Associations of dyspnea symptoms with lung function in patients with COVID-19 in the acute period (preprint)

Background Currently, the main prevalent strain of severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) is Omicron, which shows elevated viral load and spread ability, bringing new challenges to pandemic prevention and control.Objective To examine the associations of dyspnea symptoms with lung function in coronavirus disease-19 (COVID-19) patients during the acute period.Methods This study included COVID-19 cases diagnosed by real-time PCR (RT-PCR). These patients were divided into the dyspnea and non-dyspnea groups based on whether they had dyspnea symptoms at the time of admission.Results A total of 29 patients with pulmonary function tests (PFTs) were included in this study. Of all patients, 17.24% (5/29) had severe COVID-19, while the remaining cases were mild or moderate. Lung function was normal, with forced vital capacity (FVC) ≥ 80%, forced expiratory volume in 1 second (FEV1)/FVC ≥ 0.92, and diffusing capacity for carbon monoxide (DLCO) ≥ 80% in 96.55% (28/29), 79.31% (23/29), and 72.41% (21/29) of patients, respectively. Computer tomography (CT) findings were normal in 10.34% (3/29) of patients.Conclusions Multivariate analysis showed that lung function and chest CT parameters are not independently associated with dyspnea persistence in acute COVID-19 patients.

Multi-Agent Evolutionary Game Analysis of Group Panic Buying in China during the COVID-19 Pandemic (preprint)

With the global outbreak of COVID-19, the panic buying incidents triggered by the variants of the Omicron strain have severely affected the normal social order. This paper considers the complex interest game and interactive relationship among multiple subjects in the mass panic buying event caused by rumors and constructs a three-party evolution game model of local government, rumor-monger, and public. Based on the theory of evolution game, the evolutionary process of the strategy selection of game subjects is studied, and the strategy selection of the three-game subjects under different scenarios is compared and analyzed. Taking the example of the montmorillonite powder panic buying caused by the XBB virus strain rumor in China, the evolutionary game model constructed in this study is simulated and analyzed. The study shows that: the evolution process of the mass panic buying event is characterized by six stages: the initial stage E1(0,0,0); the outbreak stage E3(0,1,0);the spread stage E7(0,1,1);the climax stage E8(1,1,1);the relief stage E5(1,1,0);and the recovery stage E4(1,0,0); there are four stable points in the evolutionary game of the three game subjects, namely (no intervention, no rumor, no panic buying), (no intervention, rumor, no panic buying), (intervention, no rumor, no panic buying), and (intervention, rumor, no panic buying), and the strategy of government intervention will be adjusted according to the strategy selection of the public and the rumor-monger; under the mechanism of reward and punishment of the higher-level government, increasing the punishment and reward intensity of the higher-level government will promote the local government to intervene in the rumor-mongering event faster, but increasing the reward intensity has a more significant impact on the intervention behavior of the local government than punishment, and increasing punishment intensity has a more significant impact on the non-rumor-mongering behavior of the rumor-monger than reward; the parameters of social risk-bearing cost, risk transmission coefficient, rumor-mongering income and cost, and public drug purchase cost have different degrees of influence on the evolutionary behavior of game subjects. This study provides new ideas for effectively responding to mass panic buying events in the context of public emergencies.

Resolving the developmental mechanisms of coagulation abnormalities characteristic of SARS-CoV2 based on single-cell transcriptome analysis (preprint)

