ABSTRACT
Coronavirus disease 2019 (COVID-19) remains an uncontained, worldwide pandemic. While battling the disease in China, the Chinese government has actively promoted the use of traditional Chinese medicine, and many studies have been conducted to determine the efficacy of traditional Chinese medicine for treating COVID-19. The present review discusses the effectiveness and safety of traditional Chinese medicine in curing COVID-19 and provides clinical evidence from all confirmed cases in China. Applications of traditional Chinese medicine and specific recipes for treating other viral infections, such as those caused by severe acute respiratory syndrome coronavirus and influenza A viruses (including H1N1), are also discussed. Studies have reported that traditional Chinese medicine treatment plays a significant role in improving clinical symptoms. Therefore, further investigation may be of high translational value in revealing novel targeted therapies for COVID-19.
ABSTRACT
Purpose: The novel coronavirus disease 2019 (COVID-19) epidemic is the severe global pandemic with large numbers of infected cases and deaths in recent decades. The previous studies were all about the influence of albumin (ALB) for the severity and mortality of in-patients infected with COVID-19. But few studies exist about the influence factors to achieve viral negative conversion. Therefore, this study conducted an exploratory study to investigate the effect of albumin on negative conversion rate. Methods: Among the 190 hospitalized patients with moderate COVID-19 who had a course of disease longer than 30 days, 102 achieved viral negative conversion in 30-45 days and 88 not after 45 days. Taking other variables as concomitant variable, Cox proportional hazard regression model was applied to explore the influence of albumin to negative conversion rate under various factors. Results: By comparing patients who could and could not achieve the finally viral negative conversion, a possible nonlinear relationship between the continuous variables and clinical outcomes was examined by a restricted cubic spline regression model. An association was found between albumin levels and hazard ratio of viral negative conversion rate (P = 0.027). The increase of albumin was accompanied with decreases of hazard ratio of viral negative conversion rate (the value of albumin <38 g/L). But when the value of albumin was higher than 38 g/L, the hazard ratio of viral negative conversion rate approached 1, it means that albumin is not a risk factor for the viral negative conversion rate of COVID-19 disease. Conclusion: For patients with COVID-19, albumin is a common and observed laboratory parameter. It is associated with final viral negative conversion rate although its underlying mechanism and relationship with the viral negative conversion rate still need to be clarified.
ABSTRACT
Background: During the fight against coronavirus disease 2019 (COVID-19) in China, Qingfei Paidu decoction (QFPDD) has been widely applied to treat COVID-19 patients. Retrospective studies showed that QFPDD could improve clinical outcomes of COVID-19. Thus, it is necessary and interesting to explore the action mode of QFPDD for further application and development. Methods: Sprague-Dawley (SD) rats were randomly divided into two groups, QFPDD (n=9) and control (n=10) groups. They were parallelly treated for 12 days with QFPDD and warm distilled water, respectively. At the endpoint, the microRNA (miRNA or miR) profiles in serum were detected to identify differently expressed miRNAs (DEMs). Then, the action mode of QFPDD were explored via review of potential roles of DEMs and functional enrichment analysis of their targets (e.g., GO enrichment and KEGG pathway analysis), especially focusing on the aspects of immunity, inflammation, virus infection and pulmonary fibrosis. Core genes were identified based on KEGG pathway analysis. Metabolomics were detected in serum and significantly changed metabolites (SCMs), especially the metabolic substrates and products of enzyme of core gene were identified as biomarkers to validate the regulation of DEMs to enzyme activity of core gene through metabolomic analysis and linear correlation analysis between SCMs and DEMs. Results: 23 DEMs were identified in the serum between QFPDD and control groups, with 1636 predicted genes. Reported evidence has showed that both the DEMs and their target genes involve regulation of immunity, inflammation, virus infection and pulmonary fibrosis. Phospholipase C, gamma 1 (Plcg1) was identified as a core gene and predicted to be upregulated attributed to downregulation of novel-89-mature. The levels of three SCMs, PC(P-18:1(11Z)/22:5(4Z,7Z,10Z,13Z,16Z)), PC(22:5(4Z,7Z,10Z,13Z,16Z)/P-18:0) and PC(16:1(9Z)/16:1(9Z)), which were the metabolic substrates of phospholipase C, were significantly reduced in QFPDD group, in addition, PC(P-18:1(11Z)/22:5(4Z,7Z,10Z,13Z,16Z)) and PC(22:5(4Z,7Z,10Z,13Z,16Z)/P-18:0) presented positively linear correlation with the expression level of novel-89-mature. The level of phosphorylcholine, a product of PCs metabolized by phospholipase C, was significantly elevated in QFPDD group. Conclusion: QFPDD can induce modification of miRNAs profile, and subsequently multi-regulate the immunity, inflammation, virus infection and pulmonary fibrosis in vivo, playing an important role for the positive outcomes of COVID-19 patients treated by QFPDD in China.
Subject(s)
Tumor Virus Infections , COVID-19 , Pyruvate Carboxylase Deficiency DiseaseABSTRACT
The rapid response to the COVID-19 pandemic led to unprecedented decreases in economic activities, thereby reducing the pollutant emissions. A random forest (RF) model was applied to determine the respective contributions of meteorology and anthropogenic emissions to the changes in air quality. The result suggested that the strict lockdown measures significantly decreased primary components such as Cr (-67 %) and Fe (-61 %) inPM2.5 (p<0.01), whereas the higher relative humidity (RH) andNH3 level and the lower air temperature (T) remarkably enhanced the production of secondary aerosol, including SO42- (29 %), NO3- (29 %), and NH4+ (21 %) (p<0.05). The positive matrix factorization (PMF) result suggested that the contribution ratios of secondary formation (SF), industrial process (IP), biomass burning (BB), coal combustion (CC), and road dust (RD) changed from 36 %, 27 %, 21 %, 12 %, and 4 % before the COVID-19 outbreak to 44 %, 20 %, 20 %, 9 %, and 7 %, respectively. The rapid increase in the contribution ratio derived from SF to PM2.5 implied that the intermittent haze events during the COVID-19 period were characterized by secondary aerosol pollution, which was mainly contributed by the unfavorable meteorological conditions and highNH3 level.