Safety and Pharmacokinetics of a Novel Double Prodrug Asc10 in Healthy Subjects

Background: ASC10 is an oral double prodrug of the active antiviral ribonucleoside analog, ASC10-A (also known as beta-d-N4-hydroxycytidine), which is a potent inhibitor of SARS-CoV-2. ASC10 is rapidly metabolized into ASC10-A in vivo after oral dosing. Here, we report the results of the first-in-human, phase 1 study to determine the safety, tolerability, and pharmacokinetics (PK) of ASC10 in healthy subjects, and to assess the food effect on the pharmacokinetics. Method(s): This study included 2 parts. Part 1 (multiple-ascending-dose) consisted of 6 cohorts (8 or 12 subjects per cohort). Eligible subjects were randomized in a 3:1 ratio to receive either twice-daily (BID) doses of 50 to 800 mg ASC10 or placebo for 5.5 days, and were then followed for 7 days for safety. In Part 2 (food effect), 12 subjects were randomized in a 1:1 ratio to either 800 mg ASC10 in the fed state followed by 800 mg in the fasted state, or vice versa, with a 7-day washout period between doses. PK blood samples were collected and measured for ASC10-A along with ASC10 and molnupiravir. Safety assessments included monitoring of adverse events (AEs), measurement of vital signs, clinical laboratory tests, and physical examinations. Result(s): ASC10-A was the major circulating metabolite ( >99.94%) in subjects after oral dosing of ASC10. ASC10-A appeared rapidly in plasma, with a median Tmax of 1.00 to 2.00 h, and declined with a geometric t1/2 of approximately 1.10 to 3.04 h. After multiple dosing for 5.5 days, both Cmax and AUC of ASC10-A increased in a dose-proportional manner from doses of 50 to 800 mg BID without accumulation. of ASC10-A in the fed state occurred slightly later, with a median of 3.99 h postdose versus 2.00 h (fasted state). However, Cmax and AUC were very similar or the same between fed and fasted states. Thus, administration of ASC10 with food is unlikely to have an effect on exposure. The incidence of AEs was similar between subjects receiving ASC10 or placebo (both 66.7%) and 95.0% of AEs were mild. There were no serious adverse events as well as no clinically significant findings in clinical laboratory, vital signs, or electrocardiography. Conclusion(s): Results of this study showed that ASC10 was well tolerated, and the increase in plasma exposure of ASC10-A was dose proportional across the range of doses tested with no accumulation and no food effect. 800 mg ASC10 BID is selected for further studies in patients infected with SARS-CoV-2.

Preliminary Recommendations on the Timing of Lung Surgery after Novel Coronavirus Infection in Patients with Pulmonary Nodules and Lung Cancer.

In recent years, the corona virus disease 2019 (COVID-19) pandemic has had a huge impact on the global medical, political and economic fields. Since the beginning of the COVID-19 epidemic, our understanding of the impact of COVID-19 has grown exponentially. Recently, the COVID-19 epidemic has changed rapidly in China, and there has been controversy over how to carry out surgical operations for patients with lung neoplastic lesions. Some studies have shown that lung cancer patients undergoing surgery are more likely to experience respiratory failure and perioperative death after contract-ing COVID-19 than the general population, however, delays in cancer treatment are also associated with increased mortality among these patients. In particular, the novel coronavirus Omikron variant has a higher transmissibility and may escape the immunity obtained through the previous novel coronavirus infection and vaccination. In order to minimize the risk of novel coronavirus infection in surgical patients, it is necessary to develop new treatment guidelines, expert consensus and preventive measures. However, the current rapid change of the epidemic situation has led to insufficient time and evidence to develop guidelines and consensus. Therefore, thoracic surgeons need to evaluate specific patient populations at higher risk of severe complications before surgery and weigh the benefit of surgical treatment against the risk of novel coronavirus infection. We try to give some recommendations on lung surgery during the current domestic epidemic situation based on the guidelines and consensus of oncology and thoracic surgery organizations in different regions on lung surgery.Copyright © 2023, Chinese Journal of Lung Cancer. All rights reserved.

Preliminary Recommendations on the Timing of Lung Surgery after Novel Coronavirus Infection in Patients with Pulmonary Nodules and Lung Cancer.

