Distal Protein-Protein Interactions Contribute to SARS-CoV-2 Main Protease Substrate Binding and Nirmatrelvir Resistance (preprint)

SARS-CoV-2 main protease, Mpro, is responsible for the processing of the viral polyproteins into individual proteins, including the protease itself. Mpro is a key target of anti-COVID-19 therapeutics such as nirmatrelvir (the active component of Paxlovid). Resistance mutants identified clinically and in viral passage assays contain a combination of active site mutations (e.g. E166V, E166A, L167F), which reduce inhibitor binding and enzymatic activity, and non-active site mutations (e.g. P252L, T21I, L50F), which restore the fitness of viral replication. Although the mechanism of resistance for the active site mutations is apparent, the role of the non-active site mutations in fitness rescue remains elusive. In this study, we use the model system of a Mpro triple mutant (L50F/E166A/L167F) that confers not only nirmatrelvir drug resistance but also a similar fitness of replication compared to the wild-type both in vitro and in vivo. By comparing peptide and full-length Mpro protein as substrates, we demonstrate that the binding of Mpro substrate involves more than residues in the active site. In particular, L50F and other non-active site mutations can enhance the Mpro dimer-dimer interactions and help place the nsp5-6 substrate at the enzyme catalytic center. The structural and enzymatic activity data of Mpro L50F, L50F/E166A/L167F, and others underscore the importance of considering the whole substrate protein in studying Mpro and substrate interactions, and offers important insights into Mpro function, resistance development, and inhibitor design.

Orphanhood and caregiver death among children in the United States due to all-cause mortality 2000-2021: A Modeling Study (preprint)

Importance: Deaths of parents and grandparent caregivers linked to social and health crises threaten child wellbeing due to losses of nurturance, financial support, physical safety, family stability, and care. Little is known about the full burden of all-causes and leading cause-specific orphanhood and caregiver death beyond estimates from select causes. Objective: To estimate 2000-2021 prevalence and incidence trends of all-cause orphanhood and caregiver death among children <18, by cause, age, race/ethnicity, and state. Data Sources: National Center for Health Statistics (NCHS) birth, death, race/ethnicity, and population data to estimate fertility rates and identify causes of death; 1983-1998 ICD-9 causes-of-death harmonized to ICD-10 classifications; 1999-2021 ICD-10 causes-of-death; CDC WONDER for state-specific estimates; and American Community Survey for grandparent population estimates. Data extraction and synthesis: We extracted U.S. population-level death, birth, population size, race, and ethnicity data from NCHS and attributed to each deceased individual the average number of children left behind according to subgroup-specific fertility rates in the previous 0-17 years. We examined prevalence and incidence of orphanhood by leading causes-of-death, including COVID-19, the leading 5 causes-of-death for 1983-2021, and additional leading causes for ages 15-44. We extended these to obtain state-level outcome estimates. Main outcome measures: National incidence and prevalence of orphanhood and caregiver death from 2000-2021, with orphanhood by year, parental cause-of-death and sex, child age, race/ethnicity, and state. Results: From 2000-2021, orphanhood and custodial/co-residing grandparent caregiver loss annual incidence and prevalence trends increased 49.2% and 8.3%, respectively. By 2021, 2.9 million children (4% of all children) had experienced prevalent orphanhood and caregiver death. Populations disproportionately affected by orphanhood included 5.0% of all adolescents; 6.5%, 4.8%, and 3.9% respectively of non-Hispanic American Indian/Alaska Native, non-Hispanic Black, and non-Hispanic White children; and children in New Mexico and Southern and Eastern States. Parental death due to drug overdose during 2020-2021 surpassed COVID-19 as the leading cause of incident and prevalent orphanhood during the COVID-19 pandemic. Conclusions and Relevance: Policies, programs, and practices aimed at orphanhood prevention, identification, and linkage to services and support of nearly 3 million bereaved children are needed, foremost prioritizing rapidly increasing overdose-linked orphanhood.

