The protective effects of baicalin for respiratory diseases: an update and future perspectives.

Background: Respiratory diseases are common and frequent diseases. Due to the high pathogenicity and side effects of respiratory diseases, the discovery of new strategies for drug treatment is a hot area of research. Scutellaria baicalensis Georgi (SBG) has been used as a medicinal herb in China for over 2000 years. Baicalin (BA) is a flavonoid active ingredient extracted from SBG that BA has been found to exert various pharmacological effects against respiratory diseases. However, there is no comprehensive review of the mechanism of the effects of BA in treating respiratory diseases. This review aims to summarize the current pharmacokinetics of BA, baicalin-loaded nano-delivery system, and its molecular mechanisms and therapeutical effects for treating respiratory diseases. Method: This review reviewed databases such as PubMed, NCBI, and Web of Science from their inception to 13 December 2022, in which literature was related to "baicalin", "Scutellaria baicalensis Georgi", "COVID-19", "acute lung injury", "pulmonary arterial hypertension", "asthma", "chronic obstructive pulmonary disease", "pulmonary fibrosis", "lung cancer", "pharmacokinetics", "liposomes", "nano-emulsions", "micelles", "phospholipid complexes", "solid dispersions", "inclusion complexes", and other terms. Result: The pharmacokinetics of BA involves mainly gastrointestinal hydrolysis, the enteroglycoside cycle, multiple metabolic pathways, and excretion in bile and urine. Due to the poor bioavailability and solubility of BA, liposomes, nano-emulsions, micelles, phospholipid complexes, solid dispersions, and inclusion complexes of BA have been developed to improve its bioavailability, lung targeting, and solubility. BA exerts potent effects mainly by mediating upstream oxidative stress, inflammation, apoptosis, and immune response pathways. It regulates are the NF-κB, PI3K/AKT, TGF-ß/Smad, Nrf2/HO-1, and ERK/GSK3ß pathways. Conclusion: This review presents comprehensive information on BA about pharmacokinetics, baicalin-loaded nano-delivery system, and its therapeutic effects and potential pharmacological mechanisms in respiratory diseases. The available studies suggest that BA has excellent possible treatment of respiratory diseases and is worthy of further investigation and development.

Exploring the mechanism of action of Xuanfei Baidu granule (XFBD) in the treatment of COVID-19 based on molecular docking and molecular dynamics.

Purpose: The Corona Virus Disease 2019 (COVID-19) pandemic has become a challenge of world. The latest research has proved that Xuanfei Baidu granule (XFBD) significantly improved patient's clinical symptoms, the compound drug improves immunity by increasing the number of white blood cells and lymphocytes, and exerts anti-inflammatory effects. However, the analysis of the effective monomer components of XFBD and its mechanism of action in the treatment of COVID-19 is currently lacking. Therefore, this study used computer simulation to study the effective monomer components of XFBD and its therapeutic mechanism. Methods: We screened out the key active ingredients in XFBD through TCMSP database. Besides GeneCards database was used to search disease gene targets and screen intersection gene targets. The intersection gene targets were analyzed by GO and KEGG. The disease-core gene target-drug network was analyzed and molecular docking was used for verification. Molecular dynamics simulation verification was carried out to combine the active ingredient and the target with a stable combination. The supercomputer platform was used to measure and analyze the number of hydrogen bonds, the binding free energy, the stability of protein target at the residue level, the solvent accessible surface area, and the radius of gyration. Results: XFBD had 1308 gene targets, COVID-19 had 4600 gene targets, the intersection gene targets were 548. GO and KEGG analysis showed that XFBD played a vital role by the signaling pathways of immune response and inflammation. Molecular docking showed that I-SPD, Pachypodol and Vestitol in XFBD played a role in treating COVID-19 by acting on NLRP3, CSF2, and relieve the clinical symptoms of SARS-CoV-2 infection. Molecular dynamics was used to prove the binding stability of active ingredients and protein targets, CSF2/I-SPD combination has the strongest binding energy. Conclusion: For the first time, it was found that the important active chemical components in XFBD, such as I-SPD, Pachypodol and Vestitol, reduce inflammatory response and apoptosis by inhibiting the activation of NLRP3, and reduce the production of inflammatory factors and chemotaxis of inflammatory cells by inhibiting the activation of CSF2. Therefore, XFBD can effectively alleviate the clinical symptoms of COVID-19 through NLRP3 and CSF2.

