Network Pharmacology Study of Boosting effect from Aiye Herb on Anti-covid Properties of Cangzhu

Introduction: Cangzhu, an herbal medicine used to treat symptoms of respiratory pneumonia in traditional Chinese medical system, has shown its effectiveness in combating fever, cough, and fatigue of current pandemic while no specialty drugs are available. Latest research in network pharmacology has confirmed the theoretical mechanism behind, the drug itself is commonly prescribed alone side another herb Aiye, which believed to be able to improve the effectiveness of Cangzhu. In this study, network pharmacology will be applied in search of potential mechanism behind. Method: The Traditional Chinese Medicine Systems Pharmacology (TCMSP) is used to filter the active compounds and the target of the prescription compound. The Genecard and OMIM database are applied to identify the target related to our aim symptom fever, cough, and fatigue. The STRING database is used to analyse the intercepted targets. Compound-target interaction and protein-protein interaction networks are constructed using the Cytoscape between target disease Covid and our medicine mixture Cangzhu and Aiye. The Kyoto Encyclopaedia of Genes and Genome (KEGG) pathway and Gene Ontology (GO) enrichment analysis are performed for investigation of the molecular mechanisms. Finally, the interaction probability between the targets and the active compounds can be determined by molecular docking technology. Results: A total of 14 target are identified, in which are 10 most important targets and 2 key compounds. Besides, 216 biological processes items are obtained (P<0.05). Two hundred and seventy-one pathways are obtained (P<0.05). The result of molecular docking shows a stable binding between the active compounds and the target. Copyright © 2022 Textile Bioengineering and Informatics Society.

Guest Editorial for Selected Papers From BIOKDD 2020

THE 19th International Workshop on Data Mining in Bioinformatics (BIOKDD 2020) was held virtually on August 24, 2020 due to the COVID-19 pandemic. BIOKDD 2020 featured the special theme of "Battling COVID-19" which particularly welcomed paper submissions and invited talks related to COVID-19 research. As a whole-day workshop, altogether 15 submissions were accepted among a total of 35 submissions, and they were divided into 4 sessions: (1) Bioinformatics, (2) Data Curation, (3) Deep Learning with Biomedical Data, and (4) Data Mining & Statistical Methods. There are also 7 invited talks by domain experts. This special section features the extended versions of 6 quality papers presented in BIOKDD 2020.

The Impact of Remote Learning on College Students' Workload and Productivity during the COVID-19 Pandemic

Many college students had to switch to remote learning during the COVID-19 pandemic. Analyzing their workload and productivity after this major change is helpful to improve remote learning and teaching under these circumstances;however, there is limited quantitative evidence. Therefore, this study aims to quantitatively explore the impact of remote learning on college students' workload and productivity in the US during the pandemic. Within this issue, this research also asseses the impact of assistantships (i.e., students get paid for research, teaching, or other work) on students' workload and productivity, which has not been examined in remote learning during the pandemic. An online survey was developed and distributed, with 48 valid responses received. Descriptive analysis showed that total workload and overall productivity in remote learning were decreased, and students with assistantships had a higher total workload and higher productivity than those of students without assistantships. T-test indicated that the overall productivity in remote learning was reduced, with the most significant decrease in lecture attendance. Specifically, no significant difference in total workload between face-to-face and remote learning was detected, while significant differences in total workload and overall productivity between students with and without assistantships were identified. Further exploration of participants' comments suggested the folloiwng major reasons for decreased productivity, including inadequate learning location, distraction, lack of self-motivation, and technology and connectivity issues. This study can help students and instructors better arrange study contents to improve remote learning productivity and further reduce the negative impact of the pandemic on education activities.