In recent years, the corona virus disease 2019 (COVID-19) pandemic has had a huge impact on the global medical, political and economic fields. Since the beginning of the COVID-19 epidemic, our understanding of the impact of COVID-19 has grown exponentially. Recently, the COVID-19 epidemic has changed rapidly in China, and there has been controversy over how to carry out surgical operations for patients with lung neoplastic lesions. Some studies have shown that lung cancer patients undergoing surgery are more likely to experience respiratory failure and perioperative death after contract-ing COVID-19 than the general population, however, delays in cancer treatment are also associated with increased mortality among these patients. In particular, the novel coronavirus Omikron variant has a higher transmissibility and may escape the immunity obtained through the previous novel coronavirus infection and vaccination. In order to minimize the risk of novel coronavirus infection in surgical patients, it is necessary to develop new treatment guidelines, expert consensus and preventive measures. However, the current rapid change of the epidemic situation has led to insufficient time and evidence to develop guidelines and consensus. Therefore, thoracic surgeons need to evaluate specific patient populations at higher risk of severe complications before surgery and weigh the benefit of surgical treatment against the risk of novel coronavirus infection. We try to give some recommendations on lung surgery during the current domestic epidemic situation based on the guidelines and consensus of oncology and thoracic surgery organizations in different regions on lung surgery.Copyright © 2023, Chinese Journal of Lung Cancer. All rights reserved.

A method for assessing the COVID-19 infection risk of riding public transit

During the pandemic, to prevent the spread of the virus, countries all adopted various safety measures, including masking, social distancing, and vaccination. However, there is a lack of methods that can quantitively evaluate the effectiveness of these countermeasures. This research first develops a model to quantitively evaluate the infection risk of riding public transit. By utilizing the developed model, the effectiveness of different countermeasures could be evaluated and compared. For demonstration purposes, the developed model is applied to a particular bus route in the City of Houston, Texas. The modeling results show that masking, social distancing, and vaccination can all reduce the infection risk for passengers. And among all these countermeasures, face masking is the most effective one. In addition, model results approve that the COVID-19 infection risk is highly related to the exposure time and the risk can be controlled by reducing the exposure time. Thus, a new strategy named the "split route strategy” is proposed and compared with the "capacity reduction strategy” using the model developed. In addition, a cost-benefit analysis is performed to assess the feasibility of the proposed "split route strategy”. Furthermore, two interviews were conducted with practitioners at Houston Metro. Both interviewees believe that face masking could significantly prevent the spread of the virus, which validated the model results. © 2022

Dynamic impacts of online investor sentiment on international crude oil prices

In recent years, international crude oil prices have been subject to unusually high fluctuations due to the ravages of the COVID-19 epidemic. Under such extreme market conditions, online investor sentiment can strengthen the correlation between oil price changes and external events. We use a (rolling-window) structural vector autoregression method to investigate the dynamic impact of online investor sentiment on WTI crude oil prices before and after the COVID-19 pandemic across multiple topics of price, supply, demand, and so on, which aims to explore the fluctuation mechanism driven by sentiment and the price changes triggered by public health events. The proposed aspect-level sentiment analysis approach can effectively distinguish and measure sentiment scores of different aspects of the oil market. Our results show that the constructed oil price prosperity index contributes 49.84% to the long-term fluctuations of WTI oil price, ranking first among the influencing factors considered. In addition, the peak value of impulse shocks to WTI oil prices rose from 6.47% to 8.40% during the period of dramatic price volatility caused by the epidemic. The results sketch the mechanisms by which investor sentiment can affect crude oil prices, which help policymakers and investors protect against extreme risks in the oil market. © 2023 Elsevier Ltd

Digital Twin for Transportation Big Data: A Reinforcement Learning-Based Network Traffic Prediction Approach

Vehicular Ad-Hoc Networks (VANETs), as the crucial support of Intelligent Transportation Systems (ITS), have received great attention in recent years. With the rapid development of VANETs, various services have generated a great deal of data that can be used for transportation planning and safe driving. Especially, with the advent of Coronavirus Disease 2019 (COVID-19), the transportation system has been impacted, thus novel modes of transportation planning and intelligent applications are necessary. Digital twins can provide powerful support for artificial intelligence applications in Transportation Big Data (TBD). The features of VANETs are varying, which arises the main challenge of digital twins applying in TBD. Network traffic prediction, as part of digital twins, is useful for network management and security in VANETs, such as network planning and anomaly detection. This paper proposes a network traffic prediction algorithm aiming at time-varying traffic flows with a large number of fluctuations. This algorithm combines Deep Q-Learning (DQN) and Generative Adversarial Networks (GAN) for network traffic feature extraction. DQN is leveraged to carry out network traffic prediction, in which GAN is involved to represent Q-network. Meanwhile, the generative network can increase the number of samples to improve the prediction error. We evaluate the performance of our method by implementing it on three real network traffic data sets. Finally, we compare the two state-of-the-art competing methods with our method. IEEE

