Identification of Flavonoids from Scutellaria barbata D. Don as Inhibitors of HIV-1 and Cathepsin L Proteases and Their Structure-Activity Relationships.

Scutellaria barbata D. Don (SB, Chinese: Ban Zhi Lian), a well-known medicinal plant used in traditional Chinese medicine, is rich in flavonoids. It possesses antitumor, anti-inflammatory, and antiviral activities. In this study, we evaluated the inhibitory activities of SB extracts and its active components against HIV-1 protease (HIV-1 PR) and SARS-CoV2 viral cathepsin L protease (Cat L PR). UPLC/HRMS was used to identify and quantify the major active flavonoids in different SB extracts, and fluorescence resonance energy transfer (FRET) assays were used to determine HIV-1 PR and Cat L PR inhibitions and identify structure-activity relationships. Molecular docking was also performed, to explore the diversification in bonding patterns of the active flavonoids upon binding to the two PRs. Three SB extracts (SBW, SB30, and SB60) and nine flavonoids inhibited HIV-1 PR with an IC50 range from 0.006 to 0.83 mg/mL. Six of the flavonoids showed 10~37.6% inhibition of Cat L PR at a concentration of 0.1 mg/mL. The results showed that the introduction of the 4'-hydroxyl and 6-hydroxyl/methoxy groups was essential in the 5,6,7-trihydroxyl and 5,7,4'-trihydroxyl flavones, respectively, to enhance their dual anti-PR activities. Hence, the 5,6,7,4'-tetrahydroxyl flavone scutellarein (HIV-1 PR, IC50 = 0.068 mg/mL; Cat L PR, IC50 = 0.43 mg/mL) may serve as a lead compound to develop more effective dual protease inhibitors. The 5,7,3',4'-tetrahydroxyl flavone luteolin also showed a potent and selective inhibition of HIV-1 PR (IC50 = 0.039 mg/mL).

CCT: Lightweight compact convolutional transformer for lung disease CT image classification.

Computed tomography (CT) imaging results are an important criterion for the diagnosis of lung disease. CT images can clearly show the characteristics of lung lesions. Early and accurate detection of lung diseases helps clinicians to improve patient care effectively. Therefore, in this study, we used a lightweight compact convolutional transformer (CCT) to build a prediction model for lung disease classification using chest CT images. We added a position offset term and changed the attention mechanism of the transformer encoder to an axial attention mechanism module. As a result, the classification performance of the model was improved in terms of height and width. We show that the model effectively classifies COVID-19, community pneumonia, and normal conditions on the CC-CCII dataset. The proposed model outperforms other comparable models in the test set, achieving an accuracy of 98.5% and a sensitivity of 98.6%. The results show that our method achieves a larger field of perception on CT images, which positively affects the classification of CT images. Thus, the method can provide adequate assistance to clinicians.

The impact of COVID-19 on cultural industries: An empirical research based on stock market returns

The COVID-19 virus has challenged the development of the cultural industries seriously, so far, however few studies have used empirical methods to analyze the impact of the pandemic on the overall cultural industries. Based on the panel data of listed companies, this paper explores the impact of COVID-19 on cultural industries from the perspective of stock market returns. The empirical results show that the pandemic has a significant negative impact on the stock market returns of cultural industries, but the degrees of impact on various creative sub-sectors are significantly different. The findings also indicate that digitalization can effectively reduce the negative impact of COVID-19 on cultural companies, and the epidemic has bigger negative impacts on small and newly-established cultural companies. Moreover, we find that the stock market returns of cultural industries have an inverted U-shaped relationship with the daily growth in total confirmed cases and in total cases of death caused by COVID-19, indicating that the negative marginal impact of COVID-19 on the cultural industries increases firstly and then gradually decreases. Finally, implications for companies and governments are presented respectively based on the findings.

COVID-19 CT image segmentation method based on swin transformer.