Clinical and Immunological Characteristics in COVID-19 Convalescent Patients (preprint)

Objective: The immune responses of COVID-19 convalescent patients have not been well described. Methods Blood from thirty COVID-19 convalescent patients who were virus-free were collected. Their clinical laboratory findings and SARS-CoV-2-specific humoral and cellular immunity were detected. Results At 283 days after diagnosis of SARS-CoV-2 infection, the levels of clinical laboratory indicators and lymphocyte subtypes returned to normal levels. However, the ratio of memory/naive CD4+ T lymphocytes cells was greater in COVID-19 convalescent patients and severe COVID-19 convalescent patients, when compared with that in healthy blood donors (P=0.0135) and non-severe patients (P=0.0431), respectively. The levels of anti-SARS-CoV-2-IgM (P=0.014), S1-IgM (P=0.0004) and RBD-IgM (P=0.0002) in severe COVID-19 patients were all significantly greater than those in non-severe COVID-19 patients. When the serums of COVID-19 convalescent patients were diluted as 1:125, the predictive of serum neutralization capabilities were persistent in all patients. SARS-CoV-2-specific T cells were generated and maintained in majority of tested convalescent COVID-19 patients, regardless of the severity of disease in acute phase. Conclusion At 283 days after diagnosis of SARS-CoV-2 infection, specific cellular and humoral immunity against SARS-CoV-2 could be detectable. The severity of disease in acute phase cannot affect the strength of cellular and humoral immunity in convalescent phase.

Unveiling the Robustness of Machine Learning Models in Classifying COVID-19 Spike Sequences (preprint)

In the midst of the global COVID-19 pandemic, a wealth of data has become available to researchers, presenting a unique opportunity to investigate the behavior of the virus. This research aims to facilitate the design of efficient vaccinations and proactive measures to prevent future pandemics through the utilization of machine learning (ML) models for decision-making processes. Consequently, ensuring the reliability of ML predictions in these critical and rapidly evolving scenarios is of utmost importance. Notably, studies focusing on the genomic sequences of individuals infected with the coronavirus have revealed that the majority of variations occur within a specific region known as the spike (or S) protein. Previous research has explored the analysis of spike proteins using various ML techniques, including classification and clustering of variants. However, it is imperative to acknowledge the possibility of errors in spike proteins, which could lead to misleading outcomes and misguide decision-making authorities. Hence, a comprehensive examination of the robustness of ML and deep learning models in classifying spike sequences is essential. In this paper, we propose a framework for evaluating and benchmarking the robustness of diverse ML methods in spike sequence classification. Through extensive evaluation of a wide range of ML algorithms, ranging from classical methods like naive Bayes and logistic regression to advanced approaches such as deep neural networks, our research demonstrates that utilizing k-mers for creating the feature vector representation of spike proteins is more effective than traditional one-hot encoding-based embedding methods. Additionally, our findings indicate that deep neural networks exhibit superior accuracy and robustness compared to non-deep-learning baselines. To the best of our knowledge, this study is the first to benchmark the accuracy and robustness of machine-learning classification models against various types of random corruptions in COVID-19 spike protein sequences. The benchmarking framework established in this research holds the potential to assist future researchers in gaining a deeper understanding of the behavior of the coronavirus, enabling the implementation of proactive measures and the prevention of similar pandemics in the future.

The effect of an information intervention on the career commitment of medical students: evidence from a randomized experiment.

Introduction: The needs-based shortage of healthcare workers is severe worldwide and it would be exacerbated if many medical students switch to other careers after graduation. Maintaining and improving the career commitment of medical students, which could be a feasible, effective, and scalable way to reduce the attrition rate, is essential in medical education. We designed a randomized experiment to test whether an information intervention based on role modeling could enhance medical students' career commitment. Methods: In the randomized experiment, the sample (N = 36,482) was divided into the treatment group (N = 18,070) and the control group (N = 18,412). The intervention information consisted of image-text messages on Zhong Nanshan, who is an inspiring role model for he went to the frontline of COVID-19 in the most critical circumstances and received praise and affirmation from the public. Α difference-in-differences model was employed to identify the effect of the information intervention. Heterogeneous treatment effects were identified using sub-sample analyses. Results: The results showed that the information intervention statistically significantly reduced medical students' dropout intention by 2.7 percentage points (95% CI: -0.037 to -0.016, t = -4.95, p < 0.001), equivalent to 14.6% of the control group mean. This estimate indicates that the information intervention could significantly increase the career commitment of medical students. Finally, male and senior students were influenced more than their female and junior counterparts, which can be explained by their relatively high dropout intention. Conclusion: Role model-based information intervention improves the career commitment of medical students. The underlying behavioral model is that, when students use a role model as their reference point, they consider dropout as a substantial welfare loss. Role modeling is an effective way to improve the career commitment of medical students, especially for males and senior students.