A sustainable future-powered by gas: A brief summary from the 28th World Gas Conference (WGC)

Natural gas will play more and more important role in the sustainable low-carbon development mode characterized by low energy consumption, low pollution and low emission. It has been and will continue to be the focus of attention. The 28th World Gas Conference (WGC2022) was held on May 23-27, 2022 in Daegu, South Korea. The conference summarized the progress of world natural gas in the past four years, analyzed and judged the future development trend, and reached seven consensuses: (1) Natural gas is not only a transitional fuel, but also a basic fuel for future development. (2) Supply and demand value chain of natural gas has high flexibility and adaptability, and supply diversification has become a development advantage. (3) With the effect of the rapid increase of oil and gas price, the reversal of natural gas to coal has intensified the rapid growth of global carbon emissions. (4) Structural tension is emerging in the global LNG market, and the number of long-term agreement contracts will show an increasing trend. (5) The coordinated development of natural gas and hydrogen will accelerate the arrival of the low-carbon era. (6) Methane monitoring and leakage measurement technology in the natural gas industry will become the next important innovation. (7) Governments of various countries have continuously raised the minimum level of underground gas storage, and successively issued incentive policies to increase gas reserves and production. Based on the experience, the following suggestions are put forward for the development of China's natural gas: (1) Continue to highlight the important position of the natural gas industry, increase exploration and development, and improve supply capacity and voice;(2) To adapt to the new setup of international natural gas supply caused by the COVID-19 and the conflict between Russia and Ukraine, and to formulate overall strategies for natural gas import and export trade;(3) Attach importance to LNG business, scientifically arrange the construction of LNG import supporting facilities, and take the initiative to cooperate with natural gas resource countries;(4) The whole industrial chain of natural gas and hydrogen business should be planned and deployed together, and hydrogen and natural gas infrastructure construction should be linked up effectively;(5) Increase policy support, strengthen infrastructure construction such as underground gas storage and LNG terminal, reserve more energy to develop confidence, and build a strong defense line for energy security. © 2022 Natural Gas Industry Journal Agency. All rights reserved.

Synthesis, Antiviral, and Antibacterial Activity of the Glycyrrhizic Acid and Glycyrrhetinic Acid Derivatives.

Glycyrrhizic acid and its primary metabolite glycyrrhetinic acid, are the main active ingredients in the licorice roots (glycyrrhiza species), which are widely used in several countries of the world, especially in east asian countries (China, Japan). These ingredients and their derivatives play an important role in treating many diseases, especially infectious diseases such as COVID-19 and hepatic infections. This review aims to summarize the different ways of synthesising the amide derivatives of glycyrrhizic acid and the main ways to synthesize the glycyrrhitinic acid derivatives. Also, to determine the main biological and pharmacological activity for these compounds from the previous studies to provide essential data to researchers for future studies. Supplementary Information: The online version contains supplementary material available at 10.1134/S1068162022050132.

An Integrated Strategy Designed to Explore the Common and Diverging Mechanisms of Potential Drugs against the Novel Coronavirus Pneumonia Based on Network Pharmacology and in Silico Molecular Docking Technology

Drug repositioning may be a promising way to find potential therapies against coronavirus disease 2019. Although chloroquine and hydroxychloroquine showed controversial results against the coronavirus disease 2019 disease, the potential common and diverging mechanisms of action are not reported and need to be dissected for better understanding them. An integrated strategy was proposed to systematically decipher the common and diverging aspects of mechanism of chloroquine and hydroxychloroquine against coronavirus disease 2019-disease network based on network pharmacology and in silico molecular docking. Potential targets of the two drugs and coronavirus disease 2019 related genes were collected from online public databases. Target function enrichment analysis, tissue enrichment maps and molecular docking analysis were carried out to facilitate the systematic understanding of common and diverging mechanisms of the two drugs. Our results showed that 51 chloroquine targets and 47 hydroxychloroquine targets were associated with coronavirus disease 2019. The core targets include tumor necrosis factor, glyceraldehyde 3-phosphate dehydrogenase, lymphocyte-specific protein-tyrosine kinase, beta-2 microglobulin, nuclear receptor coactivator 1, peroxisome proliferator-activated receptor gamma and glutathione disulfide reductase. Both chloroquine and hydroxychloroquine had good binding affinity towards tumor necrosis factor (affinity=-8.6 and -8.4 kcal/mol, respectively) and glyceraldehyde 3-phosphate dehydrogenase (-7.5 and -7.5 kcal/mol). Chloroquine and hydroxychloroquine both had good affinity with angiotensin-converting enzyme 2, 3-chymotrypsin-like protease and transmembrane serine protease 2. However, hydroxychloroquine manifested better binding affinity with the three proteins comparing with that of chloroquine. Chloroquine and hydroxychloroquine could have potential to inhibit over-activated immunity and inflammation. The potential tissue-specific regulation of the two drugs against severe acute respiratory syndrome coronavirus 2 infection may related with the lung, liver, brain, placenta, kidney, blood, eye, etc. In conclusion, our data systematically demonstrated chloroquine and hydroxychloroquine may have potential regulatory effects on coronavirus disease 2019 disease network, which may affect multiple organs, protein targets and pathways. Routine measurements of the chloroquine and hydroxychloroquine blood concentrations and tailored therapy regimen may be essential. But, further rigorous and high quality randomized controlled clinical trials are warranted to validate the antiviral effects of chloroquine and hydroxychloroquine against severe acute respiratory syndrome coronavirus 2. Our proposed strategy could facilitate the drug repurposing efforts for coronavirus disease 2019 treatment.