The COVID-19 outbreak caused by the SARS-CoV-2 virus has developed into a global health emergency. In addition to causing respiratory symptoms following SARS-CoV-2 infection, COVID-19-associated coagulopathy (CAC) is the main cause of death in patients with severe COVID-19. In this study, we performed single-cell sequencing analysis of the right ventricular free wall tissue from healthy donors, patients who died in the hypercoagulable phase of CAC, and patients in the fibrinolytic phase of CAC. Among these, we collected 61,187 cells, which were enriched in 24 immune cell subsets and 13 cardiac-resident cell subsets. We found that in response to SARS-CoV-2 infection, CD9highCCR2high monocyte-derived mo promoted hyperactivation of the immune system and initiated the extrinsic coagulation pathway by activating CXCR-GNB/G-PI3K-AKT. This sequence of events is the main process contributing the development of coagulation disorders subsequent to SARS-CoV-2 infection. In the characteristic coagulation disorder caused by SARS-CoV-2, excessive immune activation is accompanied by an increase in cellular iron content, which in turn promotes oxidative stress and intensifies intercellular competition. This induces cells to alter their metabolic environment, resulting in an increase in sugar uptake, such as that via the glycosaminoglycan synthesis pathway, in CAC coagulation disorders. In addition, high levels of reactive oxygen species generated in response elevated iron levels promote the activation of unsaturated fatty acid metabolic pathways in endothelial cell subgroups, including vascular endothelial cells. This in turn promotes the excessive production of the toxic peroxidation by-product malondialdehyde, which exacerbates both the damage caused to endothelial cells and coagulation disorders.

CMC v2: Towards More Accurate COVID-19 Detection with Discriminative Video Priors (preprint)

This paper presents our solution for the 2nd COVID-19 Competition, occurring in the framework of the AIMIA Workshop at the European Conference on Computer Vision (ECCV 2022). In our approach, we employ the winning solution last year which uses a strong 3D Contrastive Mixup Classifcation network (CMC v1) as the baseline method, composed of contrastive representation learning and mixup classification. In this paper, we propose CMC v2 by introducing natural video priors to COVID-19 diagnosis. Specifcally, we adapt a pre-trained (on video dataset) video transformer backbone to COVID-19 detection. Moreover, advanced training strategies, including hybrid mixup and cutmix, slicelevel augmentation, and small resolution training are also utilized to boost the robustness and the generalization ability of the model. Among 14 participating teams, CMC v2 ranked 1st in the 2nd COVID-19 Competition with an average Macro F1 Score of 89.11%.

Boosting COVID-19 Severity Detection with Infection-aware Contrastive Mixup Classification (preprint)

This paper presents our solution for the 2nd COVID-19 Severity Detection Competition. This task aims to distinguish the Mild, Moderate, Severe, and Critical grades in COVID-19 chest CT images. In our approach, we devise a novel infection-aware 3D Contrastive Mixup Classification network for severity grading. Specifcally, we train two segmentation networks to first extract the lung region and then the inner lesion region. The lesion segmentation mask serves as complementary information for the original CT slices. To relieve the issue of imbalanced data distribution, we further improve the advanced Contrastive Mixup Classification network by weighted cross-entropy loss. On the COVID-19 severity detection leaderboard, our approach won the first place with a Macro F1 Score of 51.76%. It significantly outperforms the baseline method by over 11.46%.

Safety, Tolerability, and Immunogenicity of PIKA-Adjuvanted Re-combinant SARS-CoV-2 Spike (S) Protein Subunit Vaccine in Healthy Adults: Interim results of an open-label and randomised Phase 1 clinical trial. (preprint)

