ABSTRACT
Liupao tea, a drink homologous to medicine and food. It can treat dysentery, relieve heat, remove dampness, and regulate the intestines and stomach. The objective of this study is to explore the material basis and mechanism of Liupao tea intervention in COVID‐19 and to provide a new prevention and treatment programme for COVID‐19. We used high performance liquid chromatography to analyze the extract of Liupao tea and establish its fingerprint. The main index components of the fingerprint were determined using SARS‐COV‐2 3‐chymotrypsin‐like protease (3CLᵖʳᵒ), and an in vitro drug screening model based on fluorescence resonance energy transfer was used to evaluate its inhibitory activity in vitro. The fingerprint results showed that the alcohol extract of Liupao tea contained gallic acid, epigallocatechin gallate (EGCG), caffeine, epicatechin gallate, rutin, and ellagic acid. The molecular docking binding energies of the six index components of SARS‐CoV‐2 3Clᵖʳᵒ were all less than −5.0 kJ/mol and showed strong binding affinity. The results of in vitro activity showed that the IC₅₀ of EGCG was 8.84 μmol/L, which could inhibit SARS‐CoV‐2 3Clᵖʳᵒ to a certain extent. This study unleashed that EGCG has a certain inhibitory effect on SARS‐CoV‐2 3CLᵖʳᵒ, and Liupao tea has a certain significance as a tea drink for the prevention of COVID‐19. PRACTICAL APPLICATIONS: The objective of this study was to explore the material basis and mechanism of Liupao tea intervention in COVID‐19 and to provide a new prevention and treatment programme for COVID‐19. The molecular docking binding energies of the six index components of Liupao tea with SARS‐CoV‐2 3CLᵖʳᵒ were all less than −5.0 kJ/mol, among them, the enzyme activity experiment shows that EGCG has a certain inhibitory effect on SARS‐CoV‐2 3CLᵖʳᵒ, it can be used as a potential SARS‐CoV‐2 3CLᵖʳᵒ inhibitor. We predicted that the understandings gained in the current research may evidence that Liupao tea has a certain significance as a tea drink for the prevention of COVID‐19.
ABSTRACT
OBJECTIVE: The Coronavirus Disease 2019 (COVID-19) has brought severe damage to global health and socioeconomics. In China, traditional Chinese medicine (TCM) is the most important complementary and alternative medicine (CAM) and it has shown a beneficial role in the prevention and treatment of COVID-19. However, it is unknown whether patients are willing to accept TCM treatment. The objective of our study is to investigate the acceptance, attitude, and independent predictors of TCM among asymptomatic COVID-19 patients admitted to Shanghai fangcang hospital during the outbreak of the COVID-19 pandemic in Shanghai in 2022. METHODS: A cross-sectional study was conducted on asymptomatic COVID-19 patients in the largest fangcang hospital in Shanghai, China, from April 22, 2022, to May 25, 2022. Based on the literature review of previous similar studies, a self-report questionnaire was developed to assess the patients' attitude and acceptance of TCM, and a multivariate logistic regression analysis was conducted to determine the independent predictors of TCM acceptance. RESULTS: A total of 1,121 patients completed the survey, of whom 91.35% were willing to accept CAM treatment whereas 8.65% of participants showed no willingness. Multivariate logistic regression analysis revealed that the patients who have received two doses of COVID-19 vaccine (OR = 2.069, 95%CI: 1.029-4.162, P = 0.041 vs. not received), understood the culture of TCM (OR = 2.293, 95%CI: 1.029-4.162, P = 0.014 vs. not understood), thought the TCM treatment is safe (OR = 2.856, 95%CI: 1.334-6.112, P = 0.007 vs. not thought), thought the TCM treatment is effective (OR = 2.724, 95%CI: 1.249-5.940, P = 0.012 vs. not thought), and those who informed their attending physician if using TCM for treatment (OR = 3.455, 95%CI:1.867-6.392, P < 0.001 vs. not informed) were more likely to accept TCM treatment. However, patients who thought TCM might delay your treatment (OR = 0.256, 95%CI: 0.142-0.462, P < 0.001 not thought) was an independent predictor for unwillingness to accept TCM treatment. CONCLUSION: This study preliminarily investigated the acceptance, attitude, and predictors of intention to receive TCM among asymptomatic COVID-19 patients. It is recommended to increase the publicity of TCM, clarify the impact of TCM and communicate with attending doctors that meet the healthcare needs of asymptomatic COVID-19 patients.