The value of probabilistic forecasting in emergency medical resource planning under uncertainty

PurposeMost epidemic transmission forecasting methods can only provide deterministic outputs. This study aims to show that probabilistic forecasting, in contrast, is suitable for stochastic demand modeling and emergency medical resource planning under uncertainty.Design/methodology/approachTwo probabilistic forecasting methods, i.e. quantile regression convolutional neural network and kernel density estimation, are combined to provide the conditional quantiles and conditional densities of infected populations. The value of probabilistic forecasting in improving decision performances and controlling decision risks is investigated by an empirical study on the emergency medical resource planning for the COVID-19 pandemic.FindingsThe managerial implications obtained from the empirical results include (1) the optimization models using the conditional quantile or the point forecasting result obtain better results than those using the conditional density;(2) for sufficient resources, decision-makers' risk preferences can be incorporated to make tradeoffs between the possible surpluses and shortages of resources in the emergency medical resource planning at different quantile levels;and (3) for scarce resources, the differences in emergency medical resource planning at different quantile levels greatly decrease or disappear because of the existing of forecasting errors and supply quantity constraints.Originality/valueVery few studies concern probabilistic epidemic transmission forecasting methods, and this is the first attempt to incorporate deep learning methods into a two-phase framework for data-driven emergency medical resource planning under uncertainty. Moreover, the findings from the empirical results are valuable to select a suitable forecasting method and design an efficient emergency medical resource plan.

CD4+ T cell calibration of antigen-presenting cells optimizes antiviral CD8+ T cell immunity.

Antiviral CD8+ T cell immunity depends on the integration of various contextual cues, but how antigen-presenting cells (APCs) consolidate these signals for decoding by T cells remains unclear. Here, we describe gradual interferon-α/interferon-ß (IFNα/ß)-induced transcriptional adaptations that endow APCs with the capacity to rapidly activate the transcriptional regulators p65, IRF1 and FOS after CD4+ T cell-mediated CD40 stimulation. While these responses operate through broadly used signaling components, they induce a unique set of co-stimulatory molecules and soluble mediators that cannot be elicited by IFNα/ß or CD40 alone. These responses are critical for the acquisition of antiviral CD8+ T cell effector function, and their activity in APCs from individuals infected with severe acute respiratory syndrome coronavirus 2 correlates with milder disease. These observations uncover a sequential integration process whereby APCs rely on CD4+ T cells to select the innate circuits that guide antiviral CD8+ T cell responses.

COVID-19 relapse associated with SARS-CoV-2 evasion from CD4+ T-cell recognition in an agammaglobulinemia patient

A 25-year-old patient with a primary immunodeficiency lacking immunoglobulin production experienced a relapse after a 239-day period of persistent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Viral genetic sequencing demonstrated that SARS-CoV-2 had evolved during the infection period, with at least five mutations associated with host cellular immune recognition. Among them, the T32I mutation in ORF3a was found to evade recognition by CD4+ T cells. The virus found after relapse showed an increased proliferative capacity in vitro. SARS-CoV-2 may have evolved to evade recognition by CD4+ T cells and increased in its proliferative capacity during the persistent infection, likely leading to relapse. These mutations may further affect viral clearance in hosts with similar types of human leukocyte antigens. The early elimination of SARS-CoV-2 in immunocompromised patients is therefore important not only to improve the condition of patients but also to prevent the emergence of mutants that threaten public health. Graphical

Safety and immunogenicity of a modified COVID-19 mRNA vaccine, SW-BIC-213, as a heterologous booster in healthy adults: an open-labeled, two-centered and multi-arm randomised, phase 1 trial.

