Porcine Epidemic Diarrhea Virus and Its nsp14 Suppress ER Stress Induced GRP78.

Porcine epidemic diarrhea virus (PEDV), a member of the α-coronavirus genus, can cause vomiting, diarrhea, and dehydration in piglets. Neonatal piglets infected with PEDV have a mortality rate as high as 100%. PEDV has caused substantial economic losses to the pork industry. Endoplasmic reticulum (ER) stress, which can alleviate the accumulation of unfolded or misfolded proteins in ER, involves in coronavirus infection. Previous studies have indicated that ER stress could inhibit the replication of human coronaviruses, and some human coronaviruses in turn could suppress ER stress-related factors. In this study, we demonstrated that PEDV could interact with ER stress. We determined that ER stress could potently inhibit the replication of GⅠ, GⅡ-a, and GⅡ-b PEDV strains. Moreover, we found that these PEDV strains can dampen the expression of the 78 kDa glucose-regulated protein (GRP78), an ER stress marker, while GRP78 overexpression showed antiviral activity against PEDV. Among different PEDV proteins, PEDV non-structural protein 14 (nsp14) was revealed to play an essential role in the inhibition of GRP78 by PEDV, and its guanine-N7-methyltransferase domain is necessary for this role. Further studies show that both PEDV and its nsp14 negatively regulated host translation, which could account for their inhibitory effects against GRP78. In addition, we found that PEDV nsp14 could inhibit the activity of GRP78 promotor, helping suppress GRP78 transcription. Our results reveal that PEDV possesses the potential to antagonize ER stress, and suggest that ER stress and PEDV nsp14 could be the targets for developing anti-PEDV drugs.

Discovery of novel SARS-CoV-2 3CL protease covalent inhibitors using deep learning-based screen.

SARS-CoV-2 3CL protease is one of the key targets for drug development against COVID-19. Most known SARS-CoV-2 3CL protease inhibitors act by covalently binding to the active site cysteine. Yet, computational screens against this enzyme were mainly focused on non-covalent inhibitor discovery. Here, we developed a deep learning-based stepwise strategy for selective covalent inhibitor screen. We used a deep learning framework that integrated a directed message passing neural network with a feed-forward neural network to construct two different classifiers for either covalent or non-covalent inhibition activity prediction. These two classifiers were trained on the covalent and non-covalent 3CL protease inhibitors dataset, respectively, which achieved high prediction accuracy. We then successively applied the covalent inhibitor model and the non-covalent inhibitor model to screen a chemical library containing compounds with covalent warheads of cysteine. We experimentally tested the inhibition activity of 32 top-ranking compounds and 12 of them were active, among which 6 showed IC50 values less than 12 µM and the strongest one inhibited SARS-CoV-2 3CL protease with an IC50 of 1.4 µM. Further investigation demonstrated that 5 of the 6 active compounds showed typical covalent inhibition behavior with time-dependent activity. These new covalent inhibitors provide novel scaffolds for developing highly active SARS-CoV-2 3CL covalent inhibitors.

One-Step Formation of Targeted Liposomes in a Versatile Microfluidic Mixing Device.

Targeted liposomes, as a promising carrier, have received tremendous attention in COVID-19 vaccines, molecular imaging, and cancer treatment, due to their enhanced cellular uptake and payload accumulation at target sites. However, the conventional methods for preparing targeted liposomes still suffer from limitations, including complex operation, time-consuming, and poor reproducibility. Herein, a facile and scalable strategy is developed for one-step construction of targeted liposomes using a versatile microfluidic mixing device (MMD). The engineered MMD provides an advanced synthesis platform for multifunctional liposome with high production rate and controllability. To validate the method, a programmed death-ligand 1 (PD-L1)-targeting aptamer modified indocyanine green (ICG)-liposome (Apt-ICG@Lip) is successfully constructed via the MMD. ICG and the PD-L1-targeting aptamer are used as model drug and targeting moiety, respectively. The Apt-ICG@Lip has high encapsulation efficiency (89.9 ± 1.4%) and small mean diameter (129.16 ± 5.48 nm). In vivo studies (PD-L1-expressing tumor models) show that Apt-ICG@Lip can realize PD-L1 targeted photoacoustic imaging, fluorescence imaging, and photothermal therapy. To verify the versatility of this approach, various targeted liposomes with different functions are further prepared and investigated. These experimental results demonstrate that this method is concise, efficient, and scalable to prepare multifunctional targeted liposomal nanoplatforms for molecular imaging and disease theranostics.