CRYO-RALIB - A MODULAR LIBRARY FOR ACCELERATING ALIGNMENT IN CRYO-EM

Thanks to GPU-accelerated processing, cryo-EM has become a rapid structure determination method that permits capture of dynamical structures of molecules in solution, which has been recently demonstrated by the determination of COVID-19 spike protein in March, shortly after its breakout in late January 2020. This rapidity is critical for vaccine development in response to the emerging pandemic. Compared to the Bayesian-based 2D classification widely used in the workflow, the multi-reference alignment (MRA) is less popular. It is time-consuming despite its superior in differentiating structural variations. Interestingly, the Bayesian approach has higher complexity than MRA. We thereby reason that the popularity of Bayesian is gained through GPU acceleration, where a modular acceleration library for MRA is lacking. Here, we introduce a library called Cryo-RALib that expands the functionality of CUDA library used by GPU ISAC. It contains a GPU-accelerated MRA routine for accelerating MRA-based classification algorithms. In addition, we connect the cryo-EM image analysis with the python data science stack to make it easier for users to perform data analysis and visualization. Benchmarking on the TaiWan Computing Cloud (TWCC) shows that our implementation can accelerate the computation by one order of magnitude. The library is available at https://github.com/phonchi/Cryo-RAlib. © 2021 IEEE

‘The Future of Taiwan Studies in the Post-covid World’: Online Series on ‘covid and Governance: Global and Social Solidarity’, 31 July 2020

The covid-19 pandemic has significantly disrupted research communities and agendas worldwide, including Taiwan studies. Consequently, the largest conferences for Taiwan studies in both North America and Europe were cancelled in 2020. In response, the North American Taiwan Studies Association, the European Association of Taiwan Studies, the Japan Association for Taiwan Studies, and the International Journal of Taiwan Studies jointly organised a series of online forums that aimed to encompass transnational and interdisciplinary approaches to Taiwan studies in the context of envisioning a post-covid world. This report summarises the first event, on ‘covid and Governance: Global and Social Solidarity’, which speaks directly to a moment of chaos, frustration, and yet hopefulness for Taiwan. It presents the papers of three discussants—Drs Ya-Wen Yang, Harry Yi-Jui Wu, and Wen Liu—who identified and explored the theoretical potential and limits of different ‘keywords’ popularised during the pandemic period. © koninklijke brill nv, leiden, 2022

Network pharmacology-based analysis of Cangzhu for the treatment of Covid-19

Cangzhu is a Herbal medicine used to treat symptoms of respiratory diseases in Traditional Medicine system for hundreds of years and can be a new herbal solution for the current world pandemic. By using network pharmacology and molecular docking, this study explores the possible mechanisms of Cangzhu. One target is identified in the results. Further analysis identified 1 key target and 1 key compound. Moreover, 1052 biological processes, 61 cell compositions, and 124 molecular function items are obtained (P<0.05). One hundred and thirty pathways are obtained (P<0.05). The result of molecular docking shows a stable binding between the active compounds and the target. © 2019 Textile Bioengineering and Informatics Symposium Proceedings 2021 - 14th Textile Bioengineering and Informatics Symposium, TBIS 2021. All rights reserved.

A Cultural Interpretation of the Holistic Success and Individual Obedience of China's Fight against COVID-19 Crisis

Possibly the main reason why China can completely control the COVID-19 pandemic is that it can use state power to implement holistic and systemic deployment, integrate all resources, and form an efficient and refined grassroots management system. The sense of responsibility of the Chinese people has been a very important factor. The obedience of individuals in China does not come from the authority imposed by any external agent. It stems from its Confucian traditions and the positive pursuit of common ways of self-recognition and self-realization. These traditional values are very different from the Western individualistic construction of modernity. China's cultural orientation may not be replicated by other countries, but its way of shaping the people's sense of social responsibility and the holistic way of handling crises should be worthy of study and reference.

[Practice and thinking of acute respiratory infection surveillance for the response of emerging respiratory diseases in Shanghai].