Background: This COVID-19 pandemic has caused unprecedented morbidity, mortality, and global economic instability. Several approved vaccines demonstrated to be effective prevention against COVID-19. We aimed to evaluate the safety and immunogenicity of the PIKA-adjuvanted recombinant SARS-C0V-2 Spike (S) protein subunit vaccine in adults as a primary immunization and as a booster dose against SARS-C0V-2 infection. Methods: This was a Phase I, open label, dose-escalation study of 3 dose levels of the SARS-CoV-2 spike antigen administered intramuscularly in combination with a fixed dosage of PIKA adjuvant vaccine to evaluate the safety, tolerability, and immunogenicity of PIKA COVID-19 vaccine candidate in healthy adults. The study planned to have 3 arms: Arm A included subjects who had never received any Covid 19 vaccination or have had Covid 19 infection for > 6 months prior to enrolment, Arm B1 included subjects who had completed their primary series of Covid 19 vaccination with an inactivated Covid 19 vaccine and Arm B2 which included subjects whose primary series was completed with mRNA Covid 19 vaccine. The primary safety outcome was adverse events and safety laboratory parameters, and the secondary immunogenicity outcome was neutralizing antibody geometric mean titers and seroconversion rates against the wild type virus, Delta and Omicron variants. Findings: This interim analysis report presented the results of Arm A and Arm B1 who completed Day 35 for 2 doses in Arm A and Day 28 for a single booster dose in Arm B1. Safety results: Arm A: 60% of participants reported mainly solicited AEs after first and second vaccine. Most of those were local (mainly pain/tenderness) with few systemic (mainly fever and headaches). The majority of participants reported unsolicited events after vaccine which were mainly investigations in hematology/hepatobiliary/ Renal or Urine tract infection urine analysis. At least 80% of the participants reported mild AEs. There were 4 SAEs that were mild and were resolved. Also there were 2 medically attended AEs. Arm B1: Less than 50% of the participants reported solicited adverse events which were mainly local (pain and tenderness) and were mild. Also, less than half of the participants reported unsolicited events which were mainly investigations in hematology/hepatobiliary/ Renal or Urine tract infection urine analysis. There were no SAE and Medically attended AEs reported. Immunogenicity results: Arm A: The neutralizing antibody GMTs at day 35 were substantially higher than those at baseline for all dose groups and all variants. Seroconversion rates at 35 days ranged between 85.7% and 92.9% for 5microgram dose group, 92.9% and 100% for the 10microgram dose group and between 70% and 80% for the high dose group. Arm B1: Similar to Arm A, neutralizing antibody GMTs at day 28 were substantially higher than those at baseline for all dose groups and all variants. Seroconversion rates at 28 days ranged between 92.9% and 100% for 5microgram dose group, 80% and 100% for the 10microgram dose group and between 50% and 64.3% for the high dose group. Conclusion: The findings demonstrated that the PIKA Covid 19 vaccine is safe, well tolerated, immunogenic and can be used as a primary vaccination or as a booster dose in participants who had completed an inactivated Covid 19 vaccination series. A comparison of the immune responses presented in this interim analysis showed that geometric mean titer (GMTs) of neutralizing antibody against wild type of SARS-CoV-2 virus, Delta and Omicron of the 5microgram group was higher than the 10 microgram and 20 microgram, therefore the 5microgram was selected as the recommended dose for the Phase II and III clinical development of the PIKA Covid 19 vaccine.

The Resilience Evaluation of Agricultural Supply Chain in Green Transformation under "Double-Carbon" Emission Goal

The "carbon peak and carbon neutral" emission target has set new requirements for the supply chain structure, exacerbated by the complexity and vulnerability of the agricultural sector and global supply chains after the COVID-19 outbreak. Under these circumstances, the resilience evaluation of the agricultural supply chain based on green transformation became an important subject. Based on this topic with outstanding problems, this paper evaluates the resilience level of the agricultural supply chain in northeast China with the goal of achieving the "double carbon" objective. By focusing on its resilience, we selected Heilongjiang, Jilin, and Liaoning provinces as research subjects and collected the agricultural supply chain-related data from 2010 to 2019. Based on the relationship between supply chain nodes and the operation system, an evaluation model containing three levels was established. The entropy weight method and TOWA operator were used to carry out secondary weighting on the evaluation system and time levels containing 12 indicators, following the evaluation of the resilience level of the agricultural supply chain in three static and dynamic dimensions using the grey correlation method. The results show that the importance of the evaluation level of "internode resilience level" has always been a priority during the decade. Therefore, it is pointed out that the resilience construction and green transformation of the agricultural supply chain should be strengthened and implemented from the following three aspects: strengthening agricultural modernization, optimizing supply chain operation, and the implementation and promotion of effective policies. [ FROM AUTHOR] Copyright of Mathematical Problems in Engineering is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Specific Pupylation as IDEntity Reporter (SPIDER) for the identification of Protein-Biomolecule interactions (preprint)

