Physics-driven structural docking and protein language models accelerate antibody screening and design for broad-spectrum antiviral therapy (preprint)

Therapeutic antibodies have become one of the most influential therapeutics in modern medicine to fight against infectious pathogens, cancer, and many other diseases. However, experimental screening for highly efficacious targeting antibodies is labor-intensive, which is exacerbated by evolving antigen targets under selective pressure such as fast-mutating viral variants. As a proof-of-concept, we developed a machine learning-assisted antibody generation pipeline that greatly accelerates the screening and re-design of immunoglobulins G (IgGs) against a broad spectrum of coronavirus variants. Using over 1300 IgG sequences derived from patient B cells bound with the viral spike's receptor binding domain (RBD), we first established protein structural docking models in assessing the IgG-RBD-ACE2 interaction interfaces and predicting their viral neutralizing activities with a confidence score. The confidence score is calculated as a fraction of IgG-blocking RBD binding sites versus all ACE2-interacting sites. Additionally, employing Gaussian process regression (also known as Kriging) in a latent space of an antibody language model, we predicted the IgGs' activity profiles against viral strains. Using functional analyses and experimental validations, we subsequently prioritized IgG candidates for neutralizing a broad spectrum of viral variants (wildtype, Delta, and Omicron) and preventing the infection of host cells in vitro and hACE2 transgenic mice in vivo. To further improve the blockade efficacy for the Delta strain (B.1.617), we rationally redesigned the IgG clones with single amino acid substitutions at the RBD-binding interface. Our work expedites applications of artificial intelligence in low-data regimes when limited data is available, including protein language models (using unlabeled data) and Kriging (using few labeled data) for antibody sequence analysis, activity prediction, and efficacy improvement, which are aided by physics-driven protein docking models for antibody-antigen interface structure analyses.

Human personal air pollution clouds in a naturally ventilated office during the COVID-19 pandemic.

Personal cloud, termed as the difference in air pollutant concentrations between breathing zone and room sites, represents the bias in approximating personal inhalation exposure that is linked to accuracy of health risk assessment. This study performed a two-week field experiment in a naturally ventilated office during the COVID-19 pandemic to assess occupants' exposure to common air pollutants and to determine factors contributing to the personal cloud effect. During occupied periods, indoor average concentrations of endotoxin (0.09 EU/m3), TVOC (231 µg/m3), CO2 (630 ppm), and PM10 (14 µg/m3) were below the recommended limits, except for formaldehyde (58 µg/m3). Personal exposure concentrations, however, were significantly different from, and mostly higher than, concentrations measured at room stationary sampling sites. Although three participants shared the same office, their personal air pollution clouds were mutually distinct. The mean personal cloud magnitude ranged within 0-0.05 EU/m3, 35-192 µg/m3, 32-120 ppm, and 4-9 µg/m3 for endotoxin, TVOC, CO2, and PM10, respectively, and was independent from room concentrations. The use of hand sanitizer was strongly associated with an elevated personal cloud of endotoxin and alcohol-based VOCs. Reduced occupancy density in the office resulted in more pronounced personal CO2 clouds. The representativeness of room stationary sampling for capturing dynamic personal exposures was as low as 28% and 5% for CO2 and PM10, respectively. The findings of our study highlight the necessity of considering the personal cloud effect when assessing personal exposure in offices.

The impact of CoronaVac on the neutralization breadth and magnitude of the antibody response to SARS-CoV-2 viruses

Although immune response enhancement has been reported after primary and booster vaccines of CoronaVac, neutralization breadth of SARS-CoV-2 variants is still unclear. In the present study, we examined the neutralization magnitude and breadth of SARS-CoV-2 variants including Beta (B.1.351), Delta (B.1.617.2) and Omicron (B.1.1.529) in 33 convalescent COVID-19 patients and a cohort of 55 medical staff receiving primary CoronaVac vaccines and an additional homologous booster dose. Results showed that, as compared with the two-dose primary vaccination, the homologous booster dose achieved 2.24-, 3.98-, 4.58- and 2.90-fold increase in neutralization titer against wild-type, Beta, Delta, and Omicron, respectively. After booster dose, neutralization titer reduction for variants was less than that after the primary vaccine or that for convalescents. The proportion of recipients able to neutralize 2 or more variants increased from 36.36% post the primary vaccination to 87.27% after the booster. Significant increase in neutralization breadth of 1.24 (95% confidence interval (CI), 0.89–1.59) variants was associated with a log10 increase in neutralization titer against the wild-type. In addition, anti-RBD IgG level was identified as an excellent surrogate for positive neutralization of SARS-CoV-2 and neutralization breadth of variants. These findings highlight the value of an additional homologous CoronaVac dose in broadening the cross-neutralization against SARS-CoV-2 variants, and are critical for informing the booster dose vaccination efforts.