Shanghai Municipal Center for Disease Control and Prevention has implemented an active comprehensive surveillance project of acute respiratory infections in adults in Shanghai, including influenza like illness (ILI) and severe acute respiratory infection (SARI). By testing and identifying a variety of respiratory pathogens, it was found that influenza viruses were the main pathogens in 172 ILI cases in 2019. The positive rates of influenza A (H1N1) pdm09 virus, influenza A (H3N2) virus and influenza B virus Victoria lineage were 30.81%, 14.53% and 30.55%, respectively. The positive detection of influenza A (H1N1) pdm09 virus peaked in the first quarter. The positive rate of enterovirus/human rhinovirus was 6.40%, with a positive detection peak in the third quarter, while the positive rate of adenovirus was 4.65% with a positive detection peak in the second quarter of the year. Two human coronavirus (HCoV)-OC43 positive samples, 1 HCoV-HKU1 positive sample and 1 HCoV-NL63 positive sample were detected, respectively, and no HCoV-229E positive sample was detected. The detection rate of Staphylococcus aureus was 17.44%, and the detection rate of Klebsiellapneumoniae was 9.88%. Influenza viruses were also the main pathogens in 1 447 SARI cases. The positive rates of influenza A (H1N1) pdm09 virus, influenza A (H3N2) virus and influenza B virus Victoria lineage were 5.46%, 1.73% and 0.30%, respectively. The positive detection of influenza A (H1N1) pdm09 virus (17.50%) peaked in the first quarter. The total positive detection rate of enterovirus/human rhinovirus was 2.97%, the positive detection peaked in the first quarter. The positive rate of Mycoplasma pneumoniae was 3.25% and the positive rate of Legionella was 1.04%. 5 HCoV-229E positive samples, 10 HCoV-OC43 positive samples, 7 HCoV-HKU1 positive samples and 6 HCoV-NL63 positive samples were detected. Eight strains of Staphylococcus aureus, 4 strains of Pseudomonas aeruginosa and 3 strains of Klebsiella pneumoniae were detected after cultures. By implementing the active surveillance, we not only detected a case of human infection with avian influenza A(H7N9) virus in time, but also preliminary understood the pathogenic spectrum characteristics and seasonality of ILI and SARI in Shanghai. In recent years, the surveillance methods have been continuously improved and the number of sentinel hospitals has increased gradually. In particular, for the response to COVID-19, the Surveillance Information Reporting System of Acute Respiratory Infection based on HIS system has been promoted to cover the whole city, which might lay a foundation for the active surveillance and early warning of emerging infectious diseases in the future.

[Epidemiological characteristics and measures of prevention and control of imported COVID-19 cases in early phase in Shanghai].

Objective: To analyze the epidemiological characteristics of imported COVID-19 cases in early phase in Shanghai, introduce measures and provide reference for prevention and control of imported COVID-19 cases. Methods: Data of imported COVID-19 cases in Shanghai reported as of 30 March, 2020 were obtained from National Notifiable Disease Report System of China CDC and field epidemiological investigation reports by CDCs in Shanghai. The information about measures of prevention and control was collected from official websites and platforms of the governments. Data cleaning and statistical analysis were performed with softwares of EpiData 3.1, Excel 2019 and SAS 9.4. Results: A total of 171 imported COVID-19 cases had been reported as of 30 March, 2020 in Shanghai, including 170 confirmed cases and 1 asymptomatic infection case. Among them, cases of Chinese nationality accounted for 71.3% (122/171) and cases of foreign nationality accounted for 28.7% (49/171). The median age of the cases was 23 years (P(25), P(75): 18, 35 years), and the male to female ratio of the cases was 1.3∶1. Students accounted for 56.6% (97/171). About 45.6% (78/171) of the cases fell ill before arriving in Shanghai. The cases with mild or common clinical manifestation accounted for 96.5% (165/171) and no significant difference in clinical type was observed between overseas Chinese cases and foreign cases. The epidemic curve by diagnosis date reached peak on March 24, and the number of the cases gradually declined due to the closed-loop management process of joint port prevention and control mechanism. The 171 imported COVID-19 cases were mainly from 24 countries and regions, including the United Kingdom (64 cases, 37.3%), the United States (32 cases, 18.6%), France (19 cases, 11.0%) and Italy (16 cases, 9.4%). About 40.4% of the cases (69/171) planned to continue travelling to 21 other provinces and municipalities in China. Customs quarantine and community observation/detection points identified 43.9% (75/171) cases and 31.0% (53/171) cases, respectively. Conclusions: The imported COVID-19 cases in early phase in Shanghai were mainly young population and students accounted for high proportion. The imported risk of COVID-19 was consistent with the severity of the epidemic in foreign countries. The closed-loop management model of the joint port prevention and control mechanism plays an important role in the identification and management of the imported COVID-19 cases.