Human coronavirus OC43 and its correlation with SARS-CoV-2

Human coronavirus OC43 (HCoV-OC43) and severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) belong to the β-coronavirus genus. Since the discovery in 1967, HCoV-OC43 has been continuously circulating in human population and has become one of the common seasonal respiratory viruses. SARS-CoV-2, which has a higher morbidity and fatality rate, appeared at the end of 2019, followed by the emergence of a variety of variants, and the transmission and infection capacity of SARS-CoV-2 has been enhanced. HCoV-OC43 may be similar to SARS-CoV-2 in terms of genomic structure and function, species evolution, epidemic characteristics and clinical manifestations. In this review, the epidemiology, genomics, phylogenetic evolution and other aspects of HCoV-OC43 and SARS-CoV-2 were analyzed. Such an analysis would be helpful to understand the association and differences between the two viruses, and provide reference for understanding the potential threats of HCoV-OC43.

English Multimode Production and Usage by Artificial Intelligence and Online Reading for Sustaining Effectiveness

In order to develop oral English and comprehensive skills, reading and writing English are more important. Artificial Intelligence (AI) plays a vital role in numerous fields of our lives, such as education, healthcare, businesses, and many others. In a short time, AI has become one of the most developed disciplines in educational technology and brings a lot of enhancement to the education system. In particular, AI has aided in the presentation of novel schooling and knowledge approaches that are currently being investigated in several sectors. Different AI-based apps, such as Chatbots, Robotic Assistants, Vidreader, Seeing AI, Classcraft, and 3D holograms, have been developed to help teachers and students take advantage of and enhance the educational system. Intelligent instruction methods and sentimentalized artificial learning assistance are given special study. The education industry's main goal and desire is to create an intelligent education system, which has been made feasible by the development of teaching assistant robots, smart classrooms based on AI, and English teaching support, among other things. AI tools can now be used in all stages of learning to further improve the educational system. Students and teachers in COVID-19 have carried out their education and teaching in a variety of methods online. Learning, including virtual learning, can be done so that citizens do not lose their knowledge. This study has presented a detailed overview of the approaches and mechanisms used in the literature and then combined the literature evidence in the form of different analyses. This review will help researchers to develop and formulate new solutions in the field. © 2022 Qin Zhao and Shah Nazir.

LCOV-NET: A LIGHTWEIGHT NEURAL NETWORK FOR COVID-19 PNEUMONIA LESION SEGMENTATION FROM 3D CT IMAGES

The wide spread of coronavirus disease 2019 (COVID-19) has become a global concern and millions of people have been infected. Chest Computed Tomography (CT) imaging is important for screening and diagnosis of this disease, where segmentation of the lung infections plays a critical role for quantitative assessment of the disease progression. Currently, 3D Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance for automatic medical image segmentation tasks. However, most 3D segmentation CNNs have a large set of parameters and huge floating point operations (FLOPs), causing high command for equipments. In this work, we propose LCOV-Net, a lightweight 3D CNN for accurate segmentation of COVID-19 pneumonia lesions from CT volumes. The core component of LCOV-Net is a lightweight attention-based convolutional block (LACB), which consists of a spatiotemporal separable convolution branch to reduce parameters and a lightweight feature calibration branch to improve the learning ability. We combined our LACB module with 3D U-Net as LCOV-Net, and tested our method on a dataset of CT scans of 130 COVID-19 patients for the infection lesion segmentation. Experimental results show that: (1) our LCOV-Net outperforms existing lightweight networks for 3D segmentation and (2) compared with the widely used 3D U-Net, our LCOV-Net improved the Dice score by around 20.36% and reduced the parameter number by 90.16%, leading to 27.93% speedup. Models and code are available at https://github.com/afeizqf/LCOVNet.