BACKGROUND: We assessed the safety and immunogenicity of a core-shell structured lipopolyplex (LPP) based COVID-19 mRNA vaccine, SW-BIC-213, as a heterologous booster in healthy adults. METHODS: We conducted an open-labeled, two-centered, and three-arm randomised phase 1 trial. Healthy adults, who had completed a two-dose of inactivated COVID-19 vaccine for more than six months, were enrolled and randomized to receive a booster dose of COVILO (inactivated vaccine) (n = 20) or SW-BIC-213-25µg (n = 20), or SW-BIC-213-45µg (n = 20). The primary study endpoint was adverse events within 30 days post-boosting. The secondary endpoint was the titers of binding antibodies and neutralizing antibodies against the wild-type (WT) of SARS-CoV-2 as well as variants of concern in serum. The exploratory endpoint was the cellular immune responses. This trial was registered with http://www.chictr.org.cn (ChiCTR2200060355). FINDINGS: Between Jun 6 and Jun 22, 2022, 60 participants were enrolled and randomized to receive a booster dose of SW-BIC-213 (25 µg, n = 20, or 45 µg, n = 20) or COVILO (n = 20). The baseline demographic characteristics of the participants at enrollment were similar among the treatment groups. For the primary outcome, injection site pain and fever were more common in the SW-BIC-213 groups (25 µg and 45 µg). Grade 3 fever was reported in 25% (5/20) of participants in the SW-BIC-213-45µg group but was resolved within 48 h after onset. No fatal events or adverse events leading to study discontinuation were observed. For secondary and exploratory outcomes, SW-BIC-213 elicited higher and longer humoral and cellular immune responses than that in the COVILO group. INTERPRETATION: SW-BIC-213, a core-shell structured lipopolyplex (LPP) based mRNA vaccine, was safe, tolerable, and immunogenic as a heterologous booster in healthy Chinese adults. FUNDING: Shanghai Municipal Government, the Science and Technology and Economic Commission of Shanghai Pudong New Area, and mRNA Innovation and Translation Center of Shanghai.

Single-cell analyses and host genetics highlight the role of innate immune cells in COVID-19 severity.

Mechanisms underpinning the dysfunctional immune response in severe acute respiratory syndrome coronavirus 2 infection are elusive. We analyzed single-cell transcriptomes and T and B cell receptors (BCR) of >895,000 peripheral blood mononuclear cells from 73 coronavirus disease 2019 (COVID-19) patients and 75 healthy controls of Japanese ancestry with host genetic data. COVID-19 patients showed a low fraction of nonclassical monocytes (ncMono). We report downregulated cell transitions from classical monocytes to ncMono in COVID-19 with reduced CXCL10 expression in ncMono in severe disease. Cell-cell communication analysis inferred decreased cellular interactions involving ncMono in severe COVID-19. Clonal expansions of BCR were evident in the plasmablasts of patients. Putative disease genes identified by COVID-19 genome-wide association study showed cell type-specific expressions in monocytes and dendritic cells. A COVID-19-associated risk variant at the IFNAR2 locus (rs13050728) had context-specific and monocyte-specific expression quantitative trait loci effects. Our study highlights biological and host genetic involvement of innate immune cells in COVID-19 severity.

Analysis of Pathogenic Bacteria and Drug Resistance Among Girls with Bacterial Vaginitis.

Objective: The aim of this study was to analyze the prevalence of vaginal flora and drug resistance in bacterial vaginitis among girls. Methods: A total of 3099 girls (0-10 years old) with vaginitis who visited the Beijing Children's Hospital from January 2020 to December 2021 were included in the present study. The clinical data, results of bacterial culture of vaginal secretions, and drug sensitivity reports of the subjects were collected and analyzed. Results: Of the 3099 girls with vaginitis, 399 girls had a positive bacterial culture of vaginal secretions. Nineteen types of bacteria were cultured from the vaginal secretions of these 399 girls, with a total of 419 strains. The top three infective bacteria were Haemophilus influenzae (127 strains, 30.31%), Staphylococcus aureus (66 strains, 15.75%), and Streptococcus agalactiae (32 strains, 7.64%). Additionally, 20 girls were simultaneously infected with two types of bacteria. Staphylococcus aureus, Group G Streptococcus, Haemophilus parainfluenzae, and Pseudomonas aeruginosa more frequently occurred in mixed infections. The number and bacterial detection rate among school-age girls were higher than those of preschool-age girls. We found seasonal variation in infection rates, and vaginitis among girls was higher in summer. Recurrence of vaginitis in girls was not related to the type of pathogenic bacteria in the infection. Drug sensitivity analyses showed that the resistance rates of clindamycin and erythromycin were generally high, 70-100%. After the coronavirus disease 2019 outbreak, the resistance rates of some antibiotics had decreased to varying degrees. Conclusion: Improving the understanding of vaginal flora and drug resistance in girls with vaginitis will facilitate the selection of highly effective and sensitive antibacterial drugs and reduce the production of drug-resistant strains.

Effects of sleep quality on suicide risk in COVID-19 patients: The chain mediating of anxiety and depressive symptoms.