Business Performance Evaluation for Tourism Factory: Using DEA Approach and Delphi Method

The tourism industry contributes more than 10% of global GDP, and creates than 330 million jobs. Since the outbreak of COVID-19, tourism has been one of the hardest hit areas, and one of the most explosive growth sectors, in the post-COVID-19 era. This study analyses the operational efficiency of tourism factories, before and after the COVID-19 outbreak. This study develops a PADME (Product, Aesthetic, Digitalization, Management and Experience) efficiency evaluation model for the non-financial components of tourism factories. This study has also successfully developed the evaluation scale of the PADME model. In addition, with reference to studies on the operational efficiency of financial components, two output variables (turnover and net profit after tax), and three input variables (assets, R&D expenses, and employees) were set, and the efficiency of the PADME model was calculated. The data envelopment analysis (DEA) approach was used to measure the operational efficiency of tourism factories. The empirical research goals of this study are focused on 12 listed companies in Taiwan, with operational efficiency before and after COVID-19 analyzed in relation to their general and individual analyses. The conclusions of this study lead to both enlightening and practical management implications. Academically, this study fills a gap in the research on operational efficiency of tourism factories in the tourism industry.

Phylogeography and evolutionary dynamics analysis of porcine delta-coronavirus with host expansion to humans.

From 2003 onwards, three pandemics have been caused by coronaviruses: severe acute respiratory syndrome coronavirus (SARS-CoV); middle east respiratory syndrome coronavirus (MERS-CoV); and, most recently, SARS-CoV-2. Notably, all three were transmitted from animals to humans. This would suggest that animals are potential sources of epidemics for humans. The emerging porcine delta-coronavirus was reported to infect children. This is a red flag that marks the ability of PDCoV to break barriers of cross-species transmission to humans. Therefore, we conducted molecular genetic analysis of global clade PDCoV to characterize spatiotemporal patterns of viral diffusion and genetic diversity. PDCoV was classified into three major lineages, according to distribution and phylogenetic analysis of PDCoV. It can be inferred based on the analysis results of the currently known PDCoV strains that PDCoV might originate in Asia. We also selected six special spike amino acid sequences to align and analyze to find seven significant mutation sites. The accumulation of these mutations may enhance dynamic movements, accelerating spike protein membrane fusion events and transmission. Altogether, our study offers a novel insight into the diversification, evolution, and interspecies transmission and origin of PDCoV and emphasizes the need to study the zoonotic potential of the PDCoV and comprehensive surveillance and enhanced biosecurity precautions for PDCoV.

A knowledge graph-based method for epidemic contact tracing in public transportation.

Contact tracing is an effective measure by which to prevent further infections in public transportation systems. Considering the large number of people infected during the COVID-19 pandemic, digital contact tracing is expected to be quicker and more effective than traditional manual contact tracing, which is slow and labor-intensive. In this study, we introduce a knowledge graph-based framework for fusing multi-source data from public transportation systems to construct contact networks, design algorithms to model epidemic spread, and verify the validity of an effective digital contact tracing method. In particular, we take advantage of the trip chaining model to integrate multi-source public transportation data to construct a knowledge graph. A contact network is then extracted from the constructed knowledge graph, and a breadth-first search algorithm is developed to efficiently trace infected passengers in the contact network. The proposed framework and algorithms are validated by a case study using smart card transaction data from transit systems in Xiamen, China. We show that the knowledge graph provides an efficient framework for contact tracing with the reconstructed contact network, and the average positive tracing rate is over 96%.

The optimal vaccination strategy to control COVID-19: a modeling study in Wuhan City, China.

