Oral Liushen pill for patients with COVID-19: A prospective randomized controlled trial.

We examined the efficacy and safety of Liushen pill combined with basic treatment for patients with COVID-19. In total, 181 patients hospitalized with COVID-19, classified as asymptomatic mild type, were randomly divided into the experimental (n = 91) and control (n = 90) groups and were administered placebo (Maizao decoction) and Maizao decoction and Liushen pill, in addition to standard care, respectively. The negative conversion rate of nucleic acid (Day 7), hospital discharge rate (Days 8, 10, and 14), symptom disappearance rate (Days 3, 5, and 7), inflammatory cytokine levels, and adverse events were compared between the groups. The negative viral conversion rate was significantly higher in the experimental than in the control group (48.35 vs. 31.11%, p < 0.05). Subgroup analysis showed a similar significant trend when the Ct value was ≤30 at baseline. After 10 days, the hospital discharge rate was significantly higher in the experimental than in the control group (69.23 vs. 53.33%, p < 0.05). After 3-day medication, the headache symptoms significantly disappeared in the experimental (88.57%) compared to the control group (63.33%) (p < 0.05). After 5 days, the symptom disappearance rates of headache and cough were significantly higher in the experimental (97.14%) than in the control group (97.14 vs. 80.00, p < 0.05; 82.65 vs. 58.93%, p < 0.01, respectively). Posttreatment, the procalcitonin level was significantly lower in the experimental than in the control group (0.09 ± 0.00 vs. 0.14 ± 0.05 ng/L; p < 0.05). There were no significant between-group differences in clinical safety test indices. Early intervention with Liushen pill improved cough and headache and increased negative viral conversion and discharge rate.

Ligand/Receptor-mediated Cell Communication Alteration Causes the Lung Inflammation Microenvironment and the Redistribution of Inter-tissue Immune Cells in COVID-19 Patients (preprint)

How SARS-CoV-2 causes disturbances of the lung microenvironment and systemic immune response remains a mystery. Here, we first analyze detailedly paired single-cell transcriptome data of the lungs, blood and bone marrow of two patients who died of COVID-19. Second, our results demonstrate that SARS-CoV-2 infection significantly increases the cellular communication frequency between AT1/AT2 cells and highly inflammatory myeloid cells, and induces the pulmonary inflammation microenvironment, and drives the disorder of fibroblasts, club and ciliated cells, thereby causing the increase of pulmonary fibrosis and mucus accumulation. Third, our works reveal that the increase of the lung T cell infiltration is mainly recruited by myeloid cells through certain ligands/receptors (ANXA1/FPR1, C5AR1/RPS19 and CCL5/CCR1), rather than AT1/AT2. Fourth, we find that some ligands and receptors such as ANXA1/FPR1, CD74/COPA, CXCLs/CXCRs, ALOX5/ALOX5AP, CCL5/CCR1, are significantly activated and shared among patients’ lungs, blood and bone marrow, implying that dysregulated ligands and receptors may cause the migration, redistribution and the inflammatory storm of immune cells in different tissues. Overall, our study reveals a latent mechanism by which the disorders of ligands and receptors caused by SARS-CoV-2 infection drive cell communication alteration, the pulmonary inflammatory microenvironment and systemic immune responses across tissues in COVID-19 patients.

Chemical and chemoenzymatic stereoselective synthesis of β-nucleosides and their analogues

β-Nucleosides are fundamental building blocks of biological systems and are widely used as therapeutic agents for the treatment of cancer and viral infections, among others. In the last two years, nucleoside analogues have been investigated with renewed urgency in the search for agents that are effective against SARS-CoV-2, the cause of the ongoing global pandemic of COVID-19. This has resulted in an explosion of activities in the field of β-nucleoside synthesis. This review summarizes the historical perspective and the recent advances in the stereoselective synthesis of β-nucleosides and their analogues. The synthetic strategies to obtain β-nucleosides can be divided into three categories: (1) N-glycosylation;(2) intramolecular sugar ring formation;and (3) enzymatic transglycosylation.

The effect of glucocorticoids on mortality in severe COVID-19 patients: Evidence from 13 studies involving 6612 cases.

BACKGROUND: Since the start of the coronavirus disease 2019 (COVID-19) pandemic, there is an urgent need for effective therapies for patients with COVID-19. In this study, we aimed to assess the therapeutic efficacy of glucocorticoids in severe COVID-19. METHODS: A systematic literature search was performed across PubMed, Web of Science, EMBASE, and the Cochrane Library (up to June 26, 2021). The literature investigated the outcomes of interest were mortality and invasive mechanical ventilation. RESULTS: The search identified 13 studies with 6612 confirmed severe COVID-19 patients. Our meta-analysis found that using glucocorticoids could significantly decrease COVID-19 mortality (hazard ratio (HR) 0.60, 95% confidence interval (CI) 0.45-0.79, P < .001), relative to non-use of glucocorticoids. Meanwhile, using glucocorticoids also could significantly decrease the risk of progression to invasive mechanical ventilation for severe COVID-19 patients (HR = 0.69, 95% CI 0.58-0.83, P < .001). Compared with using dexamethasone (HR = 0.68, 95% CI 0.50-0.92, P = .012), methylprednisolone use had a better therapeutic effect for reducing the mortality of patients (HR = 0.35, 95% CI 0.19-0.64, P = .001). CONCLUSION: The result of this meta-analysis showed that using glucocorticoids could reduce mortality and risk of progression to invasive mechanical ventilation in severe COVID-19 patients.

Risk assessment of airborne COVID-19 exposure in social settings.

The COVID-19 pandemic has led to many countries oscillating between various states of lock-down as they seek to balance keeping the economy and essential services running and minimizing the risk of further transmission. Decisions are made about which activities to keep open across a range of social settings and venues guided only by ad hoc heuristics regarding social distancing and personal hygiene. Hence, we propose the dual use of computational fluid dynamic simulations and surrogate aerosol measurements for location-specific assessment of risk of infection across different real-world settings. We propose a 3-tiered risk assessment scheme to facilitate classification of scenarios into risk levels based on simulations and experiments. Threshold values of <54 and >840 viral copies and <5% and >40% of original aerosol concentration are chosen to stratify low, medium, and high risk. This can help prioritize allowable activities and guide implementation of phased lockdowns or re-opening. Using a public bus in Singapore as a case study, we evaluate the relative risk of infection across scenarios such as different activities and passenger positions and demonstrate the effectiveness of our risk assessment methodology as a simple and easily interpretable framework. For example, this study revealed that the bus's air-conditioning greatly influences dispersion and increases the risk of certain seats and that talking can result in similar relative risk to coughing for passengers around an infected person. Both numerical and experimental approaches show similar relative risk levels with a Spearman's correlation coefficient of 0.74 despite differing observables, demonstrating applicability of this risk assessment methodology to other scenarios.

COVID-19 risk assessment for the Tokyo Olympic Games (preprint)

Abstract Objectives To explore effective prevention and control measures for Coronavirus Disease 2019 (COVID-19) in large international events through simulations of different interventions according to risk assessment. Methods We used random model to calculate the number of initial infected patients. And Poisson distribution was used to determine the number of initial infected patients based on the number of countries involved. Further, to simulate the COVID-19 transmission, the susceptible-exposed-symptomatic-asymptomatic-recovered-hospitalized (SEIARH) model was established based on susceptible-exposed-infectious-recovered (SEIR) mathematical model of epidemic diseases. According to risk assessment indicators produced by different scenarios of the simulated interventions, the risk of COVID-19 transmission in Tokyo Olympic Games was assessed. Results The large-scale vaccination will effectively control the spread of COVID-19. If the effective rate of vaccine is 100%, and the vaccination rate of athletes reaches 80%, an epidemic prevention barrier can be established. Conclusions The current COVID-19 prevention measures proposed by the Japan Olympic Committee were needed to be enhanced. For the vaccination intervention had the best control effect, a mass vaccination serves was an effective way to control COVID-19. Keywords: COVID-19; SEIARH model; interventions; Tokyo Olympic Games; risk assessment

No Statistically Apparent Difference in Antiviral Effectiveness Observed Among Ribavirin Plus Interferon-Alpha, Lopinavir/Ritonavir Plus Interferon-Alpha, and Ribavirin Plus Lopinavir/Ritonavir Plus Interferon-Alpha in Patients With Mild to Moderate Coronavirus Disease 2019: Results of a Randomized, Open-Labeled Prospective Study.