No Control, No Consumption: Association of Low Perceived Control and Intention to Accept Genetically Modified Food.

Based on compensatory control theory, the aim of this study was to examine the effects of perceived control on people's acceptance of genetically modified (GM) foods by using both correlational and experimental methods. Compensatory control theory proposes that the lower an individual's perceived control, the higher their need for structure, order, and certainty. Therefore, based on beliefs about GM foods that make some people less certain that those foods are as safe as traditional foods, we hypothesized that individuals with lower levels of perceived control are more inclined to reject GM foods. The analysis of questionnaire responses in Study 1 revealed that individuals' sense of control negatively predicted their risk perception of GM foods, while the need for structure played a mediating role. In Study 2, using a between-subject design, we manipulated participants' perceived control (higher vs. lower) and subsequently measured their risk perception and purchasing preferences for GM foods. The results in Study 2 show that under lower control conditions, individuals recognize higher risks related to GM foods, which, in turn, decreases their willingness to purchase GM foods. These results not only suggest that perceived control is a potential influential personal factor of the acceptance of GM foods but also extend the scope of the application of compensatory control theory.

The Prevention Behaviors and Impact Mechanisms Among Different Chinese Social Classes at the Early Stage of COVID-19 Pandemic.

Background: Whether the pandemic can be effectively prevented and controlled depends on the entire population's adherence to recommendations and preventive behaviors. The present study aimed to investigate the social class differences and internal mechanisms of prevention behaviors in the COVID-19 pandemic. Methods: We conducted an online cross-sectional survey among the general Chinese population at the early stage of the COVID-19 pandemic. The survey website's subscribers could access the questionnaire through the Tencent online platform, and a total of 1948 participants voluntarily completed it. Most of the participants were female (n = 1257, 64.528%), between the ages of 18-29 (n = 999, 51.284%), university graduates (n = 1015, 52.105%), and had an annual family income below 100,000 yuan (n = 1119, 57.444%). The differences in COVID-19 prevention behaviors among different social classes, the mediating role of infectious threat perception and the moderating role of perceived epidemic transparency were examined. Results: 1) There were significant differences in prevention behaviors among different social classes. 2) The level of infectious threat perception played a mediating role in the relationship between social class and prevention behavior. When the individuals were from a lower social class, the level of threat perception and the level of COVID-19 prevention behaviors were also lower. 3) Perceived epidemic transparency played a moderating role in the relationship between social class and COVID-19 prevention behavior. It also played a moderating role in the relationship between social class and infectious threat perception. Conclusion: In the implementation of epidemic prevention and control measures, different social classes should be targeted and guided differently. In particular, lower-class individuals can be guided by improving the perceptions of epidemic transparency and infectious threat.

How Does Social Class Affect Need for Structure during the COVID-19 Pandemic? A Moderated Mediating Model Analysis.

The COVID-19 pandemic is profoundly affecting the minds and behaviors of people worldwide. This study investigated the differences in the need for structure among people from different social classes and the psychological mechanisms underlying this need, as well as the moderating effect of the threat posed by the pandemic. Using data collected from non-student adults in China, we found that the lower an individual's social class, the lower their need for structure, and this effect was based on the mediating role of perceived control. However, the mediating effect was moderated by pandemic threat, and the above relationship existed only when this threat was low. When the level of pandemic threat was higher, neither the effect of social class nor of perceived control on the need for structure were significant. Specifically, in higher-threat situations, the need for structure among individuals from higher social classes and who had a higher sense of control increased significantly, meaning the mediating effect was no longer significant. This finding showed that under the threat of a pandemic, individuals who have a lower need for structure will still pursue and prefer structure and order. The theoretical and practical implications of the research are also discussed.