Background: Although current studies have identified sleep disorders as an independent risk factor for suicide, the relationship between sleep disorders and suicide risk has not been well established. This study explored whether anxiety and depressive symptoms are used as mediators to participate in the impact of sleep quality on suicide risk. Methods: This is a cross-sectional study. We administered a psychological questionnaire to the participants, using a combination of self-assessment and psychiatrist assessment.Sleep quality, suicide risk, level of anxiety and depressive symptoms were assessed by PSQI, NGASR, SAS and SDS.The study subjects were 391 hospitalized COVID-19 patients from Wuhan hospitals. We used model 6 in the PROCESS (version 3.5) plug-in of SPSS software to conduct mediation test with sleep quality as the independent variable, suicide risk as the dependent variable, level of anxiety and depressive symptoms as intermediate variables. Results: The severity of anxiety and depressive symptoms and the risk of suicide in the sleep disorder group (63.15 ± 13.71, 59.85 ± 13.38, 6.52 ± 3.67) were higher than those in the non-sleep disorder group (49.83 ± 13.14, 44.87 ± 10.19, 2.87 ± 3.26) (P < 0.001). The mediation model works well, The total indirect effect was 0.22 (95%CI = [0.17, 0.28]), and the direct effect was 0.16 (95%CI = [0.08, 0.24]). Limitations: This study used a self-assessment scale. Conclusions: Anxiety and depressive symptoms played a chain mediating role between sleep quality and suicide risk.

Dynamic changes in the respiratory tract and gut antibiotic resistome of patients with COVID-19 and its association with disease severity (preprint)

Background The antibiotic resistome is the collection of all the antibiotic resistance genes (ARGs) present in an individual. Whether an individual’s susceptibility to infection and the eventual severity of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is influenced by their respiratory tract antibiotic resistome is unknown. Additional, whether a relationship exists between the respiratory tract and gut antibiotic resistance genes composition has not been fully explored. Method We recruited 66 patients with COVID-19 at three disease stages (admission, progression and recovery) and conducted a metagenome sequencing analysis of 143 sputum and 97 fecal samples obtained from them. Respiratory tract, gut metagenomes, and peripheral blood mononuclear cell (PBMC) transcriptomes are analyzed to compare the gut and respiratory tract ARGs of intensive care unit (ICU) and non-ICU (nICU) patients and determine relationships between ARGs and immune response. Results Among the respiratory tract ARGs, we found that Aminoglycoside, Multidrugand Vancomycin are increased in ICU patients compared with nICU patients. In the gut, we found that Multidrug, Vancomycin and Fosmidomycinwere increased in ICU patients. Upon further investigation a significantly positive correlation was found between the relative abundance in ARGs (i.e., subtypes of the Aminoglycoside and Tetracyclinetypes) in the respiratory tract and gut. We discovered that the relative abundances of Multidrug were significantly correlated with clinical indices, and there was a significantly positive correlation between ARGs and microbiota in respiratory tract and gut. We found that immune related pathways in PBMC were enhanced, and they were significantly correlated with the relative abundance of Multidrug, Vancomycin and Tetracycline ARGs. Based on the relative abundance of ARG types, we built a respiratory tract-gut ARG combined random-forest classifier to distinguish ICU COVID-19 patients from nICU patients with an AUC of 0.969. The level of Aminoglycoside and Vancomycinin the gut was regarded as the most prominent biomarker. Conclusions Cumulatively, our findings provide some of the first insights into the dynamic alterations of respiratory tract and gut antibiotic resistome in the progression of COVID-19 and disease severity. They also provide a better understanding of how this disease affects different cohorts of patients. As such, these findings should contribute to better diagnosis and treatment scenarios.

E-Relationship Through a Value Lens-Implications for Organizational Capability

Firms that extend their e-commerce platforms into customer decision-making to build relationships need to understand the customer journey or build e-relationships through a lens that the customer uses to assess the value created and fulfilled. By contrasting the value cycles that customers and firms use, four different activities are identified for firms with shorter and longer value cycles. By enabling customers to support value creation, fulfilling the value created by enlisting partners and expanding services, and engaging the customers during value-in-use, three organizations discussed in the published literature appear to have developed e-relationship strategies to create and sustain value both before and during COVID-19. This analysis led us to develop three different insights: customer empowerment, collaborative competency, and intelligent digital platform for organizational capability. These insights were used to analyze two different organizations interviewed during the 2020period, as they faced many COVID-19 challenges, and assess the generalizability of these capabilities. We provide three recommendations for IS leaders for building e-relationships through a customer lens, by drawing on five case studies of companies to remain agile.