BACKGROUND: Currently, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread globally, causing an unprecedented pandemic. However, there is no specific antiviral therapy for coronavirus disease 2019 (COVID-19). We conducted a clinical trial to compare the effectiveness of three antiviral treatment regimens in patients with mild to moderate COVID-19. METHODS: This was a single-center, randomized, open-labeled, prospective clinical trial. Eligible patients with mild to moderate COVID-19 were randomized into three groups: ribavirin (RBV) plus interferon-α (IFN-α), lopinavir/ritonavir (LPV/r) plus IFN-α, and RBV plus LPV/r plus IFN-α at a 1:1:1 ratio. Each patient was invited to participate in a 28-d follow-up after initiation of an antiviral regimen. The outcomes include the difference in median interval to SARS-CoV-2 nucleic acid negativity, the proportion of patients with SARS-CoV-2 nucleic acid negativity at day 14, the mortality at day 28, the proportion of patients re-classified as severe cases, and adverse events during the study period. RESULTS: In total, we enrolled 101 patients in this study. Baseline clinical and laboratory characteristics of patients were comparable among the three groups. In the analysis of intention-to-treat data, the median interval from baseline to SARS-CoV-2 nucleic acid negativity was 12 d in the LPV/r+IFN-α-treated group, as compared with 13 and 15 d in the RBV+IFN-α-treated group and in the RBV+LPV/r+ IFN-α-treated group, respectively (p=0.23). The proportion of patients with SARS-CoV-2 nucleic acid negativity in the LPV/r+IFN-α-treated group (61.1%) was higher than the RBV+ IFN-α-treated group (51.5%) and the RBV+LPV/r+IFN-α-treated group (46.9%) at day 14; however, the difference between these groups was calculated to be statistically insignificant. The RBV+LPV/r+IFN-α-treated group developed a significantly higher incidence of gastrointestinal adverse events than the LPV/r+ IFN-α-treated group and the RBV+ IFN-α-treated group. CONCLUSIONS: Our results indicate that there are no significant differences among the three regimens in terms of antiviral effectiveness in patients with mild to moderate COVID-19. Furthermore, the combination of RBV and LPV/r is associated with a significant increase in gastrointestinal adverse events, suggesting that RBV and LPV/r should not be co-administered to COVID-19 patients simultaneously. CLINICAL TRIAL REGISTRATION: www.ClinicalTrials.gov, ID: ChiCTR2000029387. Registered on January 28, 2019.

The Efficacy of Plant-Based Ionizers in Removing Aerosol for COVID-19 Mitigation.

Small-sized droplets/aerosol transmission is one of the factors responsible for the spread of COVID-19, in addition to large droplets and surface contamination (fomites). While large droplets and surface contamination can be relatively easier to deal with (i.e., using mask and proper hygiene measures), aerosol presents a different challenge due to their ability to remain airborne for a long time. This calls for mitigation solutions that can rapidly eliminate the airborne aerosol. Pre-COVID-19, air ionizers have been touted as effective tools to eliminate small particulates. In this work, we sought to evaluate the efficacy of a novel plant-based ionizer in eliminating aerosol. It was found that factors such as the ion concentration, humidity, and ventilation can drastically affect the efficacy of aerosol removal. The aerosol removal rate was quantified in terms of ACH (air changes per hour) and CADR- (clean air delivery rate-) equivalent unit, with ACH as high as 12 and CADR as high as 141 ft3/minute being achieved by a plant-based ionizer in a small isolated room. This work provides an important and timely guidance on the effective deployment of ionizers in minimizing the risk of COVID-19 spread via airborne aerosol, especially in a poorly-ventilated environment.

Blood molecular markers associated with COVID-19 immunopathology and multi-organ damage.

COVID-19 is characterized by dysregulated immune responses, metabolic dysfunction and adverse effects on the function of multiple organs. To understand host responses to COVID-19 pathophysiology, we combined transcriptomics, proteomics, and metabolomics to identify molecular markers in peripheral blood and plasma samples of 66 COVID-19-infected patients experiencing a range of disease severities and 17 healthy controls. A large number of expressed genes, proteins, metabolites, and extracellular RNAs (exRNAs) exhibit strong associations with various clinical parameters. Multiple sets of tissue-specific proteins and exRNAs varied significantly in both mild and severe patients suggesting a potential impact on tissue function. Chronic activation of neutrophils, IFN-I signaling, and a high level of inflammatory cytokines were observed in patients with severe disease progression. In contrast, COVID-19-infected patients experiencing milder disease symptoms showed robust T-cell responses. Finally, we identified genes, proteins, and exRNAs as potential biomarkers that might assist in predicting the prognosis of SARS-CoV-2 infection. These data refine our understanding of the pathophysiology and clinical progress of COVID-19.

[Thoughts and suggestions on arrangement, analysis and summary of medical data during COVID-19 epidemic].

The analysis and utilization of clinical scientific research data is an effective means to promote the progress of diagnosis and treatment, and a key step in the development of medical sciences. During the epidemic of coronavirus disease 2019(COVID-19), how to transform the limited diagnostic data into clinical research resources has attracted much attention. Based on the low efficiency of data collection and extraction, the inconsistency of data analysis, the irregularity of data report and the high timeliness of data update during the epidemic, this paper briefly analyzed the background and reasons of data application under the current situation, and then discusses the problems and feasible solutions of clinical data applications under the epidemic situation and, more importantly, for future medical clinical research methods. We put forward several methodological suggestions: ① gradually improve the medical big data model and establish the national medical health data center; ② improve the scientific research literacy of medical staff and popularize the basic skills and knowledge of GCP; ③ promote a scientific, networked and shared data collection and management mode; ④ use the mixed research method and collective analysis to improve the efficiency of clinical data analysis; ⑤ pay attention to narration of the medical feelings and emphasize the humanistic data of clinical medicine. It is expected to promote the standardized and reasonable use of clinical scientific research data, the rigorous integration of expert opinions, and ultimately the development of big data for national health care.