Positive impact of a telemedicine education program on practicing health care workers during the COVID-19 pandemic in Ontario, Canada: A mixed methods study of an Extension for Community Healthcare Outcomes (ECHO) program.

INTRODUCTION: In addition to shifting and expanding clinical responsibilities, rapidly evolving information and guidelines during the COVID-19 pandemic has made it difficult for health care workers (HCW) to synthesise and translate COVID-19 information into practice. This study evaluated whether a COVID-19-specific telemedicine education program (ECHO COVID) would impact health care workers' self-efficacy and satisfaction in the management of patients with COVID-19. METHODS: A prospective mixed methods parallel-design study was conducted among ECHO COVID participants using pre-post questionnaires and a focus group discussion. Questionnaire results were examined for changes in health care workers' self-efficacy and satisfaction. Focus group discussion data were analysed to explore health care workers' experience in ECHO COVID and the context of their practice during the COVID-19 pandemic. RESULTS: 239 health care workers registered in ECHO COVID and 114 (47.7%) completed questionnaires and attended at least one ECHO COVID session. Median self-efficacy scores increased from 5 (IQR 4-6) to 6 (IQR 6-6) (p < 0.0001), independent of profession, years in practice, age group, or practice environment. Participants were highly satisfied with ECHO COVID sessions with a median score of 4 (IQR 4-5). Focus group discussion data indicated that health care workers gained knowledge through ECHO COVID and revealed facilitators for ECHO COVID program success, including the transition to virtual care, the practicability of knowledge provided, and a 'perspective from the trenches.' DISCUSSION: This study demonstrated that a telemedicine education program aimed to support health care workers in managing patients with COVID-19 had a positive impact on health care workers' self-efficacy and satisfaction. This impact was specifically mediated by the ECHO COVID program.

The Impact of COVID-19 on the Dietary Diversity of Children and Adolescents: Evidence from a Rural/Urban Panel Study

This paper offers the first empirical evidence of the impact of COVID-19 on dietary diversity among children and adolescents in urban and rural families by using panel data collected in 2019 (before COVID-19) and 2020 (during COVID-19) in northern China. Our study uses panel data from 2,201 primary school students and 1,341 junior high-school students to apply the difference in differences (DID) method to estimate the impact of COVID-19 on dietary diversity among students in urban and rural families. We found that the dietary diversity score (DDS) of rural students decreased by 0.295 points (p < 0.01) compared with that of urban students during COVID-19. Specifically, COVID-19 significantly reduced the frequency of rural students' consumption of vegetables by 1.8 percent, protein-rich foods such as soybean products and nuts by 6.0 percent, meats by 4.0 percent, aquatic products by 6.7 percent, and eggs by 5.3 percent, compared with urban students. Further, COVID-19 had a significant negative effect on the dietary diversity of students from low- and middle-income groups, with the DDS of the low-income group decreasing by 0.31 points (p < 0.01) and that of the middle-income group by 0.12 points (p < 0.1).

Characteristics of carbonaceous aerosols in ambient PM2.5 during the COVID-19 period in Nanjing

In order to explore the variations of carbon components[including organic carbon (OC) and element carbon (EC)] in PM2.5 at the urban area of Nanjing during the breakout of COVID-19 period, PM2.5, OC and EC mass concentrations were measured by online monitoring from January to February 2020. Compared to the concentrations before the emergency response, the PM2.5 concentration after the emergency response was reduced by 41.2% and EC reduced by 57.9%. These results indicate that the shutdown significantly reduced PM2.5 and EC concentrations, but the OC concentration increased. Before the emergency response, the OC and EC concentrations were low in daytime and high at night and early morning. After the emergency response, the average concentration of EC only had a slight change within a day and maintained at low concentration level, OC showed a curve trend which was higher in the afternoon and lower in morning and evening. The significant decrease of PM2.5 concentration after the emergency response period led to the increasing of light radiation intensity, which promoted the formation of secondary organic carbon (SOC). The SOC concentration increased when the PM2.5 and EC concentrations decreased, and the correlation between OC and EC also decreased significantly. © 2021, China Environmental Science Press. All rights reserved.