS-CoV-2 VOCs and other coronaviruses.

Air quality in Nanjing during COVID-19 lockdown period

In order to investigate the impact of COVID-19 lockdown on air quality in Nanjing, the air pollutants observed from January 25 to February 10, in 2020（COVID-19 lockdown period） in Nanjing and its surrounding cities was analyzed. During the lockdown period with poor atmospheric diffusion conditions, the concentrations of PM2.5, PM10, NO2, SO2, and CO decreased obviously, with the value of 36, 44, 5, 22μg/m3 and 1.1 mg/m3, whereasO3 increased by 4%. The net effectiveness of the emission reduction measures was calculated through comparisons of concentrations of air pollutants between and before COVID in the similar meteorological conditions. Concentrations of PM2.5, PM10, SO2, NO2 and CO decreased by 41.7%, 45.3%, 14.3%, 43.5% and 18.2%, respectively, whereasO3 increased by 4.8%. Compared to capital cities of the Yangtze River Delta in the same period, the largest decline of SO2 and the medium decline of the other pollutions were appeared in Nanjing. The diurnal variation concentration of PM2.5 and PM10 changed from double peak to single peak, due to the disappearance of nighttime sub-peak of particle. The concentration ofO3 increased significantly at night, which was resulted from that sharp reduction of traffic sources weaken the titration reaction of NO toO3. The peak ofO3 during the daytime depended on the variation of the ratio of VOCs to NOx due to the emission control.

Not-so-straightforward links between believing in COVID-19-related conspiracy theories and engaging in disease-preventive behaviours

Since the start of the COVID-19 pandemic, pertinent conspiracy theories have proliferated online, raising the question: How might believing in those conspiracy theories be linked with engagement in disease-preventive behaviours? To answer this, we conducted a repeated cross-sectional survey of around 1500 respondents to examine the link between conspiracy-theory beliefs and disease-preventive behaviours across six time-points in the United States from early February to late March 2020. The findings reveal that believing in risk-acceptance conspiracy theories (RA-CTs;e.g., “COVID-19 is a man-made bioweapon”) was linked to more preventive behaviours. However, believing in risk-rejection conspiracy theories (RR-CTs;e.g., “COVID-19 is like influenza and was purposefully exaggerated”) was associated with fewer preventive behaviours. These differential links were mediated by risk perception and negative emotions and modulated by the stage of the outbreak—RA-CTs predicted higher risk perception in the mild stage, whereas RR-CTs predicted lower risk perception in the severe stage.