Huashibaidu formula attenuates sepsis-induced acute lung injury via suppressing cytokine storm: Implications for treatment of COVID-19.

BACKGROUND: Acute lung injury (ALI) is a common complication of sepsis with poor effective interventions. Huashibaidu formula (HSBD) showed good therapeutic effects in treating coronavirus disease 2019 (COVID-19) patients. PURPOSE: This study was designed to investigate the therapeutic potential and precise mechanism of HSBD against sepsis-induced ALI based on network pharmacology and animal experiments. MATERIALS AND METHODS: Network pharmacology was used to predict the possible mechanism of HSBD against sepsis. Next, a sepsis-induced ALI rat model via intraperitoneal lipopolysaccharide (LPS) was constructed to evaluate the level of inflammatory cytokines and the degree of lung injury. The expression of inflammation-related signaling pathways, including TLR4/NF-κB and PI3K/Akt was determined by western blot. RESULTS: Network pharmacology analysis indicated that HSBD might have a therapeutic effect on sepsis mainly by affecting inflammatory and immune responses. Animal experiments demonstrated that HSBD protected the lung tissue from LPS-induced injury, and inhibited the levels of inflammatory cytokines such as interleukin (IL)-1ß, granulocyte-macrophage colony-stimulating factor (GM-CSF), interferon (IFN)-γ and tumor necrosis factor (TNF)-α in the serum and IL-1ß, IL-5, IL-6, IL-18, GM-CSF, IFN-γ and TNF-α in the lung tissue. Western blot results revealed that HSBD downregulated the expression of TLR4/NF-κB and upregulated the expression of PI3K/Akt. CONCLUSION: The therapeutic mechanism of HSBD against sepsis-induced ALI mainly involved suppressing cytokine storms and relieving inflammatory symptoms by regulating the expression of TLR4/NF-κB and PI3K/Akt. Our study provides a scientific basis for the mechanistic investigation and clinical application of HSBD in the treatment of sepsis and COVID-19.

Cytokine Signature Associated With Disease Severity in COVID-19.

Coronavirus disease 2019 (COVID-19) broke out and then became a global epidemic at the end of 2019. With the increasing number of deaths, early identification of disease severity and interpretation of pathogenesis are very important. Aiming to identify biomarkers for disease severity and progression of COVID-19, 75 COVID-19 patients, 34 healthy controls and 23 patients with pandemic influenza A(H1N1) were recruited in this study. Using liquid chip technology, 48 cytokines and chemokines were examined, among which 33 were significantly elevated in COVID-19 patients compared with healthy controls. HGF and IL-1ß were strongly associated with APACHE II score in the first week after disease onset. IP-10, HGF and IL-10 were correlated positively with virus titers. Cytokines were significantly correlated with creatinine, troponin I, international normalized ratio and procalcitonin within two weeks after disease onset. Univariate analyses were carried out, and 6 cytokines including G-CSF, HGF, IL-10, IL-18, M-CSF and SCGF-ß were found to be associated with the severity of COVID-19. 11 kinds of cytokines could predict the severity of COVID-19, among which IP-10 and M-CSF were excellent predictors for disease severity. In conclusion, the levels of cytokines in COVID-19 were significantly correlated with the severity of the disease in the early stage, and serum cytokines could be used as warning indicators of the severity and progression of COVID-19. Early stratification of disease and intervention to reduce hypercytokinaemia may improve the prognosis of COVID-19 patients.

Alterations of the Gut Microbiota in Patients With Coronavirus Disease 2019 or H1N1 Influenza.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is an emerging serious global health problem. Gastrointestinal symptoms are common in COVID-19 patients, and severe acute respiratory syndrome coronavirus 2 RNA has been detected in stool specimens. However, the relationship between the gut microbiome and disease remains to be established. METHODS: We conducted a cross-sectional study of 30 patients with COVID-19, 24 patients with influenza A(H1N1), and 30 matched healthy controls (HCs) to identify differences in the gut microbiota by 16S ribosomal RNA gene V3-V4 region sequencing. RESULTS: Compared with HCs, COVID-19 patients had significantly reduced bacterial diversity; a significantly higher relative abundance of opportunistic pathogens, such as Streptococcus, Rothia, Veillonella, and Actinomyces; and a lower relative abundance of beneficial symbionts. Five biomarkers showed high accuracy for distinguishing COVID-19 patients from HCs with an area under the curve (AUC) up to 0.89. Patients with H1N1 displayed lower diversity and different overall microbial composition compared with COVID-19 patients. Seven biomarkers were selected to distinguish the 2 cohorts (AUC = 0.94). CONCLUSIONS: The gut microbial signature of patients with COVID-19 was different from that of H1N1 patients and HCs. Our study suggests the potential value of the gut microbiota as a diagnostic biomarker and therapeutic target for COVID-19, but further validation is needed.

[Analysis of potential role of Chinese classic prescriptions in treatment of COVID-19 based on TCMATCOV platform].

With the global outbreak of coronavirus disease 2019(COVID-19), screening of effective drugs has became the emphasis of research today; furthermore, screening of Chinese classic prescriptions has became one of the directions for drug development. This study analyzed the application of classic prescriptions in the diagnosis and treatment schemes based on the Diagnosis and Treatment Schemes for Coronavirus Disease at the country, provincial and municipal levels, and further explored its disrobing effect on COVID-19 disease severe phase network, and selected representative prescriptions for core target screening and gene enrichment analysis, so as to reveal its mechanism of action. Among them, 13 prescriptions were found to be used for 10 times or more, including Maxing Shigan Tang, Yinqiao San, Shengjiang San, Dayuan Drink, Xuanbai Chengqi Decoction. In addition, the COVID-19 efficacy prediction analysis platform(TCMATCOV platform) was used to calculate the network disturbances of the Chinese classic prescriptions involved. Based on the prediction results, 68 classic prescriptions were assessed on the COVID-19 disease network robustness disturbance. The average disturbance scores for the interaction confidence scores were ranked to be 0.4, 0.5, and 0.6 from the highest to the lowest. There were 7 prescriptions with a score of 17 or more, and 50 prescriptions with a score of 13 or more. Among them, the top three prescriptions were Ganlu Xiaodu Dan(18.19), Lengxiao Wan(17.74), and Maxing Shigan Tang(17.62). After further mining the action targets of these three prescriptions, it was found that COVID-19 disease-specific factors Ccl2, IL10, IL6 and TNF were all the targets of three prescriptions. Through the enrichment analysis of the biological processes of the core targets, it was found that the three prescriptions may prevent the development of the disease by affecting cell-to-cell adhesion, cytokine-mediated signaling pathway, and chronic inflammatory responses to COVID-19 at the severe phase. This study showed that the TCMATCOV platform could evaluate the disturbance effect of different prescriptions on the COVID-19 disease network, and predict potential effectiveness based on the robustness of drug-interfered pneumonia disease networks, so as to provide a reference for further experiments or clinical verification.

[TCMATCOV--a bioinformatics platform to predict efficacy of TCM against COVID-19].

There is urgent need to discover effective traditional Chinese medicine(TCM) for treating coronavirus disease 2019(COVID-19). The development of a bioinformatic tool is beneficial to predict the efficacy of TCM against COVID-19. Here we deve-loped a prediction platform TCMATCOV to predict the efficacy of the anti-coronavirus pneumonia effect of TCM, based on the interaction network imitating the disease network of COVID-19. This COVID-19 network model was constructed by protein-protein interactions of differentially expressed genes in mouse pneumonia caused by SARS-CoV and cytokines specifically up-regulated by COVID-19. TCMATCOV adopted quantitative evaluation algorithm of disease network disturbance after multi-target drug attack to predict potential drug effects. Based on the TCMATCOV platform, 106 TCM were calculated and predicted. Among them, the TCM with a high disturbance score account for a high proportion of the classic anti-COVID-19 prescriptions used by clinicians, suggesting that TCMATCOV has a good prediction ability to discover the effective TCM. The five flavors of Chinese medicine with a disturbance score greater than 1 are mainly spicy and bitter. The main meridian of these TCM is lung, heart, spleen, liver, and stomach meridian. The TCM related with QI and warm TCM have higher disturbance score. As a prediction tool for anti-COVID-19 TCM prescription, TCMATCOV platform possesses the potential to discovery possible effective TCM against COVID-19.

[Research progress of intervention of Chinese herbal medicine and its active components on human coronavirus].

The outbreak caused by 2019 novel coronavirus(2019-nCoV) is still spreading, posing a great threat to the safety and health of general population. However, there have not been any effective drugs for treatment, with symptomatic treatment and prevention prevailing. The treatment plans of severe acute respiratory syndrome(SARS) and Middle East respiratory syndrome(MERS) are often used for reference in clinic. The advantages of traditional Chinese medicine(TCM) in treating SARS and MERS are that it can intervene and block the progression of disease in early stage, significantly reduce symptoms, shorten the treatment duration of patients, reduce complications and side effects caused by hormone therapy. The coronavirus disease 2019(COVID-19) belongs to the category of TCM epidemic diseases. Chinese patent medicines and prescriptions in medical observation and clinical treatment were recommended in the "pneumonia diagnosis and treatment plan for new coronavirus infection"(trial version fifth) of the National Health Commission of the People's Republic of China. Qingfei Paidu Decotion was recommended for the treatment of COVID-19 by the National Health Commission of the People's Republic of China and National Administration of Traditional Chinese Medicine. TCM shows good clinical efficacy and great potential in the treatment of COVID-19. Previous studies of TCM have shown broad-spectrum antiviral activity, providing a variety of sources for the discovery of new antiviral drugs. In this paper, we reviewed traditional Chinese medicines and its active ingredients in the hope of bringing novel inspirations to the drug screening and clinical treatment for COVID-19.

Insight into COVID-2019 for pediatricians.

Since December 2019, patients with unexplained pneumonia have been found in Wuhan City, Hubei Province, China. The pathogen in these cases is a new type of coronavirus. The World Health Organization confirmed this diagnosis and named the pathogen SARSCoV-2. The disease caused by SARSCoV-2 is called Corona Virus Disease (COVID-2019). The virus is highly infectious and pathogenic, causing human-to-human transmission. At present, SARSCoV-2 is still rampant in the world. Zhengzhou City in Henan Province serves as an example, 102 people have been confirmed to be infected with SARSCoV-2 (at 24:00 on February 5th, 2020), including three children, the youngest is 4 years old. From the perspective of clinical pediatricians as the first line fighting the epidemic, this paper will discuss the clinical characteristics, prevention and control measures, outcomes, diagnosis, and treatment of pediatric cases.