Evolution of anti-SARS-CoV-2 spike protein titers after two-dose of COVID-19 vaccination among people living with HIV.

Background: A community COVID-19 outbreak caused by the B.1.1.7 SARS-CoV-2 variant occurred in Taiwan in May 2021. High-risk populations such as people living with HIV (PLWH) were recommended to receive two doses of COVID-19 vaccines. While SARS-CoV-2 vaccines have demonstrated promising results in general population, real-world information on the serological responses remains limited among PLWH. Methods: PLWH receiving the first dose of SARS-CoV-2 vaccine from 2020 to 2021 were enrolled. Determinations of anti-SARS-CoV-2 spike IgG titers were performed every one to three months, the third dose of the SARS-CoV-2 vaccine or confirmed SARS-CoV-2 infection. All serum samples were tested for anti-nucleocapsid antibody and those tested positive were excluded from analysis. Results: A total of 1189 PLWH were enrolled: 829 (69.7%) receiving two doses of the AZD1222 vaccine, 232 (19.5%) of the mRNA-1273 vaccine, and 128 (10.8%) of the BNT162b2 vaccine. At all time-points, PLWH receiving two doses of mRNA vaccines had consistently higher antibody levels than those receiving the AZD1222 vaccine (p <0.001 for all time-point comparisons). Factors associated with failure to achieve an anti-spike IgG titer >141 BAU/mL within 12 weeks, included type 2 diabetes mellitus (DM) (adjusted odds ratio [aOR], 2.24; 95% CI, 1.25-4), a CD4 T cell count <200 cells/mm3 upon receipt of the first dose of vaccination (aOR, 3.43; 95% CI, 1.31-9) and two homologous AZD1222 vaccinations (aOR, 16.85; 95%CI, 10.13-28). For those receiving two doses of mRNA vaccines, factors associated with failure to achieve an anti-spike IgG titer >899 BAU/mL within 12 weeks were a CD4 T cell count <200 cells/mm3 on first-dose vaccination (aOR, 3.95; 95% CI, 1.08-14.42) and dual BNT162b2 vaccination (aOR, 4.21; 95% CI, 2.57-6.89). Conclusions: Two doses of homologous mRNA vaccination achieved significantly higher serological responses than vaccination with AZD1222 among PLWH. Those with CD4 T cell counts <200 cells/mm3 and DM had consistently lower serological responses.

The Association Between Dissemination and Characteristics of Pro-/Anti-COVID-19 Vaccine Messages on Twitter: Application of the Elaboration Likelihood Model.

Background: Messages on one's stance toward vaccination on microblogging sites may affect the reader's decision on whether to receive a vaccine. Understanding the dissemination of provaccine and antivaccine messages relating to COVID-19 on social media is crucial; however, studies on this topic have remained limited. Objective: This study applies the elaboration likelihood model (ELM) to explore the characteristics of vaccine stance messages that may appeal to Twitter users. First, we examined the associations between the characteristics of vaccine stance tweets and the likelihood and number of retweets. Second, we identified the relative importance of the central and peripheral routes in decision-making on sharing a message. Methods: English-language tweets from the United States that contained provaccine and antivaccine hashtags (N=150,338) were analyzed between April 26 and August 26, 2021. Logistic and generalized negative binomial regressions were conducted to predict retweet outcomes. The content-related central-route predictors were measured using the numbers of hashtags and mentions, emotional valence, emotional intensity, and concreteness. The content-unrelated peripheral-route predictors were measured using the numbers of likes and followers and whether the source was a verified user. Results: Content-related characteristics played a prominent role in shaping decisions regarding whether to retweet antivaccine messages. Particularly, positive valence (incidence rate ratio [IRR]=1.32, P=.03) and concreteness (odds ratio [OR]=1.17, P=.01) were associated with higher numbers and likelihood of retweets of antivaccine messages, respectively; emotional intensity (subjectivity) was associated with fewer retweets of antivaccine messages (OR=0.78, P=.03; IRR=0.80, P=.04). However, these factors had either no or only small effects on the sharing of provaccine tweets. Retweets of provaccine messages were primarily determined by content-unrelated characteristics, such as the numbers of likes (OR=2.55, IRR=2.24, P<.001) and followers (OR=1.31, IRR=1.28, P<.001). Conclusions: The dissemination of antivaccine messages is associated with both content-related and content-unrelated characteristics. By contrast, the dissemination of provaccine messages is primarily driven by content-unrelated characteristics. These findings signify the importance of leveraging the peripheral route to promote the dissemination of provaccine messages. Because antivaccine tweets with positive emotions, objective content, and concrete words are more likely to be disseminated, policymakers should pay attention to antivaccine messages with such characteristics.