Owing to its significant contagion and mutation, the new crown pneumonia epidemic has caused more than 520 million infections worldwide and has brought irreversible effects on the society. Computed tomography (CT) images can clearly demonstrate lung lesions of patients. This study used deep learning techniques to assist doctors in the screening and quantitative analysis of this disease. Consequently, this study will help to improve the diagnostic efficiency and reduce the risk of infection. In this study, we propose a new method to improve U-Net for lesion segmentation in the chest CT images of COVID-19 patients. 750 annotated chest CT images of 150 patients diagnosed with COVID-19 were selected to classify, identify, and segment the background area, lung area, ground glass opacity, and lung parenchyma. First, to address the problem of a loss of lesion detail during down sampling, we replaced part of the convolution operation with atrous convolution in the encoder structure of the segmentation network and employed convolutional block attention module (CBAM) to enhance the weighting of important feature information. Second, the Swin Transformer structure is introduced in the last layer of the encoder to reduce the number of parameters and improve network performance. We used the CC-CCII lesion segmentation dataset for training and validation of the model effectiveness. The results of ablation experiments demonstrate that this method achieved significant performance gain, in which the mean pixel accuracy is 87.62%, mean intersection over union is 80.6%, and dice similarity coefficient is 88.27%. Further, we verified that this model achieved superior performance in comparison to other models. Thus, the method proposed herein can better assist doctors in evaluating and analyzing the condition of COVID-19 patients.

Microwave resonant absorption of SARS-CoV-2 viruses.

Low power microwave can effectively deactivate influenza type A virus through the nonthermal structure-resonant energy transfer effect, at a frequency matching the confined-acoustic dipolar mode frequency of the virus. Currently, aerosol is considered the major route for SARS-CoV-2 transmission. For the potential microwave-based sterilization, the microwave-resonant frequency of SARS-CoV-2 must be unraveled. Here we report a microwave absorption spectroscopy study of the SARS-CoV-2 and HCoV-229E viruses through devising a coplanar-waveguide-based sensor. Noticeable microwave absorption can be observed, while we identified the resonant frequencies of the 1st and 2nd dipolar modes of SARS-CoV-2 virus as 4 and 7.5 GHz respectively. We further found that the resonant frequencies are invariant to the virus titer, and we also studied the microwave absorption of HCoV-229E in weak acidity medium to simulate the common pH value in fluid secretion. Our results suggest the possible radiation frequency for the recently proposed microwave sterilization devices to inactivate SARS-CoV-2 virus through a nonthermal mechanism so as to control the disease transmission in the post-pandemic era.

A theory of fiscal policy response to an epidemic.

Governments worldwide have issued massive amounts of debt to inject fiscal stimulus during the COVID-19 pandemic. This paper analyzes fiscal responses to an epidemic, in which interactions at work increase the risk of disease and mortality. Fiscal policies, which are designed to borrow against the future and provide transfers to individuals suffering economic hardship, can facilitate consumption smoothing while reduce hours worked and hence mitigate infections. We examine the optimal fiscal policy and characterize the condition under which fiscal policy improves social welfare. We then extend the model analyzing the static and dynamic pecuniary externalities under scale economies-the decrease in labor supply during the epidemic lowers the contemporaneous average wage rate while enhances the post-epidemic workforce health and productivity. We suggest that fiscal policy may not work effectively unless the government coordinates working time, and the optimal size of public debt is affected by production technology and disease severity and transmissibility.

Household Clusters of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection in Suzhou, China.

OBJECTIVES: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging virus causing substantial morbidity and mortality worldwide. We performed a cross-sectional investigation of SARS-CoV-2 clusters in Suzhou to determine the transmissibility of the virus among close contacts and to assess the demographic and clinical characteristics between index and secondary cases. METHODS: We review the clustered patients with SARS-CoV-2 infections in Suzhou between 22 January and 29 February 2020. The demographic and clinical characteristics were compared between index and secondary cases. We calculated the basic reproduction number (R 0) among close contacts with SLI model. RESULTS: By 22 February, 87 patients with SARS-CoV-2 infection were reported, including 50 sporadic and 37 clustered cases, who were generated from 13 clusters. On admission, 5 (20.8%) out of 24 secondary cases were asymptomatic. The male ratio of index cases was significantly higher than that of secondary cases. Additionally, the index cases were more likely to have fever and increased CRP levels than the secondary cases. The R 0 values of clusters displayed a significantly declining trend over time for all clusters. The relative risk of infection in blood-related contacts of cases versus unrelated contacts was 1.60 for SARS-CoV-2 (95% CI: 0.42-2.95). CONCLUSIONS: In conclusion, SARS-CoV-2 has great person-to-person transmission capability among close contacts. The secondary cases are more prone to have mild symptoms than index cases. There is no increased RR of secondary infection in blood relatives versus unrelated contacts. The high rate of asymptomatic SARS-CoV-2 infections highlights the urgent need to enhance active case finding strategy for early detection of infectious patients.

Regional Travel as an Alternative Form of Tourism during the COVID-19 Pandemic: Impacts of a Low-Risk Perception and Perceived Benefits.

Previous COVID-19 tourism research has not considered the positive impact of a low-risk perception and a perception of the benefits of regional travel on taking alternative tourism. This study attempts to fill the research gap and examine the positive effect of these perceptions on tourists' attitudes to regional travel and intentions to undertake regional travel during the COVID-19 pandemic. A survey of 278 respondents confirmed that the perceived benefit positively influences tourists' attitudes and travel intentions, but that a low-risk perception only positively affects their attitudes. This study contributes to tourism risk management research by introducing the concept of a low-risk perception as a positive factor. For tourism recovery, it finds that relaxation, value, and convenience are benefits to drive people to travel.

Determinants of Tourism Stocks During the COVID-19: Evidence From the Deep Learning Models.

This paper examines the determinants of tourism stock returns in China from October 25, 2018, to October 21, 2020, including the COVID-19 era. We propose four deep learning prediction models based on the Back Propagation Neural Network (BPNN): Quantum Swarm Intelligence Algorithms (QSIA), Quantum Step Fruit-Fly Optimization Algorithm (QSFOA), Quantum Particle Swarm Optimization Algorithm (QPSO) and Quantum Genetic Algorithm (QGA). Firstly, the rough dataset is used to reduce the dimension of the indices. Secondly, the number of neurons in the multilayer of BPNN is optimized by QSIA, QSFOA, QPSO, and QGA, respectively. Finally, the deep learning models are then used to establish prediction models with the best number of neurons under these three algorithms for the non-linear real stock returns. The results indicate that the QSFOA-BPNN model has the highest prediction accuracy among all models, and it is defined as the most effective feasible method. This evidence is robust to different sub-periods.

Nanoparticle composite TPNT1 is effective against SARS-CoV-2 and influenza viruses.

A metal nanoparticle composite, namely TPNT1, which contains Au-NP (1 ppm), Ag-NP (5 ppm), ZnO-NP (60 ppm) and ClO2 (42.5 ppm) in aqueous solution was prepared and characterized by spectroscopy, transmission electron microscopy, dynamic light scattering analysis and potentiometric titration. Based on the in vitro cell-based assay, TPNT1 inhibited six major clades of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with effective concentration within the range to be used as food additives. TPNT1 was shown to block viral entry by inhibiting the binding of SARS-CoV-2 spike proteins to the angiotensin-converting enzyme 2 (ACE2) receptor and to interfere with the syncytium formation. In addition, TPNT1 also effectively reduced the cytopathic effects induced by human (H1N1) and avian (H5N1) influenza viruses, including the wild-type and oseltamivir-resistant virus isolates. Together with previously demonstrated efficacy as antimicrobials, TPNT1 can block viral entry and inhibit or prevent viral infection to provide prophylactic effects against both SARS-CoV-2 and opportunistic infections.

Inhibition of SARS-CoV-2 by Highly Potent Broad-Spectrum Anti-Coronaviral Tylophorine-Based Derivatives.

Tylophorine-based compounds and natural cardiotonic steroids (cardenolides and bufadienolides) are two classes of transmissible gastroenteritis coronavirus inhibitors, targeting viral RNA and host cell factors, respectively. We tested both types of compounds against two types of coronaviruses, to compare and contrast their antiviral properties, and with view to their further therapeutic development. Examples of both types of compounds potently inhibited the replication of both feline infectious peritonitis virus and human coronavirus OC43 with EC50 values of up to 8 and 16 nM, respectively. Strikingly, the tylophorine-based compounds tested inhibited viral yields of HCoV-OC43 to a much greater extent (7-8 log magnitudes of p.f.u./ml) than the cardiotonic steroids (about 2-3 log magnitudes of p.f.u./ml), as determined by end point assays. Based on these results, three tylophorine-based compounds were further examined for their anti-viral activities on two other human coronaviruses, HCoV-229E and SARS-CoV-2. These three tylophorine-based compounds inhibited HCoV-229E with EC50 values of up to 6.5 nM, inhibited viral yields of HCoV-229E by 6-7 log magnitudes of p.f.u./ml, and were also found to inhibit SARS-CoV-2 with EC50 values of up to 2.5-14 nM. In conclusion, tylophorine-based compounds are potent, broad-spectrum inhibitors of coronaviruses including SARS-CoV-2, and could be used for the treatment of COVID-19.

Enhancement of the IFN-ß-induced host signature informs repurposed drugs for COVID-19.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a causative agent for the outbreak of coronavirus disease 2019 (COVID-19). This global pandemic is now calling for efforts to develop more effective COVID-19 therapies. Here we use a host-directed approach, which focuses on cellular responses to diverse small-molecule treatments, to identify potentially effective drugs for COVID-19. This framework looks at the ability of compounds to elicit a similar transcriptional response to IFN-ß, a type I interferon that fails to be induced at notable levels in response to SARS-CoV-2 infection. By correlating the perturbation profiles of ~3,000 small molecules with a high-quality signature of IFN-ß-responsive genes in primary normal human bronchial epithelial cells, our analysis revealed four candidate COVID-19 compounds, namely homoharringtonine, narciclasine, anisomycin, and emetine. We experimentally confirmed that the predicted compounds significantly inhibited SARS-CoV-2 replication in Vero E6 cells at nanomolar, relatively non-toxic concentrations, with half-maximal inhibitory concentrations of 165.7 nM, 16.5 nM, and 31.4 nM for homoharringtonine, narciclasine, and anisomycin, respectively. Together, our results corroborate a host-centric strategy to inform protective antiviral therapies for COVID-19.

Humanized COVID-19 decoy antibody effectively blocks viral entry and prevents SARS-CoV-2 infection.

To circumvent the devastating pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, a humanized decoy antibody (ACE2-Fc fusion protein) was designed to target the interaction between viral spike protein and its cellular receptor, angiotensin-converting enzyme 2 (ACE2). First, we demonstrated that ACE2-Fc could specifically abrogate virus replication by blocking the entry of SARS-CoV-2 spike-expressing pseudotyped virus into both ACE2-expressing lung cells and lung organoids. The impairment of viral entry was not affected by virus variants, since efficient inhibition was also observed in six SARS-CoV-2 clinical strains, including the D614G variants which have been shown to exhibit increased infectivity. The preservation of peptidase activity also enables ACE2-Fc to reduce the angiotensin II-mediated cytokine cascade. Furthermore, this Fc domain of ACE2-Fc was shown to activate NK cell degranulation after co-incubation with Spike-expressing H1975 cells. These promising characteristics potentiate the therapeutic prospects of ACE2-Fc as an effective treatment for COVID-19.

Cerebral Venous Thrombosis in Patients with COVID-19 Infection: a Case Series and Systematic Review.

BACKGROUND: There has been increasing reports associating the coronavirus disease 2019 (COVID-19) with thromboembolic phenomenon including ischemic strokes and venous thromboembolism. Cerebral venous thrombosis (CVT) is a rare neurovascular emergency that has been observed in some COVID-19 patients, yet much remains to be learnt of its underlying pathophysiology. OBJECTIVE: We present a case series of local patients with concomitant COVID-19 infection and CVT; and aim to perform a systematic review of known cases in the current literature. METHODS: We describe two patients with concomitant COVID-19 infection and CVT from a nationwide registry in Singapore. We then conducted a literature search in PubMed and Embase using a suitable keyword search strategy from 1st December 2019 to 11th June 2020. All studies reporting CVT in COVID-19 patients were included. RESULTS: Nine studies and 14 COVID-19 patients with CVT were studied. The median age was 43 years (IQR=36-58) and majority had no significant past medical conditions (60.0%). The time taken from onset of COVID-19 symptoms to CVT diagnosis was a median of 7 days (IQR=6-14). CVT was commonly seen in the transverse (75.0%) and sigmoid sinus (50.0%); 33.3% had involvement of the deep venous sinus system. A significant proportion of patients had raised D-dimer (75.0%) and CRP levels (50.0%). Two patients reported presence of antiphospholipid antibodies. Most patients received anticoagulation (91.7%) while overall mortality rate was 45.5%. CONCLUSIONS: The high mortality rate of CVT in COVID-19 infection warrants a high index of suspicion from physicians, and early treatment with anticoagulation should be initiated.

Furin Inhibitors Block SARS-CoV-2 Spike Protein Cleavage to Suppress Virus Production and Cytopathic Effects.

Development of specific antiviral agents is an urgent unmet need for SARS-coronavirus 2 (SARS-CoV-2) infection. This study focuses on host proteases that proteolytically activate the SARS-CoV-2 spike protein, critical for its fusion after binding to angiotensin-converting enzyme 2 (ACE2), as antiviral targets. We first validate cleavage at a putative furin substrate motif at SARS-CoV-2 spikes by expressing it in VeroE6 cells and find prominent syncytium formation. Cleavage and the syncytium are abolished by treatment with the furin inhibitors decanoyl-RVKR-chloromethylketone (CMK) and naphthofluorescein, but not by the transmembrane protease serine 2 (TMPRSS2) inhibitor camostat. CMK and naphthofluorescein show antiviral effects on SARS-CoV-2-infected cells by decreasing virus production and cytopathic effects. Further analysis reveals that, similar to camostat, CMK blocks virus entry, but it further suppresses cleavage of spikes and the syncytium. Naphthofluorescein acts primarily by suppressing viral RNA transcription. Therefore, furin inhibitors may be promising antiviral agents for prevention and treatment of SARS-CoV-2 infection.

Neurology of COVID-19 in Singapore.

PURPOSE: To describe the spectrum of COVID-19 neurology in Singapore. METHOD: We prospectively studied all microbiologically-confirmed COVID-19 patients in Singapore, who were referred for any neurological complaint within three months of COVID-19 onset. Neurological diagnoses and relationship to COVID-19 was made by consensus guided by contemporaneous literature, refined using recent case definitions. RESULTS: 47,572 patients (median age 34 years, 98% males) were diagnosed with COVID-19 in Singapore between 19 March to 19 July 2020. We identified 90 patients (median age 38, 98.9% males) with neurological disorders; 39 with varying certainty of relationship to COVID-19 categorised as: i) Central nervous system syndromes-4 acute disseminated encephalomyelitis (ADEM) and encephalitis, ii) Cerebrovascular disorders-19 acute ischaemic stroke and transient ischaemic attack (AIS/TIA), 4 cerebral venous thrombosis (CVT), 2 intracerebral haemorrhage, iii) Peripheral nervous system-7 mono/polyneuropathies, and a novel group, iv) Autonomic nervous system-4 limited dysautonomic syndromes. Fifty-one other patients had pre/co-existent neurological conditions unrelated to COVID-19. Encephalitis/ADEM is delayed, occurring in critical COVID-19, while CVT and dysautonomia occurred relatively early, and largely in mild infections. AIS/TIA was variable in onset, occurring in patients with differing COVID-19 severity; remarkably 63.2% were asymptomatic. CVT was more frequent than expected and occurred in mild/asymptomatic patients. There were no neurological complications in all 81 paediatric COVID-19 cases. CONCLUSION: COVID-19 neurology has a wide spectrum of dysimmune-thrombotic disorders. We encountered relatively few neurological complications, probably because our outbreak involved largely young men with mild/asymptomatic COVID-19. It is also widely perceived that the pandemic did not unduly affect the Singapore healthcare system.

Treatment of coronavirus disease 2019 in Shandong, China: a cost and affordability analysis.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is now a global public threat. Given the pandemic of COVID-19, the economic impact of COVID-19 is essential to add value to the policy-making process. We retrospectively conducted a cost and affordability analysis to determine the medical costs of COVID-19 patients in China, and also assess the factors affecting their costs. METHODS: This analysis was retrospectively conducted in Shandong Provincial Chest Hospital between 24 January and 16 March 2020. The total direct medical expenditures were analyzed by cost factors. We also assessed affordability by comparing the simulated out-of-pocket expenditure of COVID-19 cases relative to the per capita disposable income. Differences between groups were tested by student t test and Mann-Whitney test when appropriate. A multiple logistic regression model was built to determine the risk factors associated with high cost. RESULTS: A total of 70 COVID-19 patients were included in the analysis. The overall mean cost was USD 6827 per treated episode. The highest mean cost was observed in drug acquisition, accounting for 45.1% of the overall cost. Total mean cost was significantly higher in patients with pre-existing diseases compared to those without pre-existing diseases. Pre-existing diseases and the advanced disease severity were strongly associated with higher cost. Around USD 0.49 billion were expected for clinical manage of COVID-19 in China. Among rural households, the proportions of health insurance coverage should be increased to 70% for severe cases, and 80% for critically ill cases to avoid catastrophic health expenditure. CONCLUSIONS: Our data demonstrate that clinical management of COVID-19 patients incurs a great financial burden to national health insurance. The cost for drug acquisition is the major contributor to the medical cost, whereas the risk factors for higher cost are pre-existing diseases and severity of COVID-19. Improvement of insurance coverage will need to address the barriers of rural patients to avoid the occurrence of catastrophic health expenditure.