Interference reduction isothermal nucleic acid amplification strategy for COVID-19 variant detection

Interference reduction isothermal nucleic acid amplification strategy for COVID-19 variant detection.ga1

Extensive neutralization against SARS-CoV-2 variants elicited by Omicron-specific subunit vaccine as a heterologous booster

To overcome the increased risk of SARS-CoV-2 reinfection or post-vaccination infection caused by the Omicron variant, Omicron-specific vaccines were considered a potential strategy. We reported the increased magnitude and breadth of antibody response against VOCs elicited by post-vaccination Delta and Omicron infection, compared to WT infection without vaccination. Then, in mouse models, three doses of Omicron-RBD immunization elicited comparable neutralizing antibody (NAb) titers with three doses of WT-RBD immunization, but the neutralizing activity was not cross-active. By contrast, a heterologous Omicron-RBD booster following two doses of WT-RBD immunization increased the NAb titers against Omicron by 9 folds than the homologous WT-RBD booster. Moreover, it retains neutralization against both WT and current VOCs. Results suggest that Omicron-specific subunit booster shows its advantages in the immune protection from both WT and current VOCs and that SARS-CoV-2 vaccines including two or more virus lineages might improve the NAb response. Graphical

Rapid assessment of disaster damage and economic resilience in relation to the flooding in Zhengzhou, China in 2021

The timely and accurate assessment of flooding disasters and economic resilience is significant for post-disaster reconstruction and recovery. In July 2021, the National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) Day/Night Band (DNB) daily data were explored as a proxy to assess the flooding damage caused by heavy rainfall in Zhengzhou City, China. A combination of the night-time light (NTL) changes and the radiation normalization method was used to rapidly identify affected areas and extract populations following the flooding disaster. A daily gross domestic product (GDP) prediction model was developed to evaluate the economic resilience of Zhengzhou City using multi-temporal DNB daily and monthly NTL data. The severity of the disaster was estimated by the extent of power outages, flooding crisis regions, and affected populations. It has been predicted that the Zhengzhou economy is unlikely to be restored to its normal level before the end of 2021 owing to the dual impact of the coronavirus outbreak and flooding disaster;the revised recovery-time prediction is late April 2022. We concluded that our NTL data provided new, simple, and effective insights into the post-flooding assessment of the affected areas, populations, GDP forecast, and economic recovery.

Singlehanded or joint race? Stock market volatility prediction

This paper examines whether the realized skewness and kurtosis contain predictability for Shanghai Stock Exchange Sector Index. We find kurtosis contains more information to predict the Shanghai Stock Exchange Sector Index volatility. Importantly, the model considering the combination of both skewness and kurtosis has the best predictability for the stock market volatility. Moreover, we investigate the economic values of the models and asymmetric effects of skewness and kurtosis on stock market volatility, finding skewness (skewness <0) and kurtosis (kurtosis >3) own better forecasting performance. Finally, we discuss the predictability of skewness and kurtosis during two turbulent periods of China's stock bubble and the COVID-19 pandemic.

Discovery of Potent Pyrazoline-Based Covalent SARS-CoV-2 Main Protease Inhibitors (preprint)

While vaccines and antivirals are now being deployed for the current SARS-CoV-2 pandemic, we require additional antiviral therapeutics to not only effectively combat SARS-CoV-2 and its variants, but also future coronaviruses. All coronaviruses have relatively similar genomes that provide a potential exploitable opening to develop antiviral therapies that will be effective against all coronaviruses. Among the various genes and proteins encoded by all coronaviruses, one particularly druggable or relatively easy-to-drug target is the coronavirus Main Protease (3CLpro or Mpro), an enzyme that is involved in cleaving a long peptide translated by the viral genome into its individual protein components that are then assembled into the virus to enable viral replication in the cell. Inhibiting Mpro with a small-molecule antiviral would effectively stop the ability of the virus to replicate, providing therapeutic benefit. In this study, we have utilized activity-based protein profiling (ABPP)-based chemoproteomic approaches to discover and further optimize cysteine-reactive pyrazoline-based covalent inhibitors for the SARS-CoV-2 Mpro. Structure-guided medicinal chemistry and modular synthesis of di- and tri-substituted pyrazolines bearing either chloroacetamide or vinyl sulfonamide cysteine-reactive warheads enabled the expedient exploration of structure-activity relationships (SAR), yielding nanomolar potency inhibitors against Mpro from not only SARS-CoV-2, but across many other coronaviruses. Our studies highlight promising chemical scaffolds that may contribute to future pan-coronavirus inhibitors.