BACKGROUND: Reaching optimal vaccination rates is an essential public health strategy to control the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to simulate the optimal vaccination strategy to control the disease by developing an age-specific model based on the current transmission patterns of COVID-19 in Wuhan City, China. METHODS: We collected two indicators of COVID-19, including illness onset data and age of confirmed case in Wuhan City, from December 2, 2019, to March 16, 2020. The reported cases were divided into four age groups: group 1, ≤ 14 years old; group 2, 15 to 44 years old; group 3, 44 to 64 years old; and group 4, ≥ 65 years old. An age-specific susceptible-exposed-symptomatic-asymptomatic-recovered/removed model was developed to estimate the transmissibility and simulate the optimal vaccination strategy. The effective reproduction number (Reff) was used to estimate the transmission interaction in different age groups. RESULTS: A total of 47 722 new cases were reported in Wuhan City from December 2, 2019, to March 16, 2020. Before the travel ban of Wuhan City, the highest transmissibility was observed among age group 2 (Reff = 4.28), followed by group 2 to 3 (Reff = 2.61), and group 2 to 4 (Reff = 1.69). China should vaccinate at least 85% of the total population to interrupt transmission. The priority for controlling transmission should be to vaccinate 5% to 8% of individuals in age group 2 per day (ultimately vaccinated 90% of age group 2), followed by 10% of age group 3 per day (ultimately vaccinated 90% age group 3). However, the optimal vaccination strategy for reducing the disease severity identified individuals ≥ 65 years old as a priority group, followed by those 45-64 years old. CONCLUSIONS: Approximately 85% of the total population (nearly 1.2 billion people) should be vaccinated to build an immune barrier in China to safely consider removing border restrictions. Based on these results, we concluded that 90% of adults aged 15-64 years should first be vaccinated to prevent transmission in China.

Effectiveness of potential antiviral treatments in COVID-19 transmission control: a modelling study.

BACKGROUND: Novel coronavirus disease 2019 (COVID-19) causes an immense disease burden. Although public health countermeasures effectively controlled the epidemic in China, non-pharmaceutical interventions can neither be maintained indefinitely nor conveniently implemented globally. Vaccination is mainly used to prevent COVID-19, and most current antiviral treatment evaluations focus on clinical efficacy. Therefore, we conducted population-based simulations to assess antiviral treatment effectiveness among different age groups based on its clinical efficacy. METHODS: We collected COVID-19 data of Wuhan City from published literature and established a database (from 2 December 2019 to 16 March 2020). We developed an age-specific model to evaluate the effectiveness of antiviral treatment in patients with COVID-19. Efficacy was divided into three types: (1) viral activity reduction, reflected as transmission rate decrease [reduction was set as v (0-0.8) to simulate hypothetical antiviral treatments]; (2) reduction in the duration time from symptom onset to patient recovery/removal, reflected as a 1/γ decrease (reduction was set as 1-3 days to simulate hypothetical or real-life antiviral treatments, and the time of asymptomatic was reduced by the same proportion); (3) fatality rate reduction in severely ill patients (fc) [reduction (z) was set as 0.3 to simulate real-life antiviral treatments]. The population was divided into four age groups (groups 1, 2, 3 and 4), which included those aged ≤ 14; 15-44; 45-64; and ≥ 65 years, respectively. Evaluation indices were based on outbreak duration, cumulative number of cases, total attack rate (TAR), peak date, number of peak cases, and case fatality rate (f). RESULTS: Comparing the simulation results of combination and single medication therapy s, all four age groups showed better results with combination medication. When 1/γ = 2 and v = 0.4, age group 2 had the highest TAR reduction rate (98.48%, 56.01-0.85%). When 1/γ = 2, z = 0.3, and v = 0.1, age group 1 had the highest reduction rate of f (83.08%, 0.71-0.12%). CONCLUSIONS: Antiviral treatments are more effective in COVID-19 transmission control than in mortality reduction. Overall, antiviral treatments were more effective in younger age groups, while older age groups showed higher COVID-19 prevalence and mortality. Therefore, physicians should pay more attention to prevention of viral spread and patients deaths when providing antiviral treatments to patients of older age groups.