Long-term diet and risk of SARS -CoV-2 infection and Coronavirus Disease 2019 (COVID-19) severity.

BACKGROUND: The role of diet on COVID-19 is emerging. METHODS: We included 42,935 participants aged 55 to 99 years in two ongoing cohort studies, Nurses' Health Study II and Health Professionals Follow-up Study, who completed a series of COVID-19 surveys in 2020 and 2021. Using data from food frequency questionnaires prior to COVID-19, we assessed diet quality using the Alternative Healthy Eating Index (AHEI)-2010, the alternative Mediterranean Diet (AMED) score, an Empirical Dietary Index for Hyperinsulinemia (EDIH), and an Empirical Dietary Inflammatory Pattern (EDIP). We calculated multivariable adjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) for SARS-CoV-2 infection and severity of COVID-19 after controlling for demographic, medical, and lifestyle factors. RESULTS: Among 19,754 participants tested for SARS-CoV-2, 1,941 participants reported a positive result. Of these, 1,327 reported symptoms needing assistance and another 109 were hospitalized. Healthier diet, represented by higher AHEI-2010 and AMED scores and lower EDIH and EDIP scores, were associated with lower likelihood of SARS-CoV-2 infection (ORs Q (quartile) 4 vs. Q1 (95%CI) were 0.80 (0.69, 0.92) for AHEI-2010; 0.78 (0.67, 0.92) for AMED; 1.36 (1.16, 1.57) for EDIH; and 1.13 (0.99, 1.30) for EDIP; all p for trend ≤ 0.01). In the analysis of COVID-19 severity, participants with healthier diet had lower likelihood of severe infection and were less likely to be hospitalized due to COVID-19. However, associations were no longer significant after controlling for BMI and pre-existing medical conditions. CONCLUSION: Diet may be an important modifiable risk factor for SARS-CoV-2 infection, as well as for severity of COVID-19. This association is partially mediated by BMI and pre-existing medical conditions.

Impaired cell-cell communication and axon guidance because of pulmonary hypoperfusion during postnatal alveolar development.

BACKGROUND: Pulmonary hypoperfusion is common in children with congenital heart diseases (CHDs) or pulmonary hypertension (PH) and causes adult pulmonary dysplasia. Systematic reviews have shown that some children with CHDs or PH have mitigated clinical outcomes with COVID-19. Understanding the effects of pulmonary hypoperfusion on postnatal alveolar development may aid in the development of methods to improve the pulmonary function of children with CHDs or PH and improve their care during the COVID-19 pandemic, which is characterized by cytokine storm and persistent inflammation. METHODS AND RESULTS: We created a neonatal pulmonary hypoperfusion model through pulmonary artery banding (PAB) surgery at postnatal day 1 (P1). Alveolar dysplasia was confirmed by gross and histological examination at P21. Transcriptomic analysis of pulmonary tissues at P7(alveolar stage 2) and P14(alveolar stage 4) revealed that the postnatal alveolar development track had been changed due to pulmonary hypoperfusion. Under the condition of pulmonary hypoperfusion, the cell-cell communication and axon guidance, which both determine the final number of alveoli, were lost; instead, there was hyperactive cell cycle activity. The transcriptomic results were further confirmed by the examination of axon guidance and cell cycle markers. Because axon guidance controls inflammation and immune cell activation, the loss of axon guidance may explain the lack of severe COVID-19 cases among children with CHDs or PH accompanied by pulmonary hypoperfusion. CONCLUSIONS: This study suggested that promoting cell-cell communication or supplementation with guidance molecules may treat pulmonary hypoperfusion-induced alveolar dysplasia, and that COVID-19 is less likely to cause a cytokine storm in children with CHD or PH accompanied by pulmonary hypoperfusion.

Clinical characteristics and risk factors for a prolonged length of stay of patients with asymptomatic and mild COVID-19 during the wave of Omicron from Shanghai, China.