Protein-biomolecule interactions play pivotal roles in almost all biological processes, the identification of the interacting protein is essential. By combining a substrate-based proximity labelling activity from the pupylation pathway of Mycobacterium tuberculosis , and the streptavidin (SA)-biotin system, we developed S pecific P upylation as IDE ntity R eporter (SPIDER) for identifying protein-biomolecular interactions. As a proof of principle, SPIDER was successfully applied for global identification of interacting proteins, including substrates for enzyme (CobB), the readers of m 6 A, the protein interactome of mRNA, and the target proteins of drug (lenalidomide). In addition, by SPIDER, we identified SARS-CoV-2 Omicron variant specific receptors on cell membrane and performed in-depth analysis for one candidate, Protein-g. These potential receptors could explain the differences between the Omicron variant and the Prototype strain, and further serve as target for combating the Omicron variant. Overall, we provide a robust technology which is applicable for a wide-range of protein-biomolecular interaction studies.

Lymphocyte-C-reactive protein ratio can differentiate disease severity of COVID-19 patients and serve as an assistant screening tool for hospital and ICU admission (preprint)

In this study, we aimed to explore whether Lymphocyte-C-reactive protein ratio (LCR) can differentiate disease severity of Coronavirus disease 2019 (COVID-19) patients and its value as an assistant screening tool for admission to the hospital and the intensive care unit (ICU). A total of 184 adult COVID-19 patients from the COVID-19 Treatment Center in Heilongjiang Province at the First Affiliated Hospital of Harbin Medical University between January 2020 and March 2021 were included in this study. Patients were divided into asymptomatic infection group, mild group, moderate group, severe group, and critical group according to the Diagnosis and Treatment of New Coronavirus Pneumonia (9th edition). Demographic and clinical data including gender, age, comorbidities, severity of COVID-19, white blood cell count (WBC), neutrophil proportion (NEUT%), lymphocyte count (LYMPH), lymphocyte percentage (LYM%), red blood cell distribution width (RDW), platelet (PLT), C-reaction protein (CRP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), serum creatinine (SCr), albumin (ALB), total bilirubin (TB), direct bilirubin (DBIL), indirect bilirubin (IBIL), and D-Dimer were obtained and collated from medical records at admission, from which sequential organ failure assessment (SOFA) score and LCR were calculated, and all above indicators were compared among groups. Multiple clinical parameters, including LYMPH, CRP and LCR, showed significant differences among groups. The related factors to classify COVID-19 patients into moderate, severe and critical groups included age, number of comorbidities, WBC, LCR, and AST. Among these factors, number of comorbidities showed the greatest effect, and only WBC and LCR were protective factors. The area under the receiver operating characteristic (ROC) curve of LCR to classify COVID-19 patients into moderate, severe and critical groups was 0.176. The cut-off value of LCR, and the sensitivity and specificity of ROC curve were 1780.7050, 84.6% and 66.2%, respectively. The related factors to classify COVID-19 patients into severe and critical groups included number of comorbidities, PLT, LCR, and SOFA score. Among these factors, SOFA score showed the greatest effect, and LCR was the only protective factor. The area under ROC curve of LCR to classify COVID-19 patients into severe and critical groups was 0.106. The cut-off value of LCR and the sensitivity and specificity of ROC curve were 571.2200, 81.3% and 90.0%, respectively. In summary, LCR can differentiate disease severity of COVID-19 patients and serve as a simple and objective assistant screening tool for hospital and ICU admission.

Predictive value of lactate dehydrogenase to albumin ratio (LAR) in patients with coronavirus Disease 2019 (COVID-19) (preprint)