Characteristics and outcomes of 118,155 COVID-19 individuals with a history of cancer in the United States and Spain (preprint)

PurposeWe aimed to describe the demographics, cancer subtypes, comorbidities and outcomes of patients with a history of cancer with COVID-19 from March to June 2020. Secondly, we compared patients hospitalized with COVID-19 to patients diagnosed with COVID-19 and patients hospitalized with influenza. MethodsWe conducted a cohort study using eight routinely-collected healthcare databases from Spain and the US, standardized to the Observational Medical Outcome Partnership common data model. Three cohorts of patients with a history of cancer were included: i) diagnosed with COVID-19, ii) hospitalized with COVID-19, and iii) hospitalized with influenza in 2017-2018. Patients were followed from index date to 30 days or death. We reported demographics, cancer subtypes, comorbidities, and 30-day outcomes. ResultsWe included 118,155 patients with a cancer history in the COVID-19 diagnosed and 41,939 in the COVID-19 hospitalized cohorts. The most frequent cancer subtypes were prostate and breast cancer (range: 5-19% and 1-14% in the diagnosed cohort, respectively). Hematological malignancies were also frequent, with non-Hodgkins lymphoma being among the 5 most common cancer subtypes in the diagnosed cohort. Overall, patients were more frequently aged above 65 years and had multiple comorbidities. Occurrence of death ranged from 8% to 14% and from 18% to 26% in the diagnosed and hospitalized COVID-19 cohorts, respectively. Patients hospitalized with influenza (n=242,960) had a similar distribution of cancer subtypes, sex, age and comorbidities but lower occurrence of adverse events. ConclusionPatients with a history of cancer and COVID-19 have advanced age, multiple comorbidities, and a high occurence of COVID-19-related events. Additionaly, hematological malignancies were frequent in these patients.This observational study provides epidemiologic characteristics that can inform clinical care and future etiological studies.

Circulating ACE2-expressing Exosomes Block SARS-CoV-2 Infection as an Innate Antiviral Mechanism (preprint)

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes the coronavirus disease 2019 (COVID-19) with innate and adaptive immune response triggered in such patients by viral antigens. Both convalescent plasma and engineered high affinity human monoclonal antibodies have shown therapeutic potential to treat COVID-19. Whether additional antiviral soluble factors exist in peripheral blood remain understudied. Herein, we detected circulating exosomes that express the SARS-CoV-2 viral entry receptor angiotensin-converting enzyme 2 (ACE2) in plasma of both healthy donors and convalescent COVID-19 patients. We demonstrated that exosomal ACE2 competes with cellular ACE2 for neutralization of SARS-CoV-2 infection. ACE2-expressing (ACE2+) exosomes, but not the ACE2-negative controls, blocked the binding of the viral spike (S) protein RBD to ACE2+ cells in a dose dependent manner, which was 400- to 700-fold more potent than that of vesicle-free recombinant human ACE2 extracellular domain protein (rhACE2). As a consequence, exosomal ACE2 prevented SARS-CoV-2 pseudotype virus tethering and infection of human host cells at a 50–150 fold higher efficacy than rhACE2. A similar antiviral activity of exosomal ACE2 was further demonstrated to block wild-type live SARS-CoV-2 infection. Of note, depletion of ACE2+ exosomes from COVID-19 patient plasma impaired the ability to block SARS-CoV-2 RBD binding to host cells. Furthermore, a dramatic increase in plasma ACE2+ exosome levels were detected in patients with severe COVID-19 pathogenesis. Our data demonstrate that ACE2+ exosomes can serve as a decoy therapeutic and a possible innate antiviral mechanism to block SARS-CoV-2 infection.