BACKGROUND: This study aims to investigate the clinical characteristics and the length of hospital stay (LOS), as well as risk factors for prolonged LOS in a cohort of asymptomatic and mild COVID-19 patients infected with the Omicron variant. METHODS: A total of 1166 COVID-19 patients discharged from the inpatient ward of the largest makeshift hospital (May 8-10, 2022) in Shanghai, China, were included. The demographics, medical history, and the lowest and admission cycle threshold (Ct) values of the RT-PCR tests for SARS-CoV-2 genes of the open reading frame 1ab (Ct-ORF) and the nucleocapsid protein (Ct-N) during hospitalization were recorded. Patients with LOS > 7 days, or LOS ≤ 7 days were included in the Prolonged group or the Control group, separately. The clinical characteristics and LOS of the participants in the two groups were described and compared. Multivariate Logistic and linear regression analyses were applied to explore the risk factors for prolonged LOS. The diagnostic efficacy of the lowest and admission Ct values for the Prolonged group was tested via the receiver operating characteristic (ROC) curve analysis. RESULTS: The median LOS was 6 days in the total study population. The age was older (45.52 ± 14.78 vs. 42.54 ± 15.30, P = 0.001), while both the lowest and admission Ct-ORF (27.68 ± 3.88 vs. 37.00 ± 4.62, P < 0.001; 30.48 ± 5.03 vs. 37.79 ± 3.81, P < 0.001) and Ct-N (25.79 ± 3.60 vs. 36.06 ± 5.39, P < 0.001; 28.71 ± 4.95 vs. 36.95 ± 4.59, P < 0.001) values were significantly lower in the Prolonged group. There were more mild cases in the Prolonged group (23.8% vs. 11.5%, P < 0.001). The symptom spectrum differed between the two groups. In multivariate analyses, age, disease category, and the lowest Ct-N values were shown to be associated with prolonged LOS. Besides, both the lowest and admission Ct-ORF (AUC = 0.911 and 0.873) and Ct-N (AUC = 0.912 and 0.874) showed robust diagnostic efficacy for prolonged LOS. CONCLUSIONS: Our study firstly reports the clinical characteristics and risk factors for prolonged LOS during the wave of the Omicron epidemic in Shanghai, China. These findings provide evidence for the early identification of asymptomatic and mild COVID-19 patients at a high risk of prolonged hospitalization who may require early intervention, and long-term monitoring and management.

Bioinformatics-based SARS-CoV-2 epitopes design and the impact of spike protein mutants on epitope humoral immunities.

BACKGROUND: Epitope selection is the key to peptide vaccines development. Bioinformatics tools can efficiently improve the screening of antigenic epitopes and help to choose the right ones. OBJECTIVE: To predict, synthesize and testify peptide epitopes at spike protein, assess the effect of mutations on epitope humoral immunity, thus provide clues for the design and development of epitope peptide vaccines against SARS-CoV-2. METHODS: Bioinformatics servers and immunological tools were used to identify the helper T lymphocyte, cytotoxic T lymphocyte, and linear B lymphocyte epitopes on the S protein of SARS-CoV-2. Physicochemical properties of candidate epitopes were analyzed using IEDB, VaxiJen, and AllerTOP online software. Three candidate epitopes were synthesized and their antigenic responses were evaluated by binding antibody detection. RESULTS: A total of 20 antigenic, non-toxic and non-allergenic candidate epitopes were identified from 1502 epitopes, including 6 helper T-cell epitopes, 13 cytotoxic T-cell epitopes, and 1 linear B cell epitope. After immunization with antigen containing candidate epitopes S206-221, S403-425, and S1157-1170 in rabbits, the binding titers of serum antibody to the corresponding peptide, S protein, receptor-binding domain protein were (415044, 2582, 209.3), (852819, 45238, 457767) and (357897, 10528, 13.79), respectively. The binding titers to Omicron S protein were 642, 12,878 and 7750, respectively, showing that N211L, DEL212 and K417N mutations cause the reduction of the antibody binding activity. CONCLUSIONS: Bioinformatic methods are effective in peptide epitopes design. Certain mutations of the Omicron would lead to the loss of antibody affinity to Omicron S protein.

TIMELESS is a key gene mediating thrombogenesis in COVID-19 and antiphospholipid syndrome.

Abnormal coagulation and increased risk of thrombosis are some of the symptoms associated with COVID-19 severity. Anti-phospholipid antibodies (aPLs) present in critically ill COVID-19 patients contribute to systemic thrombosis. The aim of this study was to identify key common genes to characterize genetic crosstalk between COVID-19 and antiphospholipid syndrome (APS) using bioinformatics analysis and explore novel mechanisms of immune-mediated thrombosis in critically ill COVID-19 patients. The transcriptome data of mononuclear cells from severe COVID-19 patients and APS patients were evaluated to obtain the common genes. The protein-protein interaction network and cytoHubba module analysis in Cytoscape software were used to find the associated hinge genes and hub genes. Among the common differentially expressed genes, TIMELESS depletion was identified only in patients with severe COVID-19 and not in patients with mild COVID-19, and it was validated with the GSE159678 dataset. Functional analyses using gene ontology terms and the Kyoto Encyclopedia of Genes and Genomes pathway suggested that TIMELESS might contribute to the production of antiphospholipid antibody and thrombosis in both COVID-19 and APS patients. The potential role of TIMELESS and autophagy genes in momonuclear cells were further investigated, and GSK3B was found to be associated with TIMELESS. Autophagy targeting agents have a therapeutic potential against COVID-19 and thrombogenesis in APS, which may be related to the role of autophagy genes in the modification of circadian clock proteins. Interference with TIMELESS and other genes associated with it to regulate autoantibody expression may be a potential strategy for immunotherapy against thrombogenesis in severe COVID-19 patients.

Discovery of novel SARS-CoV-2 3CL protease covalent inhibitors using deep learning-based screen

SARS-CoV-2 3CL protease is one of the key targets for drug development against COVID-19. Most known SARS-CoV-2 3CL protease inhibitors act by covalently binding to the active site cysteine. Yet, computational screens against this enzyme were mainly focused on non-covalent inhibitor discovery. Here, we developed a deep learning-based stepwise strategy for selective covalent inhibitor screen. We used a deep learning framework that integrated a directed message passing neural network with a feed-forward neural network to construct two different classifiers for either covalent or non-covalent inhibition activity prediction. These two classifiers were trained on the covalent and non-covalent 3CL protease inhibitors dataset, respectively, which achieved high prediction accuracy. We then successively applied the covalent inhibitor model and the non-covalent inhibitor model to screen a chemical library containing compounds with covalent warheads of cysteine. We experimentally tested the inhibition activity of 32 top-ranking compounds and 12 of them were active, among which 6 showed IC50 values less than 12 μM and the strongest one inhibited SARS-CoV-2 3CL protease with an IC50 of 1.4 μM. Further investigation demonstrated that 5 of the 6 active compounds showed typical covalent inhibition behavior with time-dependent activity. These new covalent inhibitors provide novel scaffolds for developing highly active SARS-CoV-2 3CL covalent inhibitors. Graphical Image 1

Bioinformatics-based SARS-CoV-2 epitopes design and the impact of Spike protein mutants on epitope humoral immunities

Graphical Background Epitope selection is the key to peptide vaccines development. Bioinformatics tools can efficiently improve the screening of antigenic epitopes and help to choose the right ones. Objective To predict, synthesize and testify peptide epitopes at spike protein, assess the effect of mutations on epitope humoral immunity, thus provide clues for the design and development of epitope peptide vaccines against SARS-CoV-2. Methods Bioinformatics servers and immunological tools were used to identify the helper T lymphocyte, cytotoxic T lymphocyte, and linear B lymphocyte epitopes on the S protein of SARS-CoV-2. Physicochemical properties of candidate epitopes were analyzed using IEDB, VaxiJen, and AllerTOP online software. Three candidate epitopes were synthesized and their antigenic responses were evaluated by binding antibody detection. Results A total of 20 antigenic, non-toxic and non-allergenic candidate epitopes were identified from 1502 epitopes, including 6 helper T-cell epitopes, 13 cytotoxic T-cell epitopes, and 1 linear B cell epitope. After immunization with antigen containing candidate epitopes S206-221, S403-425, and S1157-1170 in rabbits, the binding titers of serum antibody to the corresponding peptide, S protein, receptor-binding domain protein were (415044, 2582, 209.3), (852819, 45238, 457767) and (357897, 10528, 13.79), respectively. The binding titers to Omicron S protein were 642, 12878 and 7750, respectively, showing that N211L, DEL212 and K417N mutations cause the reduction of the antibody binding activity. Conclusions Bioinformatic methods are effective in peptide epitopes design. Certain mutations of the Omicron would lead to the loss of antibody affinity to Omicron S protein.

Discovery of 2-(furan-2-ylmethylene)hydrazine-1-carbothioamide derivatives as novel inhibitors of SARS-CoV-2 main protease.