Coronavirus Disease-2019 (COVID-19) is an emerging acute infectious disease around the world. Therefore, it is crucial to identify the risk factors of in-hospital mortality and disease severity for COVID-19 patients. We firstly proposed a biomarker ratio, lactate dehydrogenase to albumin ratio (LAR) may be more reliable to assess the predictive value of LAR for in-hospital mortality and early identification of critical COVID-19 patients. A retrospective study was conducted including patients (≥18 years old) with laboratory-confirmed COVID-19 infection who had been discharged or had died from 1 February to 29 February, 2020. The study included 321 patients and the median age of the 321 patients was 63.0 (IQR 51.0-70.0), ranging from 19 to 95 years old and 180 (56.1%) patients were male. 142 (44.2%) patients had 1 or more coexisting comorbidity. The most common symptoms on admission were fever(289[90%]) and cough(258[80.4%]). In multivariable logistic regression, only older age (OR, 1.11; 95% CI, 1.05-1.16), WBC count (OR, 1.26; 95% CI, 1.11-1.44), lymphocyte count (OR, 0.78; 95% CI, 0.62-0.99) and LAR (OR, 1.29; 95% CI, 1.18-1.40) were found to be significantly associated with in-hospital death. ROC analysis showed that LAR had a higher AUC (0.917) and the highest specificity(84.0%) and sensitivity(84.6%). Furthermore, the results showed that LAR had a higher AUC (0.931) to differentiate critical from mild patients and had a sensitivity of 87.7% and a specificity of 82.1%. Besides, LAR had an AUC (0.861) to differentiate critical from severe patients and had a sensitivity of 86.0% and a specificity of 73.8% and the role of LAR to distinguish severe from mild patients was the worst. To the best of our knowledge, a high LAR appears to predict higher odds of mortality and differentiate critical patients from mild or severe COVID-19 patients.

Regional Disparities and Influencing Factors of Eco-Efficiency of Arable Land Utilization in China

Eco-efficiency of arable land utilization (EALU) emphasizes efficient coordination between land use systems and ecosystems. It is therefore of great significance for agricultural sustainability based on the systematic assessment of EALU. This study took carbon emissions and non-point source pollution resulting from arable land utilization into the measurement system of EALU, and a super-SBM model, kernel density estimation and Tobit regression model were used to analyze regional differences and influencing factors of EALU for 31 provinces in China from 2000 to 2019. The results showed that there was an upward trend in EALU in China from 0.4393 in 2000 to 0.8929 in 2019, with an average annual growth rate of 4.01%. At the regional level, the EALU of three categories of grain functional areas generally maintains an increasing trend, with the highest average value of EALU in main grain marketing areas (MGMAs), followed by grain producing and marketing balance areas (GPMBAs) and main grain producing areas (MGPAs). There are obvious differences in EALU among provinces, and the number of provinces with high eco-efficiency has increased significantly, showing a spatial distribution pattern of “block” clustering. In terms of dynamic evolution, kernel density curves reflect the evolution of EALU in China and grain functional areas with different degrees of polarization characteristics. The results of Tobit regression show that natural conditions, financial support for agriculture, science and technology inputs, level of industrialization, agricultural mechanization, and the living standards of farmers are significant factors resulting in regional disparities of EALU. Therefore, this study proposes the implementation of differentiated arable land use/agricultural management strategies to improve the sustainable utilization of arable land.

Broad and Long-lasting Immune Response against SARS-CoV-2 Omicron and Other Variants by PIKA-Adjuvanted Recombinant SARS-CoV-2 Spike (S) Protein Subunit Vaccine (YS-SC2-010) (preprint)

Recently SARS-CoV-2 Omicron (B.1.1.529) variant was identified in South Africa with numerous mutations in spike protein, and numerous community infections have been reported and raised grave concern around the world. Some studies found that the neutralization effects of several licensed vaccines against Omicron were dramatically reduced, which significantly affected antibody mediated protection, especially for individuals whose immunization were completed after extended period. In this regard, we studied the persistence and neutralization activity toward mutant strains in animal serum immunized with PIKA-adjuvanted recombinant SARS-CoV-2 spike protein subunit vaccine (YS-SC2-010). Here we are reporting that animal serum collected at 596 days after immunization with YS-SC2-010 still retains high and persistent neutralizing activity against all the Variant of Concern (VOC) variants, including Omicron variant. Although it is a blessed event to achieve 20 months long neutralization against Omicron variant after immunization with YS-SC2-010, it was also founded that the neutralization effect of immune serum on Omicron decreased by 6.29 folds as compared to D614G, more significantly when compared with other mutant strains.

