Impact of vaccination on kinetics of neutralizing antibodies against SARS-CoV-2 by Serum live neutralization test based on a prospective cohort.

How much the vaccine contributes to the induction and development of neutralizing antibodies (NAbs) of breakthrough cases relative to those unvaccinated-infected cases is not fully understood. We conducted a prospective cohort study and collected serum samples from 576 individuals who were diagnosed with SARS-CoV-2 Delta strain infection, including 245 breakthrough cases and 331 unvaccinated-infected cases. NAbs were analyzed by live virus microneutralization test and transformation of NAb titer. NAbs titers against SARS-CoV-2 ancestral and Delta variant in breakthrough cases were 7.8-fold and 4.0-fold higher than in unvaccinated-infected cases, respectively. NAbs titers in breakthrough cases peaked at the second week after onset/infection. However, the NAbs titers in the unvaccinated-infected cases reached their highest levels during the third week. Compared to those with higher levels of NAbs, those with lower levels of NAbs had no difference in viral clearance duration time (P>0.05), did exhibit higher viral load at the beginning of infection/maximum viral load of infection. NAb levels were statistically higher in the moderate cases than in the mild cases (P<0.0001). Notably, in breakthrough cases, NAb levels were highest longer than 4 months after vaccination (Delta strain: 53118.2 U/mL), and lowest in breakthrough cases shorter than 1 month (Delta strain: 7551.2 U/mL). Cross-neutralization against the ancestral strain and the current circulating isolate (Omicron BA.5) was significantly lower than against the Delta variant in both breakthrough cases and unvaccinated-infected cases. Our study demonstrated that vaccination could induce immune responses more rapidly and greater which could be effective in controlling SARS-CoV-2.

Kinetics of SARS-CoV-2 neutralizing antibodies in Omicron breakthrough cases with inactivated vaccination: Role in inferring the history and duration of infection.

Background: The quantitative level and kinetics of neutralizing antibodies (NAbs) in individuals with Omicron breakthrough infections may differ from those of vaccinated individuals without infection. Therefore, we aimed to evaluate the difference in NAb levels to distinguish the breakthrough cases from the post-immunized population to identify early infected person in an outbreak epidemic when nasal and/or pharyngeal swab nucleic acid real-time PCR results were negative. Methods: We collected 1077 serum samples from 877 individuals, including 189 with Omicron BA.2 breakthrough infection and 688 post-immunized participants. NAb titers were detected using the surrogate virus neutralization test, and were log(2)-transformed to normalize prior to analysis using Student's unpaired t-tests. Geometric mean titers (GMT) were calculated with 95% confidence intervals (CI). Linear regression models were used to identify factors associated with NAb levels. We further conducted ROC curve analysis to evaluate the NAbs' ability to identify breakthrough infected individuals in the vaccinated population. Results: The breakthrough infection group had a consistently higher NAb levels than the post-immunized group according to time since the last vaccination. NAb titers in the breakthrough infection group were 6.4-fold higher than those in the post-immunized group (GMT: 40.72 AU/mL and 6.38 AU/mL, respectively; p<0.0001). In the breakthrough infection group, the NAbs in the convalescent phase were 10.9-fold higher than in the acute phase (GMT: 200.48 AU/mL and 18.46 AU/mL, respectively; p<0.0001). In addition, the time since infection, booster vaccination, and the time since last vaccination were associated with log(2)-transformed NAb levels in the breakthrough infection group. ROC curve analysis showed that ROC area was largest (0.728) when the cut-off value of log(2)-transformed NAb was 6, which indicated that NAb levels could identify breakthrough infected individuals in the vaccinated population. Conclusion: Our study demonstrates that the NAb titers of Omicron BA.2 variant breakthrough cases are higher than in the post-immunized group. The difference in NAb levels could be used to identify cases of breakthrough infection from the post-immunized population in an outbreak epidemic.

Discovery of inhibitors against SARS-CoV-2 main protease using fragment-based drug design.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiological agent of coronavirus disease 2019 (COVID-19), in which the main protease (Mpro) plays an important role in the virus's life cycle. In this work, two representative peptide inhibitors (11a and PF-07321332) were selected, and their interaction mechanisms of non-covalently bound with Mpro were firstly investigated by means of molecular dynamical simulation. Then, using the fragment-based drug design method, some fragments from the existing SARS-CoV and SARS-CoV-2 inhibitors were selected to replace the original P2 and P3 fragments, resulting in some new molecules. Among them, two molecules (O-74 and N-98) were confirmed by molecular docking and molecular dynamics simulation, and ADMET properties prediction was employed for further verification. The results shown that they presented excellent activity and physicochemical properties, and had the potential to be new inhibitors for SARS-CoV-2 main protease.

Biological effect of black phosphorus nanosheets on the interaction between SARS-CoV-2 S protein and ACE2.