The COVID-19 posed a serious threat to human life and health, and SARS-CoV-2 Mpro has been considered as an attractive drug target for the treatment of COVID-19. Herein, we report 2-(furan-2-ylmethylene)hydrazine-1-carbothioamide derivatives as novel inhibitors of SARS-CoV-2 Mpro developed by in-house library screening and biological evaluation. Similarity search led to the identification of compound F8-S43 with the enzymatic IC50 value of 10.76 µM. Further structure-based drug design and synthetic optimization uncovered compounds F8-B6 and F8-B22 as novel non-peptidomimetic inhibitors of Mpro with IC50 values of 1.57 µM and 1.55 µM, respectively. Moreover, enzymatic kinetic assay and mass spectrometry demonstrated that F8-B6 was a reversible covalent inhibitor of Mpro. Besides, F8-B6 showed low cytotoxicity with CC50 values of more than 100 µM in Vero and MDCK cells. Overall, these novel SARS-CoV-2 Mpro non-peptidomimetic inhibitors provide a useful starting point for further structural optimization.

Effect of elevated fasting blood glucose level on the 1-year mortality and sequelae in hospitalized COVID-19 patients: A bidirectional cohort study.

To observe the predictive effect of fasting blood glucose (FBG) level on the prognosis, clinical sequelae, and pulmonary absorption in hospitalized coronavirus disease 2019 (COVID-19) patients with and without a history of diabetes, respectively, and to evaluate the correlation between the dynamic changes of FBG and poor prognosis. In this bidirectional cohort study, we enrolled 2545 hospitalized COVID-19 patients (439 diabetics and 2106 without a diabetic history) and followed up for 1 year. The patients were divided according to the level of admission FBG. The dynamic changes of FBG were compared between the survival and the death cases. The prediction effect of FBG on 1-year mortality and sequelae was analyzed. The 1-year all cause mortality rate and in-hospital mortality rate of COVID-19 patients were J-curve correlated with FBG (p < 0.001 for both in the nondiabetic history group, p = 0.004 and p = 0.01 in the diabetic history group). FBG ≥ 7.0 mmol/L had a higher risk of developing sequelae (p = 0.025) and have slower recovery of abnormal lung scans (p < 0.001) in patients who denied a history of diabetes. Multivariable Cox regression analysis showed that FBG ≥ 7.0 mmol/L was an independent risk factor for the mortality of COVID-19 regardless of the presence or deny a history of diabetes (hazard atio [HR] = 10.63, 95% confidence interval [CI]: 7.15-15.83, p < 0.001; HR = 3.9, 95% CI: 1.56-9.77, p = 0.004, respectively). Our study shows that FBG ≥ 7.0 mmol/L can be a predictive factor of 1-year all-cause mortality in COVID-19 patients, independent of diabetes history. FBG ≥ 7.0 mmol/L has an advantage in predicting the severity, clinical sequelae, and pulmonary absorption in COVID-19 patients without a history of diabetes. Early detection, timely treatment, and strict control of blood glucose when finding hyperglycemia in COVID-19 patients (with or without diabetes) are critical for their prognosis.

Associations between predicted vitamin D status, vitamin D intake, and risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) severity.

BACKGROUND: Vitamin D may have a role in immune responses to viral infections. However, data on the association between vitamin D and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) severity have been limited and inconsistent. OBJECTIVE: We examined the associations of predicted vitamin D status and intake with risk of SARS-CoV-2 infection and COVID-19 severity. METHODS: We used data from periodic surveys (May 2020 to March 2021) within the Nurses' Health Study II. Among 39,315 participants, 1768 reported a positive test for SARS-CoV-2 infection. Usual vitamin D intake from foods and supplements were measured using a semiquantitative, pre-pandemic food-frequency questionnaire in 2015. Predicted 25-hydroxyvitamin D [25(OH)D] concentration were calculated based on a previously validated model including dietary and supplementary vitamin D intake, UV-B, and other behavioral predictors of vitamin D status. RESULTS: Higher predicted 25(OH)D concentrations, but not vitamin D intake, were associated with a lower risk of SARS-CoV-2 infection. Comparing participants in the highest quintile of predicted 25(OH)D concentrations with the lowest, the multivariable-adjusted OR was 0.76 (95% CI: 0.58, 0.99; P-trend = 0.04). Participants in the highest quartile of UV-B (OR: 0.76; 95% CI: 0.66, 0.87; P-trend = 0.002) and UV-A (OR: 0.76; 95% CI: 0.66, 0.88; P-trend < 0.001) also had a lower risk of SARS-CoV-2 infection compared with the lowest. High intake of vitamin D from supplements (≥400 IU/d) was associated with a lower risk of hospitalization (OR: 0.51; 95% CI: 0.29, 0.91; P-trend = 0.04). CONCLUSIONS: Our study provides suggestive evidence on the association between higher predicted circulating 25(OH)D concentrations and a lower risk of SARS-CoV-2 infection. Greater intake of vitamin D supplements was associated with a lower risk of hospitalization. Our data also support an association between exposure to UV-B or UV-A, independently of vitamin D and SARS-CoV-2 infection, so results for predicted 25(OH)D need to be interpreted cautiously.