Depression and anxiety and assciated factors among college students returned to campus during the outbreak of COVID-19

Objective: The purpose of this study was to investigate the state of depression and anxiety and associated factors of back-to-school college students during the outbreak of COVID-19, so as to provide theoretical basis for emotional counseling and psychological crisis intervention after long-term school closure due to epidemic outbreak.

COVID-ONE-humoral immune: The One-stop Database for COVID-19-specific Antibody Responses and Clinical Parameters (preprint)

Coronavirus disease 2019 (COVID-19), which is caused by SARS-CoV-2, varies with regard to symptoms and mortality rates among populations. Humoral immunity plays critical roles in SARS-CoV-2 infection and recovery from COVID-19. However, differences in immune responses and clinical features among COVID-19 patients remain largely unknown. Here, we report a database for COVID-19-specific IgG/IgM immune responses and clinical parameters (COVID-ONE humoral immune). COVID-ONE humoral immunity is based on a dataset that contains the IgG/IgM responses to 21 of 28 known SARS-CoV-2 proteins and 197 spike protein peptides against 2,360 COVID-19 samples collected from 783 patients. In addition, 96 clinical parameters for the 2,360 samples and information for the 783 patients are integrated into the database. Furthermore, COVID-ONE humoral immune provides a dashboard for defining samples and a one-click analysis pipeline for a single group or paired groups. A set of samples of interest is easily defined by adjusting the scale bars of a variety of parameters. After the "START" button is clicked, one can readily obtain a comprehensive analysis report for further interpretation. COVID-ONE-humoral immune is freely available at www.COVID-ONE.cn.

COVID-ONE-humoral immune: The One-stop Database for COVID-19-specific Antibody Responses and Clinical Parameters (preprint)

Coronavirus disease 2019 (COVID-19), which is caused by SARS-CoV-2, varies with regard to symptoms and mortality rates among populations. Humoral immunity plays critical roles in SARS-CoV-2 infection and recovery from COVID-19. However, differences in immune responses and clinical features among COVID-19 patients remain largely unknown. Here, we report a database for COVID-19-specific IgG/IgM immune responses and clinical parameters (COVID-ONE humoral immune). COVID-ONE humoral immunity is based on a dataset that contains the IgG/IgM responses to 21 of 28 known SARS-CoV-2 proteins and 197 spike protein peptides against 2,360 COVID-19 samples collected from 783 patients. In addition, 96 clinical parameters for the 2,360 samples and information for the 783 patients are integrated into the database. Furthermore, COVID-ONE humoral immune provides a dashboard for defining samples and a one-click analysis pipeline for a single group or paired groups. A set of samples of interest is easily defined by adjusting the scale bars of a variety of parameters. After the START button is clicked, one can readily obtain a comprehensive analysis report for further interpretation. COVID-ONE-humoral immune is freely available at www.COVID-ONE.cn.

The impact of intervention to the incidence of natural focus diseases during the outbreak of COVID-19 in Jiangsu Province, China (preprint)

Doxorubicin (DOX) is a well-known chemotherapeutic drug for most malgnencies including breast cancer and leukemia whilst the usage of DOX is limited owing to its cardiotoxicity. The present study analyzed the effects of crocin on doxorubicin’s cardiotoxic efect in rat myocardium and searched their mechanistic interaction in the pathogenesis of DOX-induced myocardial toxicity. Forty rats were divided into four groups; (a) control (received normal saline as a dose of 1 ml/kg by ip for 15 days), (b) Crocin (received crocin as a dose of 40 mg/kg/24h by ip for 15 days), (c) DOX (received DOX as a dose of 2 mg/kg/48h by ip in six injection, cumulative dose 12 mg/kg), and (d) DOX+Crocin (received DOX as a dose of 2 mg/kg/48h by ip in six injection and crocin as a dose of 40 mg/kg/24h ip for 15 days). According to the present study, DOX administration caused significant increases in lipid indices (triglyseride, low-dencity lipoproteins and very low-dencity lipoproteins) as well as cardiac markers (Creatine kinase-muscle/brain and Cardiac Troponin I). Morever, DOX caused significant increases in oxidative stress parameters (malondialdehyde and total oxidant status) as well as decreases in antioxidant defense systems (glutathione, superoxide dismutase, catalase and total antioxidant status). The present study also demonstrated that co-administration of crocin with DOX significantly ameliorated the lipid profile and biochemical parameters in rats receiving DOX. The results were supported by histopathological and immunohistochemical evaluations. Taken together, our results reveal that crocin might be a cardioprotective agent in DOX treated patients for cancer.