Concordance of Chest CT and Nucleic Acid Testing in Diagnosing Coronavirus Disease Outside its District of Origin (Wuhan, China)

OBJECTIVES: This study aimed to determine the concordance between CT and nucleic acid testing in diagnosing coronavirus disease (COVID-19) outside its district of origin (Wuhan, China). METHODS: Twenty-three consecutive patients with COVID-19, confirmed by nucleic acid testing, were enrolled from two designated hospitals outside the district of disease origin. We collected clinical, laboratory, and CT data and assessed the concordance between CT manifestations and nucleic acid test results by comparing the percentage of patients with and without abnormal CT findings. Furthermore, using Chi-square tests, we analyzed the differences in CT manifestations between patients with and without an exposure history or symptoms. RESULTS: Multiple ground-glass opacities (GGOs), with or without consolidation, were observed on the initial CT scans of 19 patients (82.6%), whereas the remaining 4 (17.4%) showed no CT abnormalities, indicating that the initial chest CT findings were not entirely concordant with the nucleic acid test results in diagnosing COVID-19. Among the latter 4 patients, we observed multiple GGOs with and without consolidation in 2 patients on the follow-up chest CT scans taken on days 7 and 14 after admission, respectively. The remaining 2 patients showed no abnormalities on the follow-up CT scans. Furthermore, abnormal CT findings were found more frequently in patients who had been exposed to COVID-19 in its district of origin than in those who had not been exposed and in symptomatic patients than in asymptomatic patients (all p<0.05). CONCLUSIONS: Patients with positive results on nucleic acid testing may or may not have the abnormal CT manifestations that are frequently found in symptomatic patients with a history of exposure to the district of COVID-19 origin.

Multiple approaches for massively parallel sequencing of SARS-CoV-2 genomes directly from clinical samples.

BACKGROUND: COVID-19 (coronavirus disease 2019) has caused a major epidemic worldwide; however, much is yet to be known about the epidemiology and evolution of the virus partly due to the scarcity of full-length SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) genomes reported. One reason is that the challenges underneath sequencing SARS-CoV-2 directly from clinical samples have not been completely tackled, i.e., sequencing samples with low viral load often results in insufficient viral reads for analyses. METHODS: We applied a novel multiplex PCR amplicon (amplicon)-based and hybrid capture (capture)-based sequencing, as well as ultra-high-throughput metatranscriptomic (meta) sequencing in retrieving complete genomes, inter-individual and intra-individual variations of SARS-CoV-2 from serials dilutions of a cultured isolate, and eight clinical samples covering a range of sample types and viral loads. We also examined and compared the sensitivity, accuracy, and other characteristics of these approaches in a comprehensive manner. RESULTS: We demonstrated that both amplicon and capture methods efficiently enriched SARS-CoV-2 content from clinical samples, while the enrichment efficiency of amplicon outran that of capture in more challenging samples. We found that capture was not as accurate as meta and amplicon in identifying between-sample variations, whereas amplicon method was not as accurate as the other two in investigating within-sample variations, suggesting amplicon sequencing was not suitable for studying virus-host interactions and viral transmission that heavily rely on intra-host dynamics. We illustrated that meta uncovered rich genetic information in the clinical samples besides SARS-CoV-2, providing references for clinical diagnostics and therapeutics. Taken all factors above and cost-effectiveness into consideration, we proposed guidance for how to choose sequencing strategy for SARS-CoV-2 under different situations. CONCLUSIONS: This is, to the best of our knowledge, the first work systematically investigating inter- and intra-individual variations of SARS-CoV-2 using amplicon- and capture-based whole-genome sequencing, as well as the first comparative study among multiple approaches. Our work offers practical solutions for genome sequencing and analyses of SARS-CoV-2 and other emerging viruses.

Concordance of Chest CT and Nucleic Acid Testing in Diagnosing Coronavirus Disease Outside its District of Origin (Wuhan, China).