Circulating ACE2-expressing Exosomes Block SARS-CoV-2 Virus Infection as an Innate Antiviral Mechanism (preprint)

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes the coronavirus disease 2019 (COVID-19) with innate and adaptive immune response triggered in such patients by viral antigens. Both convalescent plasma and engineered high affinity human monoclonal antibodies have shown therapeutic potential to treat COVID-19. Whether additional antiviral soluble factors exist in peripheral blood remain understudied. Herein, we detected circulating exosomes that express the SARS-CoV-2 viral entry receptor angiotensin-converting enzyme 2 (ACE2) in plasma of both healthy donors and convalescent COVID-19 patients. We demonstrated that exosomal ACE2 competes with cellular ACE2 for neutralization of SARS-CoV-2 infection. ACE2-expressing (ACE2+) exosomes blocked the binding of the viral spike (S) protein RBD to ACE2+ cells in a dose dependent manner, which was 400- to 700-fold more potent than that of vesicle-free recombinant human ACE2 extracellular domain protein (rhACE2). As a consequence, exosomal ACE2 prevented SARS-CoV-2 pseudotype virus tethering and infection of human host cells at a 50-150 fold higher efficacy than rhACE2. A similar antiviral activity of exosomal ACE2 was further demonstrated to block wild-type live SARS-CoV-2 infection. Of note, depletion of ACE2+ exosomes from COVID-19 patient plasma impaired the ability to block SARS-CoV-2 RBD binding to host cells. Our data demonstrate that ACE2+ exosomes can serve as a decoy therapeutic and a possible innate antiviral mechanism to block SARS-CoV-2 infection.

Ca2+-dependent mechanism of membrane insertion and destabilization by the SARS-CoV-2 fusion peptide (preprint)

Cell penetration after recognition of the SARS-CoV-2 virus by the ACE2 receptor, and the fusion of its viral envelope membrane with cellular membranes, are the early steps of infectivity. A region of the Spike protein (S) of the virus, identified as the "fusion peptide" (FP), is liberated at its N-terminal site by a specific cleavage occurring in concert with the interaction of the receptor binding domain of the Spike. Studies have shown that penetration is enhanced by the required binding of Ca2+ ions to the FPs of corona viruses, but the mechanisms of membrane insertion and destabilization remain unclear. We have predicted the preferred positions of Ca2+ binding to the SARS-CoV-2-FP, the role of Ca2+ ions in mediating peptide-membrane interactions, the preferred mode of insertion of the Ca2+-bound SARS-CoV-2-FP and consequent effects on the lipid bilayer from extensive atomistic molecular dynamics (MD) simulations and trajectory analyses. In a systematic sampling of the interactions of the Ca2+-bound peptide models with lipid membranes SARS-CoV-2-FP penetrated the bilayer and disrupted its organization only in two modes involving different structural domains. In one, the hydrophobic residues F833/I834 from the middle region of the peptide are inserted. In the other, more prevalent mode, the penetration involves residues L822/F823 from the LLF motif which is conserved in CoV-2-like viruses, and is achieved by the binding of Ca2+ ions to the D830/D839 and E819/D820 residue pairs. FP penetration is shown to modify the molecular organization in specific areas of the bilayer, and the extent of membrane binding of the SARS-CoV-2 FP is significantly reduced in the absence of Ca2+ ions. These findings provide novel mechanistic insights regarding the role of Ca2+ in mediating SARS-CoV-2 fusion and provide a detailed structural platform to aid the ongoing efforts in rational design of compounds to inhibit SARS-CoV-2 cell entry. STATEMENT OF SIGNIFICANCESARS-CoV-2, the cause of the COVID-19 pandemic, penetrates host cell membranes and uses viral-to-cellular membrane fusion to release its genetic material for replication. Experiments had identified a region termed "fusion peptide" (FP) in the Spike proteins of coronaviruses, as the spearhead in these initial processes, and suggested that Ca2+ is needed to support both functions. Absent structure and dynamics-based mechanistic information these FP functions could not be targeted for therapeutic interventions. We describe the development and determination of the missing information from analysis of extensive MD simulation trajectories, and propose specific Ca2+-dependent mechanisms of SARS-CoV-2-FP membrane insertion and destabilization. These results offer a structure-specific platform to aid the ongoing efforts to use this target for the discovery and/or of inhibitors.