Mechanism of a COVID-19 nanoparticle vaccine candidate that elicits a broadly neutralizing antibody response to SARS-CoV-2 variants (preprint)

Vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are essential for combating the coronavirus disease 2019 (COVID-19) pandemic. Neutralizing antibody responses to the original Wuhan-Hu-1 strain that were generated during infection and vaccination showed lower effectiveness against variants of concern. Here, we demonstrated that mouse plasma induced by protein nanoparticles that present rationally designed S2G{Delta}HR2 spikes can neutralize the B.1.1.7, B.1.351, and P.1 variants with comparable titers. The mechanism of nanoparticle vaccine-induced immunity was examined in mice for an I3-01v9 60-mer that presents 20 stabilized spikes. Compared with the soluble spike, this nanoparticle showed 6-fold longer retention, 4-fold greater presentation on follicular dendritic cell dendrites, and 5-fold higher germinal center reactions in lymph node follicles. Intact nanoparticles in lymph node tissues were visualized by transmission electron microscopy. In conclusion, spike-presenting protein nanoparticles that induce robust long-lived germinal centers may provide a vaccine solution for emerging SARS-CoV-2 variants.

SARS-CoV-2 Antibody Signatures for Predicting the Outcome of COVID-19 (preprint)

Background: The COIVD-19 global pandemic is far from ending. There is an urgent need to identify applicable biomarkers for predicting the outcome of COVID-19. Growing evidences have revealed that SARS-CoV-2 specific antibodies remain elevated with disease progression and severity in COIVD-19 patients. We assumed that antibodies may serve as biomarkers for predicting disease outcome.Method: By taking advantage of a newly developed SARS-CoV-2 proteome microarray, we surveyed IgM/IgG responses against 20 SARS-CoV-2 proteins in 1,034 hospitalized COVID-19 patients on admission, who were followed till 66 days. The microarray results were further correlated with clinical information, laboratory test results and patient outcomes. Cox proportional hazards model was used to explore the association between SARS-CoV-2 specific antibodies and COVID-19 mortality.Results: We found that high level of IgM against ORF7b at the time of hospitalization is an independent predictor of patient survival ( p  trend = 0.002), while levels of IgG responses to 6 non-structural proteins and 1 accessory protein, i. e., NSP4, NSP7, NSP9, NSP10, RdRp (NSP12), NSP14, and ORF3b, possess significant predictive power for patient death, even after further adjustments for demographics, comorbidities, and common laboratory markers for disease severity (all with p trend < 0.05). Spline regression analysis indicated that the correlation between ORF7b IgM, NSP9 IgG, and NSP10 IgG and the risk of COVID-19 mortality shows linear ( p = 0.0013, 0.0073 and 0.0003, respectively). Their AUCs for predictions, determined by computational cross-validations (validation1), were 0.74 (cut-off = 7.59), 0.66 (cut-off = 9.13), and 0.68 (cut-off = 6.29), respectively. Further validations were conducted in the second and third serial samples of these cases (validation2A, n = 633, validation2B, n = 382), with high accuracy of prediction for outcome.Conclusion: These findings have important implications for improving clinical management, and especially for developing medical interventions and vaccines.Funding Statement: This work was supported by grants from the Fundamental Research Funds for the Central Universities (HUST COVID-19 Rapid Response Call No. 2020kfyXGYJ040) and Wuhan Bureau of Science and Technology (No. 2020020601012218).Declaration of Interests: The authors declare no conflicts of interest.Ethics Approval Statement: The study was approved by the Ethical Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (IRB ID:TJ-C20200128).