OBJECTIVES: This study aimed to determine the concordance between CT and nucleic acid testing in diagnosing coronavirus disease (COVID-19) outside its district of origin (Wuhan, China). METHODS: Twenty-three consecutive patients with COVID-19, confirmed by nucleic acid testing, were enrolled from two designated hospitals outside the district of disease origin. We collected clinical, laboratory, and CT data and assessed the concordance between CT manifestations and nucleic acid test results by comparing the percentage of patients with and without abnormal CT findings. Furthermore, using Chi-square tests, we analyzed the differences in CT manifestations between patients with and without an exposure history or symptoms. RESULTS: Multiple ground-glass opacities (GGOs), with or without consolidation, were observed on the initial CT scans of 19 patients (82.6%), whereas the remaining 4 (17.4%) showed no CT abnormalities, indicating that the initial chest CT findings were not entirely concordant with the nucleic acid test results in diagnosing COVID-19. Among the latter 4 patients, we observed multiple GGOs with and without consolidation in 2 patients on the follow-up chest CT scans taken on days 7 and 14 after admission, respectively. The remaining 2 patients showed no abnormalities on the follow-up CT scans. Furthermore, abnormal CT findings were found more frequently in patients who had been exposed to COVID-19 in its district of origin than in those who had not been exposed and in symptomatic patients than in asymptomatic patients (all p<0.05). CONCLUSIONS: Patients with positive results on nucleic acid testing may or may not have the abnormal CT manifestations that are frequently found in symptomatic patients with a history of exposure to the district of COVID-19 origin.

A five-compartment model of age-specific transmissibility of SARS-CoV-2.

BACKGROUND: The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, also called 2019-nCoV) causes different morbidity risks to individuals in different age groups. This study attempts to quantify the age-specific transmissibility using a mathematical model. METHODS: An epidemiological model with five compartments (susceptible-exposed-symptomatic-asymptomatic-recovered/removed [SEIAR]) was developed based on observed transmission features. Coronavirus disease 2019 (COVID-19) cases were divided into four age groups: group 1, those ≤ 14 years old; group 2, those 15 to 44 years old; group 3, those 45 to 64 years old; and group 4, those ≥ 65 years old. The model was initially based on cases (including imported cases and secondary cases) collected in Hunan Province from January 5 to February 19, 2020. Another dataset, from Jilin Province, was used to test the model. RESULTS: The age-specific SEIAR model fitted the data well in each age group (P < 0.001). In Hunan Province, the highest transmissibility was from age group 4 to 3 (median: ß43 = 7.71 × 10- 9; SAR43 = 3.86 × 10- 8), followed by group 3 to 4 (median: ß34 = 3.07 × 10- 9; SAR34 = 1.53 × 10- 8), group 2 to 2 (median: ß22 = 1.24 × 10- 9; SAR22 = 6.21 × 10- 9), and group 3 to 1 (median: ß31 = 4.10 × 10- 10; SAR31 = 2.08 × 10- 9). The lowest transmissibility was from age group 3 to 3 (median: ß33 = 1.64 × 10- 19; SAR33 = 8.19 × 10- 19), followed by group 4 to 4 (median: ß44 = 3.66 × 10- 17; SAR44 = 1.83 × 10- 16), group 3 to 2 (median: ß32 = 1.21 × 10- 16; SAR32 = 6.06 × 10- 16), and group 1 to 4 (median: ß14 = 7.20 × 10- 14; SAR14 = 3.60 × 10- 13). In Jilin Province, the highest transmissibility occurred from age group 4 to 4 (median: ß43 = 4.27 × 10- 8; SAR43 = 2.13 × 10- 7), followed by group 3 to 4 (median: ß34 = 1.81 × 10- 8; SAR34 = 9.03 × 10- 8). CONCLUSIONS: SARS-CoV-2 exhibits high transmissibility between middle-aged (45 to 64 years old) and elderly (≥ 65 years old) people. Children (≤ 14 years old) have very low susceptibility to COVID-19. This study will improve our understanding of the transmission feature of SARS-CoV-2 in different age groups and suggest the most prevention measures should be applied to middle-aged and elderly people.

Changes in CT manifestations and RT-PCR testings of the coronavirus disease 2019 until recovery in patients with afferent infection vs. second-generation infection outside the original city (Wuhan): An observational study.