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.

Metacognitive Strategies, Language Learning Motivation, Self-Efficacy Belief, and English Achievement During Remote Learning: A Structural Equation Modelling Approach

Metacognitive strategies, language learning motivation, and self-efficacy belief are crucial to online or remote learning success. The purpose of the present study was to evaluate the interrelationship among metacognitive strategies, language learning motivation, self-efficacy belief, and English learning achievement. The data were collected from three surveys and an English test. The participants were 590 Chinese university students. The findings revealed that self-efficacy belief predicts English learning achievement. In particular, metacognitive strategies and language learning motivation mediate the predictive effects of self-efficacy belief on English learning achievement. The findings show the potential of enhancing online English learning achievement by facilitating learners’ self-efficacy belief, motivation, and metacognitive strategies. Implications can be gained for remote learning within and beyond the coronavirus (COVID-19) context. [ABSTRACT FROM AUTHOR] Copyright of RELC Journal is the property of Sage Publications, Ltd. 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 abstract 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 abstract. (Copyright applies to all Abstracts.)

Preclinical Evaluation and Pilot Clinical Study of Al18F-DX600-BCH for non-invasive PET Mapping of Angiotensin Converting Enzyme 2 in Mammal (preprint)

Angiotensin-converting enzyme 2 (ACE2), a transmembrane protein, is the main entry point for certain coronaviruses including the new coronavirus SARS-CoV-2 to enter cells. Synthesizing the PET imaging probe Al18F-DX600-BCH which is high-affinity ACE2 is aim to detect the expression of ACE2 in body and monitor the therapeutic effect. The Al18F-DX600-BCH was obtained manually with a 20.4% ± 5.2% radiochemical yield without attenuation correction and an over 99% purified radiochemical purity, being stable in vitro within 4 hours and cleared rapidly in blood (the half-lives of the distribution phase and clearance phase were 2.12 min and 25.31 min, respectively). Results of both biodistribution and PET imaging showed that Al18F-DX600-BCH was highly accumulated in the kidney (SUVkidney/normal > 50), and specific uptake in testis (SUVtestis/normal > 10) was observed in rat images. The kidney (++), gastrointestinal (++) and bronchial (+++) cells were evidenced of ACE2 positive by IHC staining of rats. A total of 10 volunteers were enrolled and received PET/CT 1 hour and 2 hours after injection or dynamic PET/CT during 0-330 seconds (NCT04542863), from which strong radioactivity accumulation was mostly observed in the genitourinary system (SUVrenal cortex = 32.00, SUVtestis = 4.56), and moderate accumulation in conjunctiva and nasal mucosa for several cases. This work firstly reported the probe Al18F-DX600-BCH targeting ACE2, conducting preliminary preclinical experiments and a total of 10 clinical transformations, which demonstrated the potential and possibility of non-invasive mapping of ACE2. Trial registration: ClinicalTrials.gov NCT04542863. Registered 9 September 2020.

A Greater increase in C5aR1-level at onset and a smaller decrease in IgG-level after recovery in severer COVID-19 patients: A new analysis of existing data with Ishida’s t-test1 and t-test2 (preprint)

It is important to exactly identify the difference in the changes in a receptor C5aR1-levels at onset and Immunoglobulin G (IgG)-levels after recovery between severe (acute respiratory distress syndrome) and nonsevere (pneumonia) coronavirus disease 2019 patients to reduce the severity of the disease and prevent reinfection with the causative virus. 2012 literature studies were selected from the PubMed Central® databases with keywords of (((covid-19) AND individual) NOT review) AND C5a / IgG. Three studies showing individual expression levels of C5a/C5aR1 / antibody in the patients before and after the passage of time without significance were selected by assessing the literatures. We extracted dynamics where the slope values of the regression line between the initial (X) and changed level (C) with passage of time were not zero significantly (p < 0.05) using SAS-JMP-10. We examined the significance of C in the patients with Ishida’s t-test1 and that of the difference in C between the severe and nonsevere patients with Ishida’s t-test2, which used the values on the above regression line as the expected values of C. These tests suggested a greater increase in C5aR1-levels at onset and a smaller decrease in IgG-levels after recovery in severe patients than in nonsevere patients.

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.

Mask Design for Life in the Midst of COVID-19

Existing medical masks have various disadvantages, such as the environmental damage caused by disposable masks, the discomfort and poor ventilation caused by prolonged mask wearing, and the lack of aesthetic design in mass-produced masks. Thus, this study used quality function deployment, the fuzzy analytic hierarchy process, and fuzzy comprehensive evaluation to research, develop, and design masks. The aforementioned methods were also used to determine the ranking of design requirements. The following priority ranking of design requirements from most to least important was obtained: reducing discomfort at the contact between the mask and the skin (0.265), avoiding foul odor inside the mask (0.187), convenient cleaning and portability (0.166), good airtightness (0.152), suitable aesthetic design for wearing in public and on social occasions (0.130), and reducing waste (0.100). Experts evaluated mask designs, and their opinions were subject to fuzzy analysis. Specifically, 50% of the experts evaluated the designs to be “good” or “very good”. Only 29% of the experts rated the design results as “average”. Thus, the innovative mask designed in this study can meet the needs of users, overcome the drawbacks of existing masks, and provide a feasible solution for the current COVID-19 pandemic.

CryoEM and AI reveal a structure of SARS-CoV-2 Nsp2, a multifunctional protein involved in key host processes. (preprint)

The SARS-CoV-2 protein Nsp2 has been implicated in a wide range of viral processes, but its exact functions, and the structural basis of those functions, remain unknown. Here, we report an atomic model for full-length Nsp2 obtained by combining cryo-electron microscopy with deep learning-based structure prediction from AlphaFold2. The resulting structure reveals a highly-conserved zinc ion-binding site, suggesting a role for Nsp2 in RNA binding. Mapping emerging mutations from variants of SARS-CoV-2 on the resulting structure shows potential host-Nsp2 interaction regions. Using structural analysis together with affinity tagged purification mass spectrometry experiments, we identify Nsp2 mutants that are unable to interact with the actin-nucleation-promoting WASH protein complex or with GIGYF2, an inhibitor of translation initiation and modulator of ribosome-associated quality control. Our work suggests a potential role of Nsp2 in linking viral transcription within the viral replication-transcription complexes (RTC) to the translation initiation of the viral message. Collectively, the structure reported here, combined with mutant interaction mapping, provides a foundation for functional studies of this evolutionary conserved coronavirus protein and may assist future drug design.

Impacts of worldwide individual non-pharmaceutical interventions on COVID-19 transmission across waves and space (preprint)

Governments worldwide have rapidly deployed non-pharmaceutical interventions (NPIs) to mitigate the COVID-19 pandemic. However, the effect of these individual NPI measures across space and time has yet to be sufficiently assessed, especially with the increase of policy fatigue and the urge for NPI relaxation in the vaccination era. Using the decay ratio in the suppression of COVID-19 infections, we investigated the changing performance of different NPIs across waves from global and regional levels (in 133 countries) to national and subnational (in the United States of America [USA]) scales before the implementation of mass vaccination. The synergistic effectiveness of all NPIs for reducing COVID-19 infections declined along waves, from 95.4% in the first wave to 56.0% in the third wave recently at the global level and similarly from 83.3% to 58.7% at the USA national level, while it had fluctuating performance across waves on regional and subnational scales. Regardless of geographical scale, gathering restrictions and facial coverings played significant roles in epidemic mitigation before the vaccine rollout. Our findings have important implications for continued tailoring and implementation of NPI strategies, together with vaccination, to mitigate future COVID-19 waves, caused by new variants, and other emerging respiratory infectious diseases.

Identification of anti-severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) oxysterol derivatives in vitro (preprint)

Development of effective antiviral drugs targeting the severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) are urgently needed to combat the coronavirus disease 2019 (COVID-19). Oxysterols, defined as oxidized derivatives of cholesterol, include endogenous (naturally occurring) cholesterol metabolites as well as semi-synthetic oxysterol derivatives. We have previously studied the use of semi-synthetic oxysterol derivatives as drug candidates for inhibition of cancer, fibrosis, and bone regeneration. In this study, we have screened a panel of naturally occurring and semi-synthetic oxysterol derivatives for anti-SARS-CoV-2 activity, using a cell culture infection assay. We show that the natural oxysterols, 7-ketocholesterol, 22( R )-hydroxycholesterol, 24( S )-hydroxycholesterol, and 27-hydroxycholesterol, substantially inhibited SARS-CoV-2 propagation in cultured cells. Among semi-synthetic oxysterols, Oxy186 displayed antiviral activity comparable to natural oxysterols. In addition, related oxysterol analogues Oxy210 and Oxy232 displayed more robust anti-SARS-CoV-2 activities, reducing viral replication more than 90% at 10 μM and 99% at 15 μM, respectively. When orally administered in mice, peak plasma concentrations of Oxy210 fall into a therapeutically relevant range (19 μM), based on the dose-dependent curve for antiviral activity in our cell culture infection assay. Mechanistic studies suggest that Oxy210 reduced replication of SARS-CoV-2 with disrupting the formation of double membrane vesicles (DMVs), intracellular membrane compartments associated with viral replication. Oxy210 also inhibited the replication of hepatitis C virus, another RNA virus whose replication is associated with DMVs, but not the replication of the DMV-independent hepatitis D virus. Our study warrants further evaluation of Oxy210 and Oxy232 as a safe and reliable oral medication, which could help protect vulnerable populations with increased risk developing COVID-19.