The binding of the spike glycoprotein (S protein) in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to angiotensin-converting enzyme 2 (ACE2) is the main pathway that leads to serious coronavirus disease 2019 (COVID-19) infection. In the biomedical applications of various nanomaterials, black phosphorus nanosheets (BP) have been receiving increasing attention owing to their excellent characteristics. In this study, the biological effect of BP on the interaction between the S protein and ACE2 was investigated by molecular dynamics simulations. The results indicated that the ACE2 could be quickly and stably adsorbed on the BP surface by non-specific binding and retain its structural integrity. Compared with the case without BP, the interaction of the S protein bound to ACE2 adsorbed on the BP surface was greatly weakened, including hydrogen bonds, salt bridges, and van der Waals forces. This study not only reveals that BP could effectively obstruct the binding of S protein and ACE2, which may provide a potential and reasonable drug carrier to further enhance the curative effect of inhibitors against SARS-CoV-2 infection, but also presents a novel interference mechanism for protein-protein interactions caused by nanomaterials.

A bibliometric analysis on global eHealth

Background The current coronavirus disease 2019 pandemic highlights the potential of eHealth. Drawing the knowledge map of eHealth research through data mining and visual analysis technology was helpful to systematically present the research status and future trends of global academic circles. Methods Based on the web of Science Core Collection (SCIE/SSCI) database, using bibliometric theory and visual analysis technology, this work analyzed the global eHealth research publications from 2000 to 2021, and introduced the interdisciplinary characteristics, hot topics and future trends in this field. Results A total of 10188 authors, 891 journals, 3586 institutions, 98 countries using 12 languages had conducted eHealth research in the world. The United States, the Netherlands, Australia and the United Kingdom were the main forces and international cooperation. However, the international co-operation between Eastern and Western countries was still relatively few. The frontier of global eHealth research mainly focused on #0eHealth innovation, #1physical activity, #2generalised anxiety disorder, #3lightweight authentication protocol, #4 eHealth information, #5technology readiness, #6 ehealth literacy scale, #7family carer, #8citance analysis, #9 guiding patient. Clusters #3 lightweight authentication protocol and #9 guiding patient were the latest clusters, indicating the research trend and direction of eHealth in the future. Conclusions Cooperation network framework at the regional, national and global levels and the cooperation of multidisciplinary teams with complementary backgrounds and expertise were needed to realize the in-depth popularization and application of eHealth knowledge. Interdisciplinary international cooperation should be the trend of eHealth research in the future.

Accurately Differentiating Between Patients With COVID-19, Patients With Other Viral Infections, and Healthy Individuals: Multimodal Late Fusion Learning Approach.

BACKGROUND: Effectively identifying patients with COVID-19 using nonpolymerase chain reaction biomedical data is critical for achieving optimal clinical outcomes. Currently, there is a lack of comprehensive understanding in various biomedical features and appropriate analytical approaches for enabling the early detection and effective diagnosis of patients with COVID-19. OBJECTIVE: We aimed to combine low-dimensional clinical and lab testing data, as well as high-dimensional computed tomography (CT) imaging data, to accurately differentiate between healthy individuals, patients with COVID-19, and patients with non-COVID viral pneumonia, especially at the early stage of infection. METHODS: In this study, we recruited 214 patients with nonsevere COVID-19, 148 patients with severe COVID-19, 198 noninfected healthy participants, and 129 patients with non-COVID viral pneumonia. The participants' clinical information (ie, 23 features), lab testing results (ie, 10 features), and CT scans upon admission were acquired and used as 3 input feature modalities. To enable the late fusion of multimodal features, we constructed a deep learning model to extract a 10-feature high-level representation of CT scans. We then developed 3 machine learning models (ie, k-nearest neighbor, random forest, and support vector machine models) based on the combined 43 features from all 3 modalities to differentiate between the following 4 classes: nonsevere, severe, healthy, and viral pneumonia. RESULTS: Multimodal features provided substantial performance gain from the use of any single feature modality. All 3 machine learning models had high overall prediction accuracy (95.4%-97.7%) and high class-specific prediction accuracy (90.6%-99.9%). CONCLUSIONS: Compared to the existing binary classification benchmarks that are often focused on single-feature modality, this study's hybrid deep learning-machine learning framework provided a novel and effective breakthrough for clinical applications. Our findings, which come from a relatively large sample size, and analytical workflow will supplement and assist with clinical decision support for current COVID-19 diagnostic methods and other clinical applications with high-dimensional multimodal biomedical features.

Structure of RNA-dependent RNA polymerase from 2019-nCoV, a major antiviral drug target (preprint)

A novel coronavirus (2019-nCoV) outbreak has caused a global pandemic resulting in tens of thousands of infections and thousands of deaths worldwide. The RNA-dependent RNA polymerase (RdRp, also named nsp12), which catalyzes the synthesis of viral RNA, is a key component of coronaviral replication/transcription machinery and appears to be a primary target for the antiviral drug, remdesivir. Here we report the cryo-EM structure of 2019-nCoV full-length nsp12 in complex with cofactors nsp7 and nsp8 at a resolution of 2.9-[A]. Additional to the conserved architecture of the polymerase core of the viral polymerase family and a nidovirus RdRp-associated nucleotidyltransferase (NiRAN) domain featured in coronaviral RdRp, nsp12 possesses a newly identified {beta}-hairpin domain at its N-terminal. Key residues for viral replication and transcription are observed. A comparative analysis to show how remdesivir binds to this polymerase is also provided. This structure provides insight into the central component of coronaviral replication/transcription machinery and sheds light on the design of new antiviral therapeutics targeting viral RdRp. One Sentence SummaryStructure of 2019-nCov RNA polymerase.