Subject(s)
COVID-19 , Humans , Medicine, Chinese Traditional , COVID-19 Vaccines , Cross-Sectional Studies , Pandemics/prevention & control , China , HospitalsABSTRACT
The sudden outbreak of the Corona Virus Disease 2019 (COVID-19) broke the stable trend of air quality improvement in Chinese cities due to the emergency response measures, such as the lockdown policy. In this study, 333 Chinese cities are divided into six levels by economic factors, such as first-tier, new first-tier, second-tier, third-tier, fourth-tier, and fifth-tier, and the time of each year was defined as pre-lockdown, lockdown and reopen periods. The results show that, during the pre-lockdown period, the concentrations of NO2 and PM2.5 decreased by 10.13% and 6.15%, respectively, compared with the same period averages in 2017–2019. The fifth-tier cities have the minimum reductions of NO2 and PM2.5. The lockdown policy has significantly improved the air quality in Chinese cities during the COVID-19 pandemic. The concentrations of NO2 and PM2.5 decreased by 42.38% and 29.34%, respectively, but the air quality of first-tier cities was least affected by lockdown. During the reopen period, the concentrations of NO2 and PM2.5 decreased by 14.28% and 25.71%, respectively, and the NO2 concentrations in each city are similar for the season. The NO2 and PM2.5 concentrations in 2020 without lockdown were estimated through a multivariate linear regression model. The actual values of both NO2 and PM2.5 concentrations during the lockdown period are lower than the projected values based on the 2017–2019 trend, again indicating that the lockdown policy influences their concentrations.
Subject(s)
COVID-19 , Virus DiseasesABSTRACT
The approved worldwide use of two messenger RNA (mRNA) vaccines (BNT162b2 and mRNA-1273) in late 2020 has proven the remarkable success of mRNA therapeutics together with lipid nanoformulation technology in protecting people against coronaviruses during COVID-19 pandemic. This unprecedented and exciting dual strategy with nanoformulations and mRNA therapeutics in play is believed to be a promising paradigm in targeted cancer immunotherapy in future. Recent advances in nanoformulation technologies play a prominent role in adapting mRNA platform in cancer treatment. In this review, we introduce the biologic principles and advancements of mRNA technology, and chemistry fundamentals of intriguing mRNA delivery nanoformulations. We discuss the latest promising nano-mRNA therapeutics for enhanced cancer immunotherapy by modulation of targeted specific subtypes of immune cells, such as dendritic cells (DCs) at peripheral lymphoid organs for initiating mRNA cancer vaccine-mediated antigen specific immunotherapy, and DCs, natural killer (NK) cells, cytotoxic T cells, or multiple immunosuppressive immune cells at tumor microenvironment (TME) for reversing immune evasion. We highlight the clinical progress of advanced nano-mRNA therapeutics in targeted cancer therapy and provide our perspectives on future directions of this transformative integrated technology toward clinical implementation.