Central Contributions of Myocardial Injury to Adverse Outcomes in Patients With Coronavirus Disease 2019 (preprint)

Objective: this study aimed to explore the impacts of myocardial injury on the clinical severity and outcomes in patients with Coronavirus Disease 2019 (COVID-19).Methods: we analyzed the electronic medical records of 1646 COVID-19 inpatients in Wuhan Huoshenshan Hospital. Results: 327 (19.9%) developed into severe cases, 23 (1.4%) died. In comparison to common cases, severe cases showed older age, more comorbidities, abnormal immune responses, as well as liver, renal, cardiac and coagulation disorders. Multivariable logistic regression identified that older age , combining with arrhythmia, abnormal lymphocyte percentage, elevated hypersensitive C reactive protein (hs-CRP) and myocardial injury were the independent risk factors for the incidence of severe cases. Moreover, Kaplan-Meier survival analysis showed that patients with myocardial injury had increasing risks of mortality, incidence of severe cases, acute respiratory distress syndrome (ARDS), and intensive care unit (ICU) admission. Particularly, myocardial injury patients co-existed with any other risk factor further deteriorated the clinical outcomes.Conclusion: The presence of myocardial injury and its co-existing with older age, arrhythmia, abnormal lymphocyte percentage, or elevated hs-CRP were greatly associated with the incidence of severe patients and poor clinical outcomes.

Association of Initial Symptoms or Comorbidities With Pneumonia Lesions in COVID-19 Patients: Based on Artificial Intelligence-Enabled CT Quantitation (preprint)

Background: Coronavirus disease 2019 (COVID-19) patients with a larger ratio of pneumonia lesions are more likely to progress to acute respiratory distress syndrome and death. This study aimed to investigate the relationship of baseline parameters with pneumonia lesions on admission, as quantified by an artificial intelligence (AI) algorithm using computed tomography (CT) images. Methods: This retrospective study quantitatively assessed lung lesions on CT using an AI algorithm in 1630 consecutive patients confirmed with COVID-19 on admission and classified the patients into none (0%), mild (>0–25%), intermediate (>25–50%), and severe (>50%) groups, according to the lesion ratio of the whole lung. A multivariate linear regression model was established to explore the relationship between the lesion ratio and laboratory parameters. The baseline parameters associated with lung lesions, including demographics, initial symptoms, and comorbidities, were determined using a multivariate ordinal regression model. Results: The 1630 patients confirmed with COVID-19 had a median whole lung lesion ratio of 4.1%, and the right lower lung lobe had the most lesions among the five lung lobes based on the evaluation of CT using AI algorithm. The whole lung lesion ratio was associated with the levels of plasma fibrinogen (r=0.280, p<0.001), plasma D-dimer (r=0.248, p<0.001), serum α-hydroxybutyrate dehydrogenase (r=0.363, p<0.001), serum albumin (r=-0.300, p<0.001), and peripheral blood leukocyte count (r=0.194, p<0.001). Among the four patients groups categorised by whole lung lesion ratio, the highest frequency of cough (p<0.001) and shortness of breath (p<0.001) were found in the severe group, and the highest frequency of hypertension (p<0.001), diabetes (p<0.001) and anemia (p=0.039) were observed in the intermediate group. Based on baseline ordinal regression analysis, cough (p=0.009), shortness of breath (p<0.001), hypertension (p=0.002), diabetes (p=0.005), and anemia (p=0.006) were independent risk factors for more severe lung lesions. Conclusions: Based on AI-enabled CT quantitation, patients with initial symptoms of cough/shortness of breath, or with comorbidities of hypertension, diabetes, or anemia, had a higher risk for more severe lung lesions on admission in COVID-19 patients.

Brief Analysis of the ARIMA model on the COVID-19 in Italy (preprint)

Coronavirus disease 2019 (COVID-19) has been considered as a global threat infectious disease, and various mathematical models are being used to conduct multiple studies to analyze and predict the evolution of this epidemic. We statistically analyze the epidemic data from February 24 to March 30, 2020 in Italy, and proposes a simple time series analysis model based on the Auto Regressive Integrated Moving Average (ARIMA). The cumulative number of newly diagnosed and newly diagnosed patients in Italy is preprocessed and can be used to predict the spread of the Italian COVID-19 epidemic. The conclusion is that an inflection point is expected to occur in Italy in early April, and some reliable points are put forward for the inflection point of the epidemic: strengthen regional isolation and protection, do a good job of personal hygiene, and quickly treat the team leaders existing medical forces. It is hoped that the "City Closure" decree issued by the Italian government will go in the right direction, because this is the only way to curb the epidemic.