AT1 Receptors: Their Actions from Hypertension to Cognitive Impairment.

Hypertension is one of the most prevalent cardiovascular disorders worldwide, affecting 1.13 billion people, or 14% of the global population. Hypertension is the single biggest risk factor for cerebrovascular dysfunction. According to the American Heart Association, high blood pressure (BP), especially in middle-aged individuals (~ 40 to 60 years old), is associated with an increased risk of dementia, later in life. Alzheimer's disease and cerebrovascular disease are the two leading causes of dementia, accounting for around 80% of the total cases and usually combining mixed pathologies from both. Little is known regarding how hypertension affects cognitive function, so the impact of its treatment on cognitive impairment has been difficult to assess. The brain renin-angiotensin system (RAS) is essential for BP regulation and overactivity of this system has been established to precede the development and maintenance of hypertension. Angiotensin II (Ang-II), the main peptide within this system, induces vasoconstriction and impairs neuro-vascular coupling by acting on brain Ang-II type 1 receptors (AT1R). In this review, we systemically analyzed the association between RAS and biological mechanisms of cognitive impairment, from the perspective of AT1R located in the central nervous system. Additionally, the possible contribution of brain AT1R to global cognition decline in COVID-19 cases will be discussed as well.

A Joint Optimization Model considering the Product User's Risk Preference for Supply System Disruption

Logistics distribution is the terminal link that connects the manufacturer and product user and determines the efficiency of the manufacturer’s service. Therefore, the disruption risk of the joint system is an essential factor affecting the product user experience. In this paper, while considering the product user’s supply disruption risk preference (PUSDRP), a biobjective integer nonlinear programming (INLP) model with subjective cost-utility is proposed to solve the manufacturer’s combined location routing inventory problem (CLRIP). According to the user’s time satisfaction requirement, a routing change selection framework (RCSF) is designed based on the bounded rational behavior of the user. Additionally, the Lagrange Relaxation and Modified Genetic Algorithm (LR-MGA) is proposed. The LR method relaxes the model, and the MGA finds a compromise solution. The experimental results show that the biobjective cost-utility model proposed in this paper is effective and efficient. The RCSF based on user behavior is superior to the traditional expected utility theory model. The compromise solution provides a better solution for the manufacturer order allocation delivery combinatorial optimization problem. The compromise solution not only reduces the manufacturer’s total operating cost but also improves the user's subjective utility. To improve the stability of cooperation between manufacturers and users, the behavior decision-making method urges manufacturers to consider product users’ supply disruption risk preferences (PUSDRPs) in attempting to optimize economic benefits for the long term. This paper uses behavior decision-making methods to expand the ideas of the CLRIP joint system.

A transferable deep learning approach to fast screen potential antiviral drugs against SARS-CoV-2.

The COVID-19 pandemic calls for rapid development of effective treatments. Although various drug repurpose approaches have been used to screen the FDA-approved drugs and drug candidates in clinical phases against SARS-CoV-2, the coronavirus that causes this disease, no magic bullets have been found until now. In this study, we used directed message passing neural network to first build a broad-spectrum anti-beta-coronavirus compound prediction model, which gave satisfactory predictions on newly reported active compounds against SARS-CoV-2. Then, we applied transfer learning to fine-tune the model with the recently reported anti-SARS-CoV-2 compounds and derived a SARS-CoV-2 specific prediction model COVIDVS-3. We used COVIDVS-3 to screen a large compound library with 4.9 million drug-like molecules from ZINC15 database and recommended a list of potential anti-SARS-CoV-2 compounds for further experimental testing. As a proof-of-concept, we experimentally tested seven high-scored compounds that also demonstrated good binding strength in docking studies against the 3C-like protease of SARS-CoV-2 and found one novel compound that can inhibit the enzyme. Our model is highly efficient and can be used to screen large compound databases with millions or more compounds to accelerate the drug discovery process for the treatment of COVID-19.