OBJECTIVE: To investigate changes in CT manifestations and results of reverse transcription polymerase chain reaction (RT-PCR) testing between afferent and second-generation coronavirus disease 2019 (COVID-19) outside the original city (Wuhan) until recovery. METHODS: We collected 26 consecutive COVID-19 patients undergoing initial and follow-up CT scans together with RT-PCR until recovery from 2 hospitals outside the original city. Seventeen patients with afferent infection and 9 with second-generation infection were assigned to Group A and B, respectively. By observing CT manifestations, we scored COVID-19, and statistically analyzed numbers of patients with changes in CT scores and RT-PCR results between stages. RESULTS: The total score of COVID-19 on initial CT manifestations was higher in Group A than in Group B (P < 0.05). COVID-19 progressed more frequently from stage 1-2, and relieved from stage 3-4 in Group A (P < 0.05). The similar trend in Group A could not be found in Group B. Results of RT-PCR in most of patients in Group A turned negative at stage 4 while those in Group B turned negative at stage 3 (P < 0.05). CONCLUSION: Changes in CT manifestation and RT-PCR result can be different between afferent and second-generation COVID-19 until recovery.

CT manifestations of the coronavirus disease 2019 of imported infection versus second-generation infection in patients outside the original district (Wuhan, China) of this disease: An observational study.

To explore the discrepancy in computed tomography (CT) manifestations of the coronavirus disease 2019 (COVID-19) in patients outside the original district (Wuhan, China) between cases with imported infection and second-generation infection, 22 patients with COVID-19 from 2 hospitals in Nanchong, China, 938 km away from the original district (Wuhan, China) of this disease were enrolled. All patients underwent initial and follow-up CT after admission during the treatment, and were divided into 2 groups. Group A and B were composed of 15 patients with a history of exposure to the original district (Wuhan, China) in short-term (i.e., imported infection), and 7 with a close contact with the patients with confirmed COVID-19 or with the healthy individuals from the original district (i.e., second-generation infection), respectively. Initial CT features including extent score and density score between groups were statistically compared. We found that all patients in group A and 3 of 7 patients in group B had abnormal CT findings while 4 of 7 patients in group B had not. Patients with abnormal CT findings were more frequent in group A than in group B (P < .05). On initial CT, pure ground glass opacity (GGO), and GGO with consolidation and/or other abnormalities were found in 20% (3/15) and 80% (12/15) patients in group A, respectively, while 1 (14.3%), 2 (28.6%), and 4 (57.1%) had pure GGOs, GGO with focal consolidation, and normal CT appearances in Group B, respectively. Patients with extent and density scores of ≥5 were more frequent in group A than in group B (all P-values < .01). Additionally, 3 of 4 (75%) patients with normal initial CT findings had focal pure GGO lesions on follow-up. In conclusion, COVID-19 in patients with a history of exposure to the original district can be severer than with the second-generation infection on CT.

A mathematical model for simulating the phase-based transmissibility of a novel coronavirus.

BACKGROUND: As reported by the World Health Organization, a novel coronavirus (2019-nCoV) was identified as the causative virus of Wuhan pneumonia of unknown etiology by Chinese authorities on 7 January, 2020. The virus was named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by International Committee on Taxonomy of Viruses on 11 February, 2020. This study aimed to develop a mathematical model for calculating the transmissibility of the virus. METHODS: In this study, we developed a Bats-Hosts-Reservoir-People transmission network model for simulating the potential transmission from the infection source (probably be bats) to the human infection. Since the Bats-Hosts-Reservoir network was hard to explore clearly and public concerns were focusing on the transmission from Huanan Seafood Wholesale Market (reservoir) to people, we simplified the model as Reservoir-People (RP) transmission network model. The next generation matrix approach was adopted to calculate the basic reproduction number (R0) from the RP model to assess the transmissibility of the SARS-CoV-2. RESULTS: The value of R0 was estimated of 2.30 from reservoir to person and 3.58 from person to person which means that the expected number of secondary infections that result from introducing a single infected individual into an otherwise susceptible population was 3.58. CONCLUSIONS: Our model showed that the transmissibility of SARS-CoV-2 was higher than the Middle East respiratory syndrome in the Middle East countries, similar to severe acute respiratory syndrome, but lower than MERS in the Republic of Korea.