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To handle the difficulties of modeling and prediction caused by the abnormal influenza sequence during COVID-19, this study established a hybrid prediction model of Long-Short Term Memory neural network (LSTM) and seasonal autoregressive integrated moving average (SARIMA) based on Singular spectrum analysis (SSA), which provided an effective scientific basis for the high-precision prediction of influenza in Shanxi Province during the COVID-19. Seasonal-trend decomposition using Loess (STL) was adopted to analyze the season characteristics of the ratio of weekly influenza-like illness (ILI) patients in Shanxi Province, China, from the 14th week in 2010 to the 13th week in 2021. The SARIMA model, the LSTM model and the LSTM-SARIMA hybrid model based on SSA were established to predict the influenza in Shanxi Province during the COVID-19. Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) were used to evaluate the performance of the models. Affected by the COVID-19, the influenza time sequence in Shanxi Province has been complicated since the beginning of 2020, with the peak incidence much lower than before. Compared with those of the SARIMA model, the MAE and MAPE of the LSTM-SARIMA hybrid model based on SSA decreased by 28.9 and 32.2%, respectively, in fitting performance; in terms of prediction performances, the MAE and MAPE decreased by 52.5 and 52.1%, respectively. Compared with those of the LSTM model, the MAE and MAPE of the LSTM-SARIMA hybrid model based on SSA decreased by 26.2 and 27.5%, respectively, in fitting performance; in terms of prediction performances, the MAE and MAPE decreased by 35.0 and 35.3%, respectively. The fitting and prediction performances of the LSTM-SARIMA hybrid model based on SSA were better than those of the SARIMA and the LSTM models. Generally speaking, we can apply the LSTM-SARIMA hybrid model based on SSA to the prediction of influenza during the COVID-19, and offer a leg-up for public policy.
Subject(s)
COVID-19ABSTRACT
During the epidemic of coronavirus disease 2019(COVID-19), the local Centers for Disease Control were bombarded with large amounts of questions from the public and the human hotline system was unable to meet the demands. As a result, Jinan Centers for Disease Coatrd developed an "intelligent question answering robot system" to cope with this situation. This paper introduces the design of the robot system and construction and classification of the knowledge base, and evaluates its application effects. The robot system can greatly reduce pressure on the human hotline, actively record and analyze users' demands, and improve the quality and efficiency of Centers for Disease Coatrd consultation service. It is a valuable and growable operating mode of consultation service, which can provide reference for the information service in future public health events.
ABSTRACT
Liupao tea, a drink homologous to medicine and food. It can treat dysentery, relieve heat, remove dampness, and regulate the intestines and stomach. The objective of this study is to explore the material basis and mechanism of Liupao tea intervention in COVID-19 and to provide a new prevention and treatment programme for COVID-19. We used high performance liquid chromatography to analyze the extract of Liupao tea and establish its fingerprint. The main index components of the fingerprint were determined using SARS-COV-2 3-chymotrypsin-like protease (3CLpro ), and an in vitro drug screening model based on fluorescence resonance energy transfer was used to evaluate its inhibitory activity in vitro. The fingerprint results showed that the alcohol extract of Liupao tea contained gallic acid, epigallocatechin gallate (EGCG), caffeine, epicatechin gallate, rutin, and ellagic acid. The molecular docking binding energies of the six index components of SARS-CoV-2 3Clpro were all less than -5.0 kJ/mol and showed strong binding affinity. The results of in vitro activity showed that the IC50 of EGCG was 8.84 µmol/L, which could inhibit SARS-CoV-2 3Clpro to a certain extent. This study unleashed that EGCG has a certain inhibitory effect on SARS-CoV-2 3CLpro , and Liupao tea has a certain significance as a tea drink for the prevention of COVID-19. PRACTICAL APPLICATIONS: The objective of this study was to explore the material basis and mechanism of Liupao tea intervention in COVID-19 and to provide a new prevention and treatment programme for COVID-19. The molecular docking binding energies of the six index components of Liupao tea with SARS-CoV-2 3CLpro were all less than -5.0 kJ/mol, among them, the enzyme activity experiment shows that EGCG has a certain inhibitory effect on SARS-CoV-2 3CLpro , it can be used as a potential SARS-CoV-2 3CLpro inhibitor. We predicted that the understandings gained in the current research may evidence that Liupao tea has a certain significance as a tea drink for the prevention of COVID-19.