Extracorporeal membrane oxygenation for coronavirus disease 2019-associated acute respiratory distress syndrome: Report of two cases and review of the literature.

BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2, is a worldwide pandemic. Some COVID-19 patients develop severe acute respiratory distress syndrome and progress to respiratory failure. In such cases, extracorporeal membrane oxygenation (ECMO) treatment is a necessary life-saving procedure. CASE SUMMARY: Two special COVID-19 cases-one full-term pregnant woman and one elderly (72-year-old) man-were treated by veno-venous (VV)-ECMO in the Second People's Hospital of Zhongshan, Zhongshan City, Guangdong Province, China. Both patients had developed refractory hypoxemia shortly after hospital admission, despite conventional support, and were therefore managed by VV-ECMO. Although both experienced multiple ECMO-related complications on top of the COVID-19 disease, their conditions improved gradually. Both patients were weaned successfully from the ECMO therapy. At the time of writing of this report, the woman has recovered completely and been discharged from hospital to home; the man remains on mechanical ventilation, due to respiratory muscle weakness and suspected lung fibrosis. As ECMO itself is associated with various complications, it is very important to understand and treat these complications to achieve optimal outcome. CONCLUSION: VV-ECMO can provide sufficient gas exchange for COVID-19 patients with acute respiratory distress syndrome. However, it is crucial to understand and treat ECMO-related complications.

Mycobacterium vaccae Nebulization in the Treatment of COVID-19: A Randomized, Double-Blind, Placebo-Controlled Trial.

Background: Severe acute respiratory syndrome coronavirus 2 infection is associated with strong infectiousness and has no effective therapy. We aimed to explore the efficacy and safety of Mycobacterium vaccae nebulization in the treatment of Coronavirus Disease 2019 (COVID-19). Methods: In this randomized, double-blind, placebo-controlled clinical trial, we included 31 adult patients with moderate COVID-19 who were admitted to the Fourth People's Hospital of Nanning (Nanning, China) between January 22, 2020 and February 17, 2020. Patients were randomly divided into two groups: group A (standard care group) and group B (M. vaccae in combination with standard care group). The primary outcome was the time interval from admission to viral RNA negative conversion (oropharyngeal swabs were used in this study). Secondary outcomes included chest computed tomography (CT), mortality, length of hospital stay, complications during treatment, and so on. Patients were followed up to 4 weeks after discharge (reexamination of viral RNA, chest CT, etc.). Results: Nucleic acid test negative conversion time in group B was shorter than that in group A (2.9 days [2.7-8.7] vs. 6.8 days [3.3-13.8]; p = 0.045). No death and no conversion to severe or critical cases were observed in both groups. Two weeks after discharge, neither "relapse" nor "return to positive" cases were found. Four weeks after discharge, it was found that there was no case of " relapse " or "return to positive" in group B, and 1 patient in group A showed "return to positive", but there was no clinical manifestation and imaging progression. No adverse reactions related to M. vaccae were found during observation period. Conclusion:M. vaccae treatment might shorten the time interval from admission to viral RNA negative conversion, which might be beneficial to the prevention and treatment of COVID-19. Clinical Trial Registration: ChiCTR2000030016.

Scutellaria baicalensis extract and baicalein inhibit replication of SARS-CoV-2 and its 3C-like protease in vitro.

COVID-19 has become a global pandemic and there is an urgent call for developing drugs against the virus (SARS-CoV-2). The 3C-like protease (3CLpro) of SARS-CoV-2 is a preferred target for broad spectrum anti-coronavirus drug discovery. We studied the anti-SARS-CoV-2 activity of S. baicalensis and its ingredients. We found that the ethanol extract of S. baicalensis and its major component, baicalein, inhibit SARS-CoV-2 3CLpro activity in vitro with IC50's of 8.52 µg/ml and 0.39 µM, respectively. Both of them inhibit the replication of SARS-CoV-2 in Vero cells with EC50's of 0.74 µg/ml and 2.9 µM, respectively. While baicalein is mainly active at the viral post-entry stage, the ethanol extract also inhibits viral entry. We further identified four baicalein analogues from other herbs that inhibit SARS-CoV-2 3CLpro activity at µM concentration. All the active compounds and the S. baicalensis extract also inhibit the SARS-CoV 3CLpro, demonstrating their potential as broad-spectrum anti-coronavirus drugs.