Simultaneous Detection of SARS-CoV-2 and Six Other Human Coronaviruses by Multiplex PCR and MALDI-TOF MS (preprint)

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is challenging the health systems worldwide, and large population testing is a vital step to control this pandemic. Here, we developed a new method (named HCoV-MS), which combines multiplex PCR with matrix-assisted laser desorption/ionization-time of flight mass spectrometry to simultaneously detect and differentiate seven human coronaviruses (HCoVs). The HCoV-MS method had good specificity and sensitivity, with a detection limit of 1-5 copies/reaction. To validate the HCoV-MS method, we tested 151 clinical samples, and the results showed good concordance with real-time PCR. In addition, 41 D614G variants were identified, which were consistent with the sequencing results. This method was also used in EQAE-SARS-COV in 2020, and all the samples were accurately identified. Taken together, HCoV-MS could be used as an effective method for large-scale detection. It was also capable of detecting key single nucleotide polymorphism about variants.

Clinical features and effectiveness of SARS-CoV-2 vaccine in children with omicron infection in a tertiary hospital during the Omicron wave in China, December 2022–January 2023 (preprint)

There are limited data about Omicron infection in children in China. Here, we evaluated the infection fatality rates, clinical features and efficacy of SARS-CoV-2 vaccine in children with Omicron infection in a tertiary hospital during the first wave of SARS-CoV-2 caused by Omicron in China, December 2022-January 2023.We used the week as a statistical unit, and the positive rate of NAT was 0.03% from December 1 to December 7, the week before the Zero-COVID strategy was relaxed. Following the repeal of the Zero-COVID policy, the positive rate of NAT rose to 8.3% in the first week, peaked at 85.2% in the third week, and then steadily fell.The NAT positive rate in children peaked (90.4%) in the third week following the termination of the Zero-COVID policy.43.6% (232/532) of the 532 pediatric patients received vaccinations, with the majority (95.3%, 221/232) receiving two doses and the remainder receiving one.532 of the 641 pediatric patients who tested positive for NAT were seen in the pediatric outpatient clinic. Eventually, 51 pediatric patients were admitted to hospitals. Overall, the symptoms of infection were mild, and the rate of severe disease was low, whereas vaccination had a favorable effect on lowering the risk of severe illness in children.

Privacy-Preserving Individual-Level COVID-19 Infection Prediction via Federated Graph Learning (preprint)

Accurately predicting individual-level infection state is of great value since its essential role in reducing the damage of the epidemic. However, there exists an inescapable risk of privacy leakage in the fine-grained user mobility trajectories required by individual-level infection prediction. In this paper, we focus on developing a framework of privacy-preserving individual-level infection prediction based on federated learning (FL) and graph neural networks (GNN). We propose Falcon, a Federated grAph Learning method for privacy-preserving individual-level infeCtion predictiON. It utilizes a novel hypergraph structure with spatio-temporal hyperedges to describe the complex interactions between individuals and locations in the contagion process. By organically combining the FL framework with hypergraph neural networks, the information propagation process of the graph machine learning is able to be divided into two stages distributed on the server and the clients, respectively, so as to effectively protect user privacy while transmitting high-level information. Furthermore, it elaborately designs a differential privacy perturbation mechanism as well as a plausible pseudo location generation approach to preserve user privacy in the graph structure. Besides, it introduces a cooperative coupling mechanism between the individual-level prediction model and an additional region-level model to mitigate the detrimental impacts caused by the injected obfuscation mechanisms. Extensive experimental results show that our methodology outperforms state-of-the-art algorithms and is able to protect user privacy against actual privacy attacks. Our code and datasets are available at the link: https://github.com/wjfu99/FL-epidemic.

How fragile we are. Influence of STimulator of INterferon Genes, STING, variants on pathogen recognition and immune response efficiency (preprint)

The STimulator of INterferon Genes (STING) protein is a cornerstone of the human immune response. Its activation by cGAMP upon the presence of cytosolic DNA stimulates the production of type I interferons and inflammatory cytokines which are crucial for protecting cells from infections. STING signaling pathway can also influence both tumor-suppressive and tumor-promoting mechanisms, rendering it an appealing target for drug design. In the human population, several STING variants exist and exhibit dramatic differences in their activity, impacting the efficiency of the host defense against infections. Understanding the differential molecular mechanisms exhibited by these variants is of utmost importance notably towards personalized medicine treatments against diseases such as viral infections (COVID-19, Dengue…), cancers, or auto-inflammatory diseases. Owing to micro-seconds scale molecular modeling simulations and post-processing by contacts analysis and Machine Learning techniques, we reveal the dynamical behavior of four STING variants (wild type, G230A, R293Q, and G230A-R293Q) and we rationalize the variability of efficiency observed experimentally. Our results show that the decrease of STING activity is linked to a stiffening of key-structural features of the binding cavity, together with changes of the interaction patterns within the protein.

Psychological Impact of the COVID-19 Pandemic on Emergency Dental Care Providers on the Front Lines in China.

Coronavirus disease 2019 (COVID-19) is an infectious disease that emerged at the end of 2019. On 30 January 2020, the World Health Organization (WHO) classified it as a pandemic. To examine the psychological effects on dental care providers in China in the midst of the COVID-19 outbreak and factors closely associated with those effects, we conducted a cross-sectional study online with 4 widely used self-administered questionnaires: the Patient Health Questionnaire-9, the General Anxiety Disorder-7, the Perceived Stress Scale-10, and the Acute Stress Disorder Scale. Univariate and multivariate analyses were performed to evaluate the variables that potentially affected the mental health of emergency dental care providers. As a result, 969 out of 1035 questionnaires were included in the analysis, with 642 respondents reporting more than 1 symptom (66.3%). The symptom of perceived stress was reported by the largest proportion of the respondents (66.2%, n = 641), and anxiety the least (7.1%, n = 69). After adjustment for confounders, it was found that dental practitioners with preexisting physical health conditions were at higher risk of depression (odds ratio [OR], 1.972; 95% CI, 1.128-3.448; P = .017), and perceived stress (odds ratio, 2.397 95% CI, 1.283-4.478; P = .006). Additionally, feelings of fear, helplessness, or terror resulting from the possibility of contracting COVID-19 were significantly associated with the prevalence of all the 4 psychological symptoms observed (P < .05). In the present study, we found that dental care providers suffered psychological depression, stress, anxiety, and posttraumatic stress disorder (PTSD) during COVID-19, which indicates the importance of psychological support at times of major epidemic outbreaks. Chinese Clinical Trial Registry number: ChiCTR2000031538.

Policy-Aware Mobility Model Explains the Growth of COVID-19 in Cities (preprint)

With the continued spread of coronavirus, the task of forecasting distinctive COVID-19 growth curves in different cities, which remain inadequately explained by standard epidemiological models, is critical for medical supply and treatment. Predictions must take into account non-pharmaceutical interventions to slow the spread of coronavirus, including stay-at-home orders, social distancing, quarantine and compulsory mask-wearing, leading to reductions in intra-city mobility and viral transmission. Moreover, recent work associating coronavirus with human mobility and detailed movement data suggest the need to consider urban mobility in disease forecasts. Here we show that by incorporating intra-city mobility and policy adoption into a novel metapopulation SEIR model, we can accurately predict complex COVID-19 growth patterns in U.S. cities ($R^2$ = 0.990). Estimated mobility change due to policy interventions is consistent with empirical observation from Apple Mobility Trends Reports (Pearson's R = 0.872), suggesting the utility of model-based predictions where data are limited. Our model also reproduces urban "superspreading", where a few neighborhoods account for most secondary infections across urban space, arising from uneven neighborhood populations and heightened intra-city churn in popular neighborhoods. Therefore, our model can facilitate location-aware mobility reduction policy that more effectively mitigates disease transmission at similar social cost. Finally, we demonstrate our model can serve as a fine-grained analytic and simulation framework that informs the design of rational non-pharmaceutical interventions policies.

Computed tomography in coronavirus disease 2019: diagnosis and clinical significance

Objective To investigate the computed tomography (CT) features of the coronavirus disease 2019 (COVID-19) and the clinical significance, so as to improve our understanding of CT imaging of this disease. Methods The chest CT features of seven COVID-19 patients, who were diagnosed by virus nucleic acid test from Jan. 25 to Feb. 15, 2020 in Changhai Hospital of Naval Medical University (Second Military Medical University), were analyzed retrospectively. There were six males and one female, aged (51.1±18.8) years (range 29-75 years). All the seven patients received chest CT plain scan examimation. The CT images were interpreted by two experienced senior radiologists, and the distribution, location and density of lesions, number of involved lobes, air bronchogram, mediastinal lymphadenopathy and pleural effusion were analyzed. Results The average time from onset of symptoms to CT examination was 3.6 d (range 1-9 d) in the seven COVID-19 patients. The lesions were distributed in single lung in one case and bilateral lungs in six cases. The lesions involved middle and lateral fields of lungs in five cases and the whole field of lungs in two cases. The lesions showed ground-glass opacity in four cases and mixed shadow in three cases. The lesions involved two or less lobes in four cases and five lobes in three cases. One case had air bronchogram. No mediastinal lymphadenopathy or pleural effusion were found. Conclusion COVID-19 patients have characteristic CT findings, which has important clinical significance for the diagnosis and treatment of COVID-19. However, the diagnosis should be confirmed based on the patient's epidemic history, clinical symptoms and laboratory indicators.

Safety, Tolerability and Immunogenicity of a Recombinant Adenovirus Type 5 Vectored COVID-19 Vaccine in Healthy Adults in China: Preliminary Report of a First-In Human Single-Center, Open-Label, Dose-Escalating Clinical Trial (preprint)

Background: We aimed to assess the safety, tolerability and immunogenicity of a recombinant adenovirus type 5 (Ad5) vectored COVID-19 vaccine expressing the spike glycoprotein of a SARS-Cov-2 strain. This is the first-in-human study of a candidate vaccine against COVID-19.Methods: We conducted a single-center, open-label, dose-escalating clinical trial of Ad5 vectored COVID-19 vaccine. Healthy adults aged between 18-60 years were sequentially enrolled and allocated to receive a single intramuscular injection in one of three dose groups: 5 × 10^10, 1×10^11, and 1·5×10^11 viral particles. Safety was assessed over the next 28 days. Specific antibodies were measured on enzyme-linked immunosorbent assay (ELISA), and the neutralizing antibody responses induced by vaccination were detected by using SARS-CoV-2 virus neutralization and pseudovirus neutralization tests. T-cell responses were accessed by enzyme-linked immunospot (ELISpot) and flow-cytometry assays. Results: A total of 108 participants were recruited and received low dose, middle dose, or high dose vaccine, with 36 in each dose group. 30(83·3%), 30(83·3%), and 27(75·0%) recipients in the low dose, middle dose, and high dose groups reported at least one adverse reaction within the first 7 days after the vaccination. The most common injection-site adverse reaction was pain, the most commonly reported systematic adverse reactions were fever, fatigue, headache, and muscle pain. A majority of the adverse reactions that were reported in all dose groups were mild or moderate in severity. No serious adverse event was noted within 28 days post-vaccination. Both ELISA antibodies and neutralizing antibodies increased significantly at day 14, and peaked 28 days post-vaccination. Specific T cell response peaked at day 14 post-vaccination.Conclusions: The Ad5 vectored COVID-19 vaccine is tolerable and immunogenic. Humoral responses against SARS-CoV-2 peaked at day 28 post-vaccination in health adults, and rapid specific T cell responses were noted since day 14.Trial Registration: The study is registered with ClinicalTrials.gov, number NCT04313127. Funding Statement: National Key R&D Program of China (2020YFC10841400), National Science and Technology Major Project (2016ZX10004001, 2018ZX09201005), and CanSino Biotechnology Inc.Declaration of Interests: Mr. Gou report being employees of Tianjin CanSino Biotechnology Inc, No other potential conflict of interest relevant to this article was reported.Ethics Approval Statement: The protocol and informed consent were approved by the Institutional Review Board of the Jiangsu Provincial Center of Disease Control and Prevention. Written informed consents from all participants were obtained before screening. This study was undertaken by Jiangsu Provincial Center of Disease Control and Prevention, Hubei Provincial Center for Disease Control and Prevention and Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology in accordance with the Declaration of Helsinki and Good Clinical Practice.

ACE inhibition and cardiometabolic risk factors, lung ACE2 and TMPRSS2 gene expression, and plasma ACE2 levels: a Mendelian randomization study (preprint)

ObjectivesTo use human genetic variants that proxy angiotensin-converting enzyme (ACE) inhibitor drug effects and cardiovascular risk factors to provide insight into how these exposures affect lung ACE2 and TMPRSS2 gene expression and circulating ACE2 levels. DesignTwo-sample Mendelian randomization (MR) analysis. SettingSummary-level genetic association data. ParticipantsParticipants were predominantly of European ancestry. Variants that proxy ACE inhibitor drug effects and cardiometabolic risk factors (body mass index, chronic obstructive pulmonary disease, lifetime smoking index, low-density lipoprotein cholesterol, systolic blood pressure and type 2 diabetes mellitus) were selected from publicly available genome-wide association study data (sample sizes ranging from 188,577 to 898,130 participants). Genetic association estimates for lung expression of ACE2 and TMPRSS2 were obtained from the Gene-Tissue Expression (GTEx) project (515 participants) and the Lung eQTL Consortium (1,038 participants). Genetic association estimates for circulating plasma ACE2 levels were obtained from the INTERVAL study (4,947 participants). Main outcomes and measuresLung ACE2 and TMPRSS2 expression and plasma ACE2 levels. ResultsThere were no association of genetically proxied ACE inhibition with any of the outcomes considered here. There was evidence of a positive association of genetic liability to type 2 diabetes mellitus with lung ACE2 gene expression in GTEx (p = 4x10-4) and with circulating plasma ACE2 levels in INTERVAL (p = 0.03), but not with lung ACE2 expression in the Lung eQTL Consortium study (p = 0.68). There were no associations between genetically predicted levels of the other cardiometabolic traits with the outcomes. ConclusionsThis study does not provide evidence to support that ACE inhibitor antihypertensive drugs affect lung ACE2 and TMPRSS2 expression or plasma ACE2 levels. In the current COVID-19 pandemic, our findings do not support a change in ACE inhibitor medication use without clinical justification. Summary boxesO_ST_ABSWhat is already known on this topicC_ST_ABSO_LISevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the current coronavirus disease 2019 (COVID-19) pandemic. C_LIO_LISerine protease TMPRSS2 is involved in priming the SARS-CoV-2 spike protein for cellular entry through the angiotensin-converting enzyme 2 (ACE2) receptor. C_LIO_LIExpression of ACE2 and TMPRSS2 in the lung epithelium might have implications for risk of SARS-CoV-2 infection and severity of COVID-19. C_LI What this study addsO_LIWe used human genetic variants that proxy ACE inhibitor drug effects and cardiometabolic risk factors to provide insight into how these exposures affect lung ACE2 and TMPRSS2 expression and circulating ACE2 levels. C_LIO_LIOur findings do not support the hypothesis that ACE inhibitors have effects on ACE2 expression. C_LIO_LIWe found some support for an association of genetic liability to type 2 diabetes mellitus with higher lung ACE2 expression and plasma ACE2 levels, but evidence was inconsistent across studies. C_LI

Computational Evaluation of the COVID-19 3c-like Protease Inhibition Mechanism, and Drug Repurposing Screening (preprint)

The rapid spread of the COVID-19 outbreak is now a global threat with over a million diagnosed cases and more than 70 thousand deaths. Specific treatments and effective drugs regarding such disease are in urgent need. To contribute to the drug discovery against COVID-19, we performed computational study to understand the inhibition mechanism of the COVID-19 3c-like protease, and search for possible drug candidates from approved or experimental drugs through drug repurposing screening against the DrugBank database. Two novel computational methods were applied in this study. We applied the “Consecutive Histogram Monte Carlo” (CHMC) sampling method for understanding the inhibition mechanism from studying the 2-D binding free energy landscape. We also applied the “Movable Type” (MT) free energy method for the lead compound screening by evaluating the binding free energies of the COVID-19 3c-like protease – inhibitor complexes. Lead compounds from the DrugBank database were first filtered using ligand similarity comparison to 19 published SARS 3c-like protease inhibitors. 70 selected compounds were then evaluated for protein-ligand binding affinities using the MT free energy method. 4 drug candidates with strong binding affinities and reasonable protein-ligand binding modes were selected from this study, i.e. Enalkiren (DB03395), Rupintrivir (DB05102), Saralasin (DB06763) and TRV-120027 (DB12199).

[Management and prevention of dental emergency during corona virus disease 2019 (COVID-19) epidemic]

The outbreak of corona virus disease 2019 (COVID-19) has developed rapidly and the situation of prevention and control is severe. During the epidemic period of COVID-19, due to the particularity of diagnosis and treatment of oral diseases, there is great challenges for how to deal with various types of dental emergency. In order to prevent and control the epidemic situation strictly, and to perform a scientific and orderly clinical diagnosis and treatment of dental emergency, this article provided suggestions on personnel management training, procedures and treatment, protection and disinfection of dental emergency during COVID-19 epidemic, and reference for dental institutions and medical staff.