Toll-like receptor 7 (TLR7)-mediated antiviral response protects mice from lethal SARS-CoV-2 infection (preprint)

SARS-CoV-2-induced impaired antiviral and excessive inflammatory responses cause fatal pneumonia. However, the key pattern recognition receptors that elicit effective antiviral and lethal inflammatory responses in-vivo are not well defined. CoVs possess single-stranded RNA (ssRNA) that is abundantly produced during infection and stimulates both antiviral interferon (IFN) and inflammatory cytokine/ chemokine responses. Therefore, in this study, using wild-type control and TLR7 deficient BALB/c mice infected with a mouse-adapted SARS-COV-2 (MA-CoV-2), we evaluated the role of TLR7 signaling in MA-CoV-2-induced antiviral and inflammatory responses and disease outcome. We show that TLR7-deficient mice are more susceptible to MA-CoV-2 infection as compared to infected control mice. Further evaluation of MA-CoV-2 infected lungs showed significantly reduced mRNA levels of antiviral type I and type III IFNs, IFN stimulated genes (ISGs, ISG15 and CXCL10), and several pro-inflammatory cytokines/chemokines in TLR7 deficient compared to control mice. Reduced lung IFN/ISG levels and increased morbidity/mortality in TLR7 deficient mice correlated with high lung viral titer. Detailed examination of total cells from MA-CoV-2 infected lungs showed high neutrophil count in TLR7 deficient mice compared to control mice. Additionally, blocking TLR7 activity post-MA-CoV-2 infection using a specific inhibitor also enhanced disease severity. In summary, our results conclusively establish that TLR7 signaling is protective during SARS-CoV-2 infection, and despite robust inflammatory response, TLR7-mediated IFN/ISG responses likely protect the host from lethal disease. Given similar outcomes in control and TLR7 deficient humans and mice, these results show that MA-CoV-2 infected mice serve as excellent model to study COVID-19.

The SARS-CoV-2 spike N-terminal domain engages 9-O-acetylated α2-8-linked sialic acids (preprint)

SARS-CoV-2 viruses engage ACE2 as a functional receptor with their spike protein. The S1 domain of the spike protein contains a C-terminal receptor-binding domain (RBD) and an N-terminal domain (NTD) which, in other coronaviruses, includes a glycan-binding cleft. However, for the SARS-CoV-2 NTD protein-glycan binding was only observed weakly for sialic acids with highly sensitive methods. Amino acid changes in the NTD of Variants of Concern (VoC) shows antigenic pressure, which can be an indication of functionality. To analyze gain or loss of glycan-binding in VoC, trimeric fluorescent NTD proteins were used. Binding properties were analyzed biochemically on Vero E6 cells and tissue samples. Unexpectedly, the SARS-CoV-2 Beta (501Y.V2-1) NTD binding to Vero E6 cells was sensitive to sialidase pretreatment. Glycan microarray analyses identified a putative 9-O-acetylated sialic acid as a ligand, which was confirmed by catch-and-release ESI-MS, STD-NMR analyses, and a graphene-based electrochemical sensor. The Beta (501Y.V2-1) variant attained an enhanced glycan binding modality in the NTD with specificity towards 9-O-acetylated structures, suggesting a dual-receptor functionality of the SARS-CoV-2 S1 domain, which was quickly selected against. This demonstrates plasticity for improved engagement to sialic acids, possibly under immunological pressure.

Understanding the impact of COVID-19 risk perceptions on mitigation behaviors: A mixed methods approach using survey instruments and serious games (preprint)