[Analysis of adenovirus infection in acute respiratory tract infection cases in Shanghai from 2015 to 2019].

Objective: To study the epidemiological characteristics and mixed infection of adenovirus in acute respiratory tract infections in Shanghai from 2015 to 2019, and to provide scientific basis for the prevention and control of adenovirus. Methods: Acute respiratory tract infections were collected from 3 hospitals in Shanghai from 2015 to 2019. Relevant information was registered and respiratory specimens were sampled for detection of respiratory pathogens by multiplex PCR. Results: A total of 1 543 cases of acute respiratory tract infection were included. The positive rate of adenovirus was 2.92%(45/1 543), the positive rates of influenza like illness (ILI) and severe acute respiratory illness (SARI) were 2.74%(29/1 058) and 3.30%(16/485), respectively. The positive rate of ILI during January-May 2019 was 5.43%(7/129), higher than that in the same period of 2015- 2018 (0.52%-4.48%) (Fisher's exact test value=8.92, P=0.036). The incidence of adenovirus-positive cases was mainly distributed in the first and second quarters, accounting for 62.22% (28/45). The difference of the incidence of adenovirus-positive cases in each quarter was significant (χ(2)= 12.52, P=0.006). The positive rate in the second quarter was highest (6.03%), which was higher than that in other quarters (1.89%-2.93%). There were significant differences among different age groups (χ(2)=16.94, P=0.001), and the positive rate decreased with age (χ(2)=10.16, P=0.001). The positive rate of 13-19 years old group (9.43%) was higher than that of other age groups (1.48%-4.81%). The positive rate of student group (12.07%) was higher than that of other occupations (2.61%). The difference was systematic (χ(2)=11.53, P=0.001). Mixed infection accounted for 31.11% (14/45) of 45 adenovirus positive cases. The mixed infection rates of ILI and SARI were 34.48% (10/29) and 25.00% (4/16), respectively. Among 14 cases of mixed infection, the main mixed infection pathogens of adenovirus were influenza A virus and coronavirus. Conclusion: Adenovirus surveillance should be further strengthened in adolescents with a focus on students and other key groups in the second quarter.

[Investigation of an epidemic cluster caused by COVID⁃19 cases in incubation period in Shanghai].

Objective: To analyze the epidemiological characteristics of a cluster of 5 confirmed COVID⁃19 cases related with the transmission in incubation period of initial case, and find out the infection source and transmission chain.. Methods: According to "The Prevention and Control Protocol for Coronavirus Disease 2019 (Third Edition)" issued by the National Health Commission, a field epidemiological survey was conducted for the 5 cases in January 2020. Nasopharyngeal swabs and sputum samples were collected from them for the detection of 2019-nCoV by real time RT-PCR. Multi prevention and control measures were taken, such as tracking and screening close contacts, medical isolation observation, investigating the epidemiological link, analyzing transmission chain. Results: Case 1, who had common environmental exposure with other COVID⁃19 cases, got sick on 20 January, 2020 and was confirmed on 1 February. Case 2 became symptomatic on 22 January and was confirmed on 27 January. Case 3 got sick on 25 January and was confirmed on 30 January. Case 4 had illness onset on 20 January and was confirmed on 1 February. Case 5 got sick on 23 January and was confirmed on 31 January. Among the 5 cases, case 2 died and the illness of other cases were effectively controlled. After exclusion of other common exposure factors, case 1 had a 6-hour meeting with case 2 and case 3 on 19 January. Case 2 and case 3 might be infected by case 1 during the incubation period. It is the key point for epidemiological investigation. Conclusion: The epidemiological investigation indