Optimizing Vaccine Site Locations While Considering Travel Inconvenience and Public Health Outcomes (preprint)

During the COVID-19 pandemic, there were over three million infections in Los Angeles County (LAC). To facilitate distribution when vaccines first became available, LAC set up six mega-sites for dispensing a large number of vaccines to the public. To understand if another choice of mega-site location would have improved accessibility and health outcomes, and to provide insight into future vaccine allocation problems, we propose a multi-objective mixed integer linear programming model that balances travel convenience, infection reduction, and equitable distribution. We provide a tractable objective formulation that effectively proxies real-world public health goals of reducing infections while considering travel inconvenience and equitable distribution of resources. Compared with the solution empirically used in LAC in 2020, we recommend more dispersed mega-site locations that result in a 28% reduction in travel inconvenience and avert an additional 1,000 infections.

Extending Dynamic Origin-Destination Estimation to Understand Traffic Patterns During COVID-19 (preprint)

Estimating dynamic Origin-Destination (OD) traffic flow is crucial for understanding traffic patterns and the traffic network. While dynamic origin-destination estimation (DODE) has been studied for decades as a useful tool for estimating traffic flow, few existing models have considered its potential in evaluating the influence of policy on travel activity. This paper proposes a data-driven approach to estimate OD traffic flow using sensor data on highways and local roads. We extend prior DODE models to improve accuracy and realism in order to estimate how policies affect OD traffic flow in large urban networks. We applied our approach to a case study in Los Angeles County, where we developed a traffic network, estimated OD traffic flow between health districts during COVID-19, and analyzed the relationship between OD traffic flow and demographic characteristics such as income. Our findings demonstrate that the proposed approach provides valuable insights into traffic flow patterns and their underlying demographic factors for a large-scale traffic network. Specifically, our approach allows for evaluating the impact of policy changes on travel activity. The approach has practical applications for transportation planning and traffic management, enabling a better understanding of traffic flow patterns and the impact of policy changes on travel activity.

Study of fusion peptide release for the spike protein of SARS-CoV-2.

The spike protein of SARS-CoV-2 can recognize the ACE2 membrane protein on the host cell and plays a key role in the membrane fusion process between the virus envelope and the host cell membrane. However, to date, the mechanism for the spike protein recognizing host cells and initiating membrane fusion remains unknown. In this study, based on the general assumption that all three S1/S2 junctions of the spike protein are cleaved, structures with different forms of S1 subunit stripping and S2' site cleavage were constructed. Then, the minimum requirement for the release of the fusion peptide was studied by all-atom structure-based MD simulations. The results from simulations showed that stripping an S1 subunit from the A-, B- or C-chain of the spike protein and cleaving the specific S2' site on the B-chain (C-chain or A-chain) may result in the release of the fusion peptide, suggesting that the requirement for the release of FP may be more relaxed than previously expected.

The challenges of screen time in children with typical development and children with developmental disorders during COVID-19 pandemic.

Background: The significant lifestyle changes that occurred during the lockdown period associated with the COVID-19 pandemic may have had many potential adverse effects on children, in particular, sedentary screen exposure among children, including those with developmental disorders. We conducted a cross-sectional study to investigate and compare the screen time and outdoor activity time of children with typically development (TD) and those with developmental disorders during and before the emergence of COVID-19, and identified the risk factors related to screen time during the COVID-19 pandemic. Methods: A total of 496 children were surveyed via online questionnaires. Parents or/and children filled in the online questionnaire, including basic characteristics, screen time, outdoor activity time, and other related factors. The Statistical Product and Service Solutions software was used to analyze all data. Results: Children spent less time outdoors (t=14.774, P<0.001) and more time on electronic screens (t=-14.069, P<0.001) during the lockdown period of COVID-19, compared to the periods before COVID-19. Age (P=0.037), pre-COVID-19 screen time (P=0.005), screen time used for learning/education (P<0.001), screen time of siblings (P=0.007), and use of screen devices as electronic babysitters (P=0.005) were risk factors for screen time during the COVID-19 pandemic, while restrictive use of electronic devices by parents (P<0.05) was a protective factor. The screen time of children with autism spectrum disorder (ASD) or attention deficit hyperactivity disorder (ADHD) was significantly longer than children with TD before COVID-19 pandemic, but there is no statistical difference during the COVID-19 pandemic. Conclusions: During the COVID-19 pandemic, children's screen exposure time increased, and outdoor activities decreased significantly. This represents a significant challenge, and we should focus our efforts on managing children's screen time and promoting healthier lifestyles, including children with typical development, as well as those with developmental disorders.

A Porcine Epidemic Diarrhea Virus Isolated from a Sow Farm Vaccinated with CV777 Strain in Yinchuan, China: Characterization, Antigenicity, and Pathogenicity

Porcine epidemic diarrhea virus (PEDV) is a porcine enteric coronavirus globally, causing serious economic losses to the global pig industry since 2010. Here, a PEDV CH/Yinchuan/2021 strain was isolated in a CV777-vaccinated sow farm which experienced a large-scale PEDV invasion in Yinchuan, China, in 2021. Our results demonstrated that the CH/Yinchuan/2021 isolate could efficiently propagate in Vero cells, and its proliferation ability was weaker than that of CV777 at 10 passages (P10). Phylogenetic analysis of the S gene revealed that CH/Yinchuan/2021 was clustered into subgroup GIIa, forming an independent branch with 2020-2021 isolates in China. Moreover, GII was obviously allocated into four clades, showing regional and temporal differences in PEDV global isolates. Notably, CH/Yinchuan/2021 was analyzed as a recombinant originated from an American isolate and a Chinese isolate, with a big recombinant region spanning ORF1a and S1. Importantly, we found that CH/Yinchuan/2021 harbored multiple mutations relative to CV777 in neutralizing epitopes (S10, S1A, COE, and SS6). Homology modelling showed that these amino acid differences in S protein occur on the surface of its structure, especially the insertion and deletion of multiple consecutive residues at the S10 epitope. In addition, cross-neutralization analysis confirmed that the differences in the S protein of CH/Yinchuan/2021 changed its antigenicity compared with the CV777 strain, resulting in a different neutralization profile. Animal pathogenicity test showed that CH/Yinchuan/2021 caused PEDV-typified symptoms and 100% mortality in 3-day-old piglets. These data will provide valuable information to understand the epidemiology, molecular characteristics, evolution, and antigenicity of PEDV circulating in China.

User review analysis of dating apps based on text mining.

With the continuous development of information technology, more and more people have become to use online dating apps, and the trend has been exacerbated by the COVID-19 pandemic in these years. However, there is a phenomenon that most of user reviews of mainstream dating apps are negative. To study this phenomenon, we have used topic model to mine negative reviews of mainstream dating apps, and constructed a two-stage machine learning model using data dimensionality reduction and text classification to classify user reviews of dating apps. The research results show that: firstly, the reasons for the current negative reviews of dating apps are mainly concentrated in the charging mechanism, fake accounts, subscription and advertising push mechanism and matching mechanism in the apps, proposed corresponding improvement suggestions are proposed by us; secondly, using principal component analysis to reduce the dimensionality of the text vector, and then using XGBoost model to learn the low-dimensional data after oversampling, a better classification accuracy of user reviews can be obtained. We hope These findings can help dating apps operators to improve services and achieve sustainable business operations of their apps.

Metabolomic Profiling of Lungs from Mice Reveals the Variability of Metabolites in Pneumocystis Infection and the Metabolic Abnormalities in BAFF-R-Deficient Mice.

Purpose: The incidence of Pneumocystis pneumonia (PCP) in patients without human immunodeficiency virus (HIV) has been increasing. In this study, we aimed to investigate the metabolic changes in Pneumocystis infection and the metabolic abnormalities in B-cell-activating factor receptor (BAFF-R)-deficient mice with Pneumocystis infection. Methods: The important function of B cells during Pneumocystis infection is increasingly recognized. In this study, a Pneumocystis-infected mouse model was constructed in BAFF-R-/- mice and wild-type (WT) mice. Lungs of uninfected WT C57BL/6, WT Pneumocystis-infected, and BAFF-R-/- Pneumocystis-infected mice were used for metabolomic analyses to compare the metabolomic profiles among the groups, with the aim of exploring the metabolic influence of Pneumocystis infection and the influence of mature B-cell deficiency during infection. Results: The results indicated that many metabolites, mainly lipids and lipid-like molecules, were dysregulated in Pneumocystis-infected WT mice compared with uninfected WT C57BL/6 mice. The data also demonstrated significant changes in tryptophan metabolism, and the expression levels of key enzymes of tryptophan metabolism, such as indoleamine 2,3-dioxygenase 1 (IDO1), were significantly upregulated. In addition, B-cell development and function might be associated with lipid metabolism. We found a lower level of alitretinoin and the abnormalities of fatty acid metabolism in BAFF-R-/- Pneumocystis-infected mice. The mRNA levels of enzymes associated with fatty acid metabolism in the lung were upregulated in BAFF-R-/- Pneumocystis-infected mice and positively correlated with the level of IL17A, thus suggesting that the abnormalities of fatty acid metabolism may be associated with greater inflammatory cell infiltration in the lung tissue of BAFF-R-/- Pneumocystis-infected mice compared with the WT Pneumocystis-infected mice. Conclusion: Our data revealed the variability of metabolites in Pneumocystis-infected mice, suggesting that the metabolism plays a vital role in the immune response to Pneumocystis infection.

Seeing the forest and the trees: Holistic view of social distancing on the spread of COVID-19 in China.

The human social and behavioral activities play significant roles in the spread of COVID-19. Social-distancing centered non-pharmaceutical interventions (NPIs) are the best strategies to curb the spread of COVID-19 prior to an effective pharmaceutical or vaccine solution. This study investigates various social-distancing measures' impact on the spread of COVID-19 using advanced global and novel local geospatial techniques. Social distancing measures are acquired through website analysis, document text analysis, and other big data extraction strategies. A spatial panel regression model and a newly proposed geographically weighted panel regression model are applied to investigate the global and local relationships between the spread of COVID-19 and the various social distancing measures. Results from the combined global and local analyses confirm the effectiveness of NPI strategies to curb the spread of COVID-19. While global level strategies allow a nation to implement social distancing measures immediately at the beginning to minimize the impact of the disease, local level strategies fine tune such measures based on different times and places to provide targeted implementation to balance conflicting demands during the pandemic. The local level analysis further suggests that implementing different NPI strategies in different locations might allow us to battle unknown global pandemic more efficiently.

A Novel Universal Primer Multiplex Real-Time PCR (UP-M-rtPCR) Approach for Specific Identification and Quantitation of Cat, Dog, Fox, and Mink Fractions Using Nuclear DNA Sequences.

Adulteration of meat with carnivorous animals (such as cats, dogs, foxes, and minks) can cause ethical problems and lead to disease transmission; however, DNA quantitative methods for four carnivorous species in one tube reaction are still rare. In this study, a carnivore-specific nuclear DNA sequence that is conserved in carnivorous animals but has base differences within the sequence was used to design universal primers for its conserved region and corresponding species-specific probes for the hypervariable region. A novel universal primer multiplex real-time PCR (UP-M-rtPCR) approach was developed for the specific identification and quantitation of cat, dog, fox, and mink fractions in a single reaction, with a 0.05 ng absolute limit of detection (LOD) and 0.05% relative LOD. This approach simplifies the PCR system and improves the efficiency of simultaneous identification of multiple animal-derived ingredients in meat. UP-M-rtPCR showed good accuracy (0.48-7.04% relative deviation) and precision (1.42-13.78% relative standard deviation) for quantitative analysis of cat, dog, fox, and mink DNA as well as excellent applicability for the evaluation of meat samples.

Comparing aerosol exposure and prevention strategies during bystander, pre- hospital, and inpatient cardiopulmonary resuscitation (preprint)

Background To evaluate aerosol exposure risk and prevention strategies during bystander, pre-hospital, and inpatient cardiopulmonary resuscitation (CPR). Methods This study compared hands-only CPR, CPR with a surgical or N95 mask, and CPR with a non-rebreather mask at 15 L/min. 30:2 compression-ventilation ratio CPR was tested with face-mask ventilation (FMV), FMV with a high efficiency particulate air (HEPA) filter; supraglottic airway (SGA), SGA with a surgical mask, SGA with a HEPA filter, or SGA with both. Continuous CPR was tested with an endotracheal tube (ET), ET with a surgical mask, a HEPA filter, or both. Aerosol concentration at the head, trunk, and feet of the mannequin were measured to evaluate exposure to CPR personnel. Results Hands-only CPR with a surgical or N95 face mask coverings and ET tube ventilation CPR with filters showed the lowest aerosol exposure among all study groups, including CPR with NRM oxygenation, FMV, and SGA ventilation. NRM had a mask effect and reduced aerosol exposure at the head, trunk, and feet of the mannequin. FMV with filters during 30:2 CPR reduced aerosol exposure at the head and trunk, but increased at the feet of the mannequin. A tightly-sealed SGA when used with a HEPA filter, reduced aerosol exposure by 21.00%-63.14% compared with a loose-fitting one. Conclusion Hands-only CPR with a proper fit surgical or N95 face mask coverings is as safe as ET tube ventilation CPR with filters, compared with CPR with NRM, FMV, and SGA. FMV or tight-sealed SGA ventilation with filters prolonged the duration to achieve estimated infective dose of SARS-CoV-2 2.4-2.5 times longer than hands-on CPR only. However, a loose-fitting SGA is not protective at all to chest compressor or health workers standing at the foot side of the victim, so should be used with caution even when using with HEPA filters.

Using the concept of circular economy to reduce the environmental impact of COVID-19 face mask waste

COVID-19 pandemic has posed severe threats to the society globally. World Health Organization (WHO) guidelines suggest that people wear face masks as a precautionary measure daily. This has resulted in the generation of massive amounts of mask-associated waste in the environment. Owing to the criticality of the epidemic, there has not been a large-scale investigation on where to discard masks, making this situation daunting. As the pandemic continues, the use of masks continues to increase, repeated use and disposal of masks has become an imperative issue. Most disposable masks comprise chemical fibers in the filter layer. Without proper treatment and disposal, these large amounts of chemical waste will eventually flow into rivers or oceans, leading to serious pollution. Therefore, to reduce the negative effects on the marine environment, it is crucial that we produce reusable masks and reduce disposable wearing habits. This study aimed to resolve this challenge using textile materials created by recycling fish-scale waste. Functional and comfortable masks manufactured without chemical additives to achieve multiple functions can increase the willingness to wear and be reused. Hence, product use can be prolonged, and the use of disposable masks can be curtailed. The product manufactured herein is biodegradable in nature, thus conforming to the green sustainable initiative.

Alterations in bile acids as metabolic signatures in the patients with human adenovirus type 7 infection.

Objectives: The changes in metabolism by human adenovirus (HAdV) infection was unclear. The potential mechanism of HAdV-7 causing acute respiratory tract infection was explored. Methods: Totally 35 patients with HAdV-7 infection, 32 asymptomatic cases with HAdV-7 and 14 healthy controls were enrolled from an outbreak of HAdV-7 in the army. The serum samples were analyzed by untargeted and targeted metabolomics. The effects of differential metabolites were verified on HAdV-7 replication in an A549 cell line. Results: The untargeted metabolomics analysis revealed more significant changes in the classes of sphingolipids, polyketides, glycerolipids, fatty acyls, and carboxylic acids and their derivatives in the patients with HAdV-7 than in healthy controls. Two key metabolic pathways of secondary and primary bile acid biosynthesis were noted from pathway enrichment analysis. Targeted metabolomics analysis showed that the levels of unconjugated bile acids in the patients were significantly lower, while the levels of glyco- and tauro- conjugated bile acids in patients and asymptomatic cases were higher than those in the healthy controls. The profiles of cytokines and peripheral lymphocyte subsets obviously varied at different levels of bile acids, with significant differences after HAdV-7 infection. A cell verification test demonstrated that the replication of HAdV-7 significantly reduced when GCDCA and TCA were added. Conclusion: Bile acids inhibited HAdV-7 replication in vitro. Alterations in bile acids was metabolic signatures of HAdV-7 infected subjects, and our results suggested bile acids might play protective roles against HAdV-7 infection.

Integrated time-series transcriptomic and metabolomic analyses reveal different inflammatory and adaptive immune responses contributing to host resistance to PRRSV.

Porcine reproductive and respiratory syndrome virus (PRRSV) is a highly contagious disease that affects the global pig industry. To understand mechanisms of susceptibility/resistance to PRRSV, this study profiled the time-serial white blood cells transcriptomic and serum metabolomic responses to PRRSV in piglets from a crossbred population of PRRSV-resistant Tongcheng pigs and PRRSV-susceptible Large White pigs. Gene set enrichment analysis (GSEA) illustrated that PRRSV infection up-regulated the expression levels of marker genes of dendritic cells, monocytes and neutrophils and inflammatory response, but down-regulated T cells, B cells and NK cells markers. CIBERSORT analysis confirmed the higher T cells proportion in resistant pigs during PRRSV infection. Resistant pigs showed a significantly higher level of T cell activation and lower expression levels of monocyte surface signatures post infection than susceptible pigs, corresponding to more severe suppression of T cell immunity and inflammatory response in susceptible pigs. Differentially expressed genes between resistant/susceptible pigs during the course of infection were significantly enriched in oxidative stress, innate immunity and humoral immunity, cell cycle, biotic stimulated cellular response, wounding response and behavior related pathways. Fourteen of these genes were distributed in 5 different QTL regions associated with PRRSV-related traits. Chemokine CXCL10 levels post PRRSV infection were differentially expressed between resistant pigs and susceptible pigs and can be a promising marker for susceptibility/resistance to PRRSV. Furthermore, the metabolomics dataset indicated differences in amino acid pathways and lipid metabolism between pre-infection/post-infection and resistant/susceptible pigs. The majority of metabolites levels were also down-regulated after PRRSV infection and were significantly positively correlated to the expression levels of marker genes in adaptive immune response. The integration of transcriptome and metabolome revealed concerted molecular events triggered by the infection, notably involving inflammatory response, adaptive immunity and G protein-coupled receptor downstream signaling. This study has increased our knowledge of the immune response differences induced by PRRSV infection and susceptibility differences at the transcriptomic and metabolomic levels, providing the basis for the PRRSV resistance mechanism and effective PRRS control.

XAF1 Protects Host against Emerging RNA Viruses by Stabilizing IRF1-Dependent Antiviral Immunity.

XIAP-associated factor 1 (XAF1) is an interferon (IFN)-stimulated gene (ISG) that enhances IFN-induced apoptosis. However, it is unexplored whether XAF1 is essential for the host fighting against invaded viruses. Here, we find that XAF1 is significantly upregulated in the host cells infected with emerging RNA viruses, including influenza, Zika virus (ZIKV), and SARS-CoV-2. IFN regulatory factor 1 (IRF1), a key transcription factor in immune cells, determines the induction of XAF1 during antiviral immunity. Ectopic expression of XAF1 protects host cells against various RNA viruses independent of apoptosis. Knockout of XAF1 attenuates host antiviral innate immunity in vitro and in vivo, which leads to more severe lung injuries and higher mortality in the influenza infection mouse model. XAF1 stabilizes IRF1 protein by antagonizing the CHIP-mediated degradation of IRF1, thus inducing more antiviral IRF1 target genes, including DDX58, DDX60, MX1, and OAS2. Our study has described a protective role of XAF1 in the host antiviral innate immunity against RNA viruses. We have also elucidated the molecular mechanism that IRF1 and XAF1 form a positive feedback loop to induce rapid and robust antiviral immunity. IMPORTANCE Rapid and robust induction of antiviral genes is essential for the host to clear the invaded viruses. In addition to the IRF3/7-IFN-I-STAT1 signaling axis, the XAF1-IRF1 positive feedback loop synergistically or independently drives the transcription of antiviral genes. Moreover, XAF1 is a sensitive and reliable gene that positively correlates with the viral infection, suggesting that XAF1 is a potential diagnostic marker for viral infectious diseases. In addition to the antitumor role, our study has shown that XAF1 is essential for antiviral immunity. XAF1 is not only a proapoptotic ISG, but it also stabilizes the master transcription factor IRF1 to induce antiviral genes. IRF1 directly binds to the IRF-Es of its target gene promoters and drives their transcriptions, which suggests a unique role of the XAF1-IRF1 loop in antiviral innate immunity, particularly in the host defect of IFN-I signaling such as invertebrates.

Emergent cesarean section in a preterm pregnant woman with severe COVID-19 pneumonia in Taiwan: A case report.

OBJECTIVE: The pandemic Coronavirus Disease 2019 (COVID-19) is a global public health crisis. Many maternity units worldwide are currently establishing the management protocols for these patients. CASE REPORT: We report the first critically ill pregnant woman with COVID-19-induced respiratory failure undergoing emergent caesarean delivery at 32 weeks of gestation, in the setting of a positive pressure operating room (OR) with negative pressure anteroom in Taiwan. CONCLUSION: Multidisciplinary planning and collaboration are necessary to achieve satisfactory clinical outcomes in pregnancies with critical COVID-19 pneumonia. The combinations of comprehensive evaluation, timely treatment as well as establishment of rigorous protocol and safe environment for the emergent delivery are important.

Exploring the mechanism of Platycodonis Radix-Licorice for prevention and treatment of COVID-19 based on network pharmacology and molecular docking

Objective: To investigate the possible mechanism of Platycodonis Radix-Licorice drug pair in the intervention of COVID-19 by using network pharmacology and molecular docking technique. Methods The database TCMSP was retrieved for the chemical constituents and targets of Platycodonis Radix-Licorice drug pair. Coronavirus disease targets were screened by the Gene Cards, OMIM,TTD, PharmGkb and DrugBank database. Cytoscape 3.7.2 software was used to construct the drug-component-target network. The PPI(protein-protein interaction) network was obtained by drug-disease intersection targets, and the core genes were found through CytoNCA plug-in. Meanwhile, GO(gene ontology) analysis and KEGG(Kyoto encyclopedia of genes and genomes) pathway analysis were performed by using Bioconductor database to predict the mechanism. AutoDock Tools 1.5.6 software was used to simulate the molecular docking of the main active ingredients with the novel coronavirus key binding site protein [SARS-CoV-2 main protease(severe acute respiratory syndrome coronavirus 2 main protease, Mpro) and ACE2(angiotensin converting enzyme 2)]. Results A total of 7 active ingredients of Platycodonis Radix,92 active ingredients of Licorice,2766 drug targets, and 674 disease targets were obtained, and 67 drug-disease common targets were excavated. The key targets involved RELA,STAT1,MAPK3,TP53,MAPK1,MAPK8,STAT3,MAPK14,IL1 B and TNF by the database STRING and CytoNCA plug-in.Go enrichment analysis showed that the main functions of Platycodonis Radix-Licorice drug pair on the intervention of COVID-19 were antioxidant reaction, cell respond to chemical stress, regulation of apoptotic signaling pathways, reaction to lipopolysaccharides and reaction to bacteria-derived molecules, etc.. KEGG pathways involved Coronavirus disease-COVID-19 pathway, IL-17 signaling pathway and so on, were mainly associated with immune response, inflammation-related pathways, inhibition of viral infection, and other inhibition of cancer. The molecular docking results showed that glepidotin A,quercetin, licochalcone a and luteolin had good binding ability with Mpro and ACE2. Conclusion Platycodonis Radix-Licorice drug pair act on SARS-CoV-2 through multiple components, multiple targets, and multiple channel combination. And the main active ingredients have a fine binding ability with Mpro and ACE2. The method can provide theoretical support for the possibility of traditional Chinese medicine(TCM) against COVID-19.

A Machine-Learning Analysis of the Impacts of the COVID-19 Pandemic on Small Business Owners and Implications for Canadian Government Policy Response.

This study applies a machine-learning technique to a dataset of 38,000 textual comments from Canadian small business owners on the impacts of coronavirus disease 2019 (COVID-19). Topic modelling revealed seven topics covering the short- and longer-term impacts of the pandemic, government relief programs and loan eligibility issues, mental health, and other impacts on business owners. The results emphasize the importance of policy response in aiding small business crisis management and offer implications for theory and policy. Moreover, the study provides an example of using a machine-learning-based automated content analysis in the fields of crisis management, small business, and public policy.

Cette étude applique une technique d'apprentissage automatique à un ensemble de données de 38 000 commentaires publiés par des propriétaires de petites entreprises canadiennes sur les impacts de la maladie à coronavirus 2019 (COVID-19). La modélisation thématique a révélé sept sujets couvrant les effets de la pandémie à court et à long terme, les programmes d'aide gouvernementaux, les questions d'admissibilité aux prêts, la santé mentale ainsi que d'autres retombées sur les propriétaires d'entreprise. Les résultats soulignent l'importance d'une intervention politique pour aider les petites entreprises à gérer la crise et offrent des implications pour la théorie et la politique. En outre, l'étude fournit un exemple d'utilisation d'une analyse automatisée de contenu basée sur l'apprentissage automatique dans les domaines de la gestion de crise, des petites entreprises et de la politique publique.

Medical and non-medical students' knowledge, attitude and willingness towards the COVID-19 vaccine in China: a cross-sectional online survey.

In the context of the novel Coronavirus outbreak and China's official policy of free vaccination against COVID-19 for all, medical students' attitudes and knowledge toward vaccines can influence public acceptance to some extent, however, the large base of non-medical students cannot be ignored. We aimed to investigate the knowledge, attitude, and willingness toward the COVID-19 vaccine among medical and non-medical students. Online surveys were completed by 652 medical students and 590 non-medical students to compare differences in knowledge and attitude of COVID-19 vaccine and vaccination willingness from three universities in the Zhejiang Province. The awareness rate of the vaccine among medical students (65.3%) was higher than that of non-medical students (53.6%). The approval rate of medical students for the safety and efficacy of the COVID-19 vaccine was higher than that of non-medical students. 81.8% of university students were willing to be vaccinated against COVID-19; Multiple stepwise regression analyses showed that lower class grades, rural students' origin, COVID-19 vaccine attitude and higher cognition level of health self-management influenced the acceptance of COVID-19 vaccination among medical students. However, urban origin, COVID-19 vaccine attitude were the factors hindering non-medical students' vaccination against COVID-19. The knowledge, attitude and willingness toward the COVID-19 vaccine on medical and non-medical students had different characteristics. Moreover, health self-management was associated with COVID-19 vaccination willingness. Staff involved in the university should pay more attention to the self-managementability of students, send out accurate and transparent information to enhance their cognitive level, further improving the students' willingness to receive the COVID-19 vaccine.

Harnessing Natural Products by a Pharmacophore-Oriented Semisynthesis Approach for the Discovery of Potential Anti-SARS-CoV-2 Agents.

Natural products possessing unique scaffolds may have antiviral activity but their complex structures hinder facile synthesis. A pharmacophore-oriented semisynthesis approach was applied to (-)-maoelactone A (1) and oridonin (2) for the discovery of anti-SARS-CoV-2 agents. The Wolff rearrangement/lactonization cascade (WRLC) reaction was developed to construct the unprecedented maoelactone-type scaffold during semisynthesis of 1. Further mechanistic study suggested a concerted mechanism for Wolff rearrangement and a water-assisted stepwise process for lactonization. The WRLC reaction then enabled the creation of a novel family by assembly of the maoelactone-type scaffold and the pharmacophore of 2, whereby one derivative inhibited SARS-CoV-2 replication in HPA EpiC cells with a low EC50 value (19±1 nM) and a high TI value (>1000), both values better than those of remdesivir.