COVID-19 risk mitigation behavior, including social distancing and mask wearing, was a principal factor influencing the spread of COVID-19. Yet this behavior, and its association with COVID-19 perceptions and beliefs, is poorly understood. Here we used a mixed methods approach combining serious game data with survey instruments to describe relationships between perceptions and behavior. Using a series of survey questions, participants were described along a spectrum denoting their perception of their susceptibility to COVID-19 associated with a list of activities. Afterwards, participants engaged with a serious game to examine behavioral responses to scenarios involving shopping at a grocery store and going to a park during simulated pandemic conditions. Messages describing the simulated infection risk were shown to drive many behavioral decisions. Another significant correlate, derived from survey results, was the participants perception of susceptibility associated with various activities for acquiring the COVID-19 infection. Individuals that perceived every day activities, such as grocery shopping, as unlikely to lead to a COVID-19 infection spent more time near others in the game-simulated grocery store environment compared to those that consider such activities as risky. Additionally, we found that participant behavior became increasingly risky as time progresses if they were lucky enough not to experience an infection. This reflects behavior observed in the United States and more broadly, possibly explains how people update their perception of the risk of activities. Overall, results show a link between perception and action with regards to COVID-19 and support the use of targeted risk messaging to influence behavior. Moreover, the link between reported real-world perceptions and game behavior suggest that serious games can be used as valuable tools to test policies, risk messaging and communication, with the goal of nudging individuals with varied and nuanced perceptions and belief sets towards behaviors that will reduce the impact of COVID-19.

Surveillance of SARS-CoV-2 in the environment and animal samples of the Huanan Seafood Market (preprint)

Emerging in December 2019, coronavirus disease 2019 (COVID-19) eventually became a pandemic and has posed a tremendous threat to global public health. However, the origins of SARS-CoV-2, the causative agent of COVID-19, remain to be determined. It has reported that a certain number of the early case clusters had a contact history with Huanan Seafood Market. Therefore, surveillance of SARS-CoV-2 within the market is of vital importance. Herein, we presented the SARS-CoV-2 detection results of 1380 samples collected from the environment and the animals within the market in early 2020. By SARS-CoV-2-specific RT-qPCR, 73 environmental samples tested positive for SARS-CoV-2 and three live viruses were successfully isolated. The viruses from the market shared nucleotide identity of 99.980% to 99.993% with the human isolate HCoV/Wuhan/IVDC-HB-01. In contrast, no virus was detected in the animal swabs covering 18 species of animals in the market. The SARS-COV-2 nucleic acids in the positive environmental samples showed significant correlation of abundance of Homo sapiens with SARS-CoV-2. In summary, this study provided convincing evidence of the prevalence of SARS-CoV-2 in the Huanan Seafood Market during the early stage of COVID-19 outbreak.

The Effect of Online Support of an Internet Plus Shared Care Diabetes Management Model on Metabolic Indicators for Patients With Type 2 Diabetes During the COVID-19 Pandemic (preprint)

Purpose: This study aimed to explore the influences of online support of an Internet plus Shared Care diabetes management model on metabolic indicators and the differences before and after the coronavirus disease 2019 (COVID-19) pandemic. Method: Type 2 diabetes patients who visited the Peking University First Hospital Internet plus Shared Care clinic from May 18, 2020 to June 20, 2020 (after the COVID-19 pandemic subsided) were enrolled in the study. The age, gender, usage of insulin, and duration of diabetes of the patients were collected. The glycosylated hemoglobin (HbA1c), interval between two consecutive visits, communication frequencies with online diabetes educators through an app, online self-monitoring of blood glucose (SMBG) and upload count and SMBG pairing count (before–after meal) were collected before (prior to January 20, 2020) and after (from May 18, 2020 to June 20, 2020) the COVID-19 pandemic for logistic regression analysis. The R-3.4.4 and TWANG programs were used for analysis. The group of patients whose HbA1c did not change during the pandemic was the control group, while the group of patients with improved HbA1c was the dependent variable. Independent variables included age, gender, duration of disease, insulin usage, online communication amount, SMBG count, and SMBG pairing count. Propensity score matching (PSM) was applied with age, duration, gender, body mass index (BMI), HbA1c, low density lipoprotein- cholesterol (LDL-C), and blood pressure (BP) at baseline as the concomitant variable. After the PSM weighting, the average treatment effect (ATE) of post-pandemic BMI, HbA1c, LDL-C, and BP was compared with the baseline. Results: A total of 387 patients were enrolled in the study including 184 female (47.5%). The baseline values were the following: age, 61.7±9.4 year;, duration of diabetes, 11.7±8.2 years; BMI, 25.9±3.8Kg/m 2 ; HbA1c, 7.2±1.3%; LDL-C, 2.49±0.85mmol/L; systolic BP, 130.8±14.9 mmHg; and diastolic BP, 81.1±40.9 mmHg. Among variables, online communication amounted to a statistically significant contribution to the HbA1c improvement after the COVID-19 pandemic (OR=2.178, p=0.003). During the pandemic, each patient received 18 (3, 56) times online communication support per quarter. Patients were divided into four groups by quartiles: Q1 (more than 56 times/quarter, n=95), Q2 (18–56 times/quarter, n=97), Q3 (3–18 times/quarter, n=93), and Q4 (0–3 times/quarter, n=102). After PSM, post-pandemic data showed significant differences. Between-group variance was found in HbA1c (Q1 vs. Q3, -0.42±0.16%, p=0.009; Q1 vs. Q4, -0.53±0.15%, p=0.0009) and BMI (Q1 vs. Q3, -1.2±0.5, p=0.02; Q1 vs. Q4 -1.5±0.7, p=0.01) of patients. Conclusion: During the COVID-19 pandemic, high-quality online support of the Internet plus Shared Care diabetes management model can significantly improve the HbA1c and BMI of type 2 diabetes patients.