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).

Antibody Landscape Against SARS-CoV-2 Proteome Revealed Significant Differences between Non-Structural/ Accessory Proteins and Structural Proteins (preprint)

The immunogenicity of SARS-CoV-2 proteome is largely unknown, especially for non-structural proteins and accessory proteins. Here we collected 2,360 COVID-19 sera and 601 control sera. We analyzed these sera on a protein microarray with 20 proteins of SARS-CoV-2, built an antibody response landscape for IgG and IgM. We found that non-structural proteins and accessory proteins NSP1, NSP7, NSP8, RdRp, ORF3b and ORF9b elicit prevalent IgG responses. The IgG patterns and dynamic of non-structural/ accessory proteins are different from that of S and N protein. The IgG responses against these 6 proteins are associated with disease severity and clinical outcome and declined sharply about 20 days after symptom onset. In non-survivors, sharp decrease of IgG antibodies against S1 and N protein before death was observed. The global antibody responses to non-structural/ accessory proteins revealed here may facilitate deeper understanding of SARS-CoV-2 immunology.Funding: This work was partially supported by the National Key Research and Development Program of China Grant (No.2016YFA0500600), National Natural Science Foundation of China (No. 31970130, 31600672, 31670831, 31370813, 31900112 and 21907065).Conflict of Interest: The authors declare no competing interests.Ethical Approval: The study was approved by the Ethical Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (ITJ-C20200128). Written informed consent was obtained from all participants enrolled in this study.

Multidimensional Self-Attention for Aspect Term Extraction and Biomedical Named Entity Recognition

Wide attention has been paid to named entity recognition (NER) in specific fields. Among the representative tasks are the aspect term extraction (ATE) in user online comments and the biomedical named entity recognition (BioNER) in medical documents. Existing methods only perform well in a particular field, and it is difficult to maintain an advantage in other fields. In this article, we propose a supervised learning method that can be used for much special domain NER tasks. The model consists of two parts, a multidimensional self-attention (MDSA) network and a CNN-based model. The multidimensional self-attention mechanism can calculate the importance of the context to the current word, select the relevance according to the importance, and complete the update of the word vector. This update mechanism allows the subsequent CNN model to have variable-length memory of sentence context. We conduct experiments on benchmark datasets of ATE and BioNER tasks. The results show that our model surpasses most baseline methods.

Antibody landscape against SARS-CoV-2 proteome revealed significant differences between non-structural/ accessory proteins and structural proteins (preprint)

The immunogenicity of SARS-CoV-2 proteome is largely unknown, especially for non-structural proteins and accessory proteins. Here we collected 2,360 COVID-19 sera and 601 control sera. We analyzed these sera on a protein microarray with 20 proteins of SARS-CoV-2, built an antibody response landscape for IgG and IgM. We found that non-structural proteins and accessory proteins NSP1, NSP7, NSP8, RdRp, ORF3b and ORF9b elicit prevalent IgG responses. The IgG patterns and dynamic of non-structural/ accessory proteins are different from that of S and N protein. The IgG responses against these 6 proteins are associated with disease severity and clinical outcome and declined sharply about 20 days after symptom onset. In non-survivors, sharp decrease of IgG antibodies against S1 and N protein before death was observed. The global antibody responses to non-structural/ accessory proteins revealed here may facilitate deeper understanding of SARS-CoV-2 immunology. HighlightsO_LIAn antibody response landscape against SARS-CoV-2 proteome was constructed C_LIO_LINon-structural/accessory proteins elicit prevalent antibody responses but likely through a different mechanism to that of structural proteins C_LIO_LIIgG antibodies against non-structural/accessory proteins are more associated with disease severity and clinical outcome C_LIO_LIFor non-survivors, the levels of IgG antibodies against S1 and N decline significantly before death C_LI