Clinical assessment of SARS-CoV-2 infectivity by rapid antigen test compared with virus isolation.

Although real-time reverse transcriptase polymerase chain reaction (real-time RT-PCR) remains as a golden standard for detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, it can not be easily expanded to large-scaled screening during outbreaks, and the positive results do not necessarily correlate with infectious status of the identified subjects. In this study, the performance of Vstrip® RV2 COVID-19 Antigen Rapid Test (RAT) and its correlation with virus infectivity was examined by virus culture using 163 sequential respiratory specimens collected from 26 SARS-CoV-2 infected patients. When the presence of cytopathic effects (CPE) in cell culture was used as a reference method for virus infectivity, the sensitivity, specificity and accuracy of Vstrip® RV2 COVID-19 Antigen Rapid Test was 96.43%, 89.63%, and 90.8%, respectively. The highest Ct value was 27.7 for RdRp gene and 25.79 for E gene within CPE-positive samples, and the highest Ct value was 31.9 for RdRp gene and 29.1 for E gene within RAT positive samples. When the Ct values of specimens were below 25, the CPE and RAT results had high degree of consistency. We concluded that the RAT could be a great alternative method for determining the infectious potential of individuals with high viral load.

The natural tannins oligomeric proanthocyanidins and punicalagin are potent inhibitors of infection by SARS-CoV-2 in vitro (preprint)

The COVID-19 pandemic continues to infect people worldwide. While the vaccinated population has been increasing, the rising breakthrough infection persists in the vaccinated population. For living with the virus, the dietary guidelines to prevent virus infection are worthy of and timely to develop further. Tannic acid has been demonstrated to be an effective inhibitor of coronavirus and is under clinical trial. Here we found that two other members of the tannins family, oligomeric proanthocyanidins (OPCs) and punicalagin, are also potent inhibitors against SARS-CoV-2 infection with different mechanisms. OPCs and punicalagin showed inhibitory activity against omicron variants of SARS-CoV-2 infection. The water extractant of the grape seed was rich in OPCs and also exhibited the strongest inhibitory activities for viral entry of wild-type and other variants in vitro. Moreover, we evaluated the inhibitory activity of grape seed extractants (GSE) supplementation against SARS-CoV-2 viral entry in vivo and observed that serum samples from the healthy human subjects had suppressive activity against different variants of SARS-CoV-2 vpp infection after taking GSE capsules. Our results suggest that natural tannins acted as potent inhibitors against SARS-CoV-2 infection, and GSE supplementation could serve as healthy food for infection prevention.

Comparison of SARS-CoV-2 entry inhibitors based on ACE2 receptor or engineered Spike-binding peptides (preprint)

With increasing resistance of SARS-CoV-2 variants to antibodies, there is interest in developing entry inhibitors that target essential receptor binding regions of the viral Spike protein and thereby present a high bar for viral resistance. Such inhibitors can be derivatives of the viral receptor, ACE2, or peptides engineered to interact specifically with the receptor-binding pocket. We compared the efficacy of a series of both types of entry inhibitors, constructed as fusions to an antibody Fc domain. Such a design can increase protein stability and act to both neutralize free virus and recruit effector functions to clear infected cells. We tested the reagents against prototype variants of SARS-CoV-2, using both Spike pseudotyped VSV vectors and viral plaque assays. These analyses revealed that an optimized ACE2 derivative could neutralize all variants we tested with high efficacy. In contrast, the Spike-binding peptides had varying activities against different variants, with resistance observed for the Spike proteins from Beta, Gamma and Omicron. The resistance mapped to mutations at Spike residues K417 and N501 and could be overcome for one of the peptides by linking two copies in tandem, effectively creating a tetrameric reagent in the Fc fusion. Finally, both the optimized ACE2 and tetrameric peptide inhibitors provided some protection to human ACE2 transgenic mice challenged with the SARS-CoV-2 Delta variant, which typically causes death in this model within 7-9 days.