COVID-19: risk factors for severe cases of the Delta variant.

BACKGROUND: Since April 2021, the SARS-CoV-2 (B.1.167) Delta variant has been rampant worldwide. Recently, this variant has spread in Guangzhou, China. Our objective was to characterize the clinical features and risk factors of severe cases of the Delta variant in Guangzhou. METHODS: A total of 144 patients with the Delta variant were enrolled, and the data between the severe and non-severe groups were compared. Logistic regression methods and Cox multivariate regression analysis were used to investigate the risk factors of severe cases. RESULTS: The severity of the Delta variant was 11.1%. Each 1-year increase in age (OR, 1.089; 95% CI, 1.035-1.147; P = 0.001) and each 1-µmol/L increase in total bilirubin (OR, 1.198; 95% CI, 1.021-1.406; P = 0.039) were risk factors for severe cases. Moreover, the risk of progression to severe cases increased 13.444-fold and 3.922-fold when the age was greater than 58.5 years (HR, 13.444; 95% CI, 2.989-60.480; P = 0.001) or the total bilirubin level was greater than 7.23 µmol/L (HR, 3.922; 95% CI, 1.260-12.207; P = 0.018), respectively. CONCLUSION: Older age and elevated total bilirubin were independent risk factors for severe cases of the Delta variant in Guangzhou, especially if the age was greater than 58.5 years or the total bilirubin level was greater than 7.23 µmol/L.

Intensity-Based Computation Tomography (CT) Evaluation of Temporal Changes in Lung Abnormalities During the Recovery Stage in COVID-19 In-Hospital Patients (preprint)

Background: The coronavirus disease-19 (COVID-19) and its variants have increased rapidly worldwide since December 2019, with respiratory disease being a prominent complication. As such, optimizing evaluation methods and identifying factors predictive of disease progress remain critical. The purpose of the study was to assess late phase (≥3 weeks) pulmonary changes using intensity-based computed tomography (CT) scoring in COVID-19 patients and determine the clinical characteristics predicting lung abnormalities and recovery. Methods: : We conducted a retrospective study on 42 patients (14 males, 28 females; age 65±10 years) with COVID-19. Only patients with at least 3 CT scans taken at least 3 weeks after initial symptom onset were included in the study. Two scoring methods were assessed: (1) area-based scoring (ABS) and (2) intensity-weighted scoring (IWS). Temporal changes in the average lung lesion were evaluated by the calculating the averaged area under the curve (AUC) of the CT score-time curve. Correlations between averaged AUCs and clinical characteristics were determined. Results: Using the ABS system, temporal changes in lung abnormalities during recovery were highly variable (P=0.934). By contrast, the IWS system detected more subtle changes in lung abnormalities during in COVID-19 patients, with consistent week-to-week relative reductions in IWS (P=0.025). Strong relationships were observed with D-dimer and C-reactive protein (CRP) levels on admission, with hazard ratios (HR)(95%CI) of 5.32 (1.25-22.6)(P=0.026) and 1.05 (1.10-1.09)(P=0.017), respectively. Conclusion: Our results suggest COVID-19-mediated pulmonary abnormalities persist well-beyond 3-weeks of symptom onset, with intensity-weighted rather than area-based scoring being more sensitive. Moreover, D-dimer and CRP levels were predictive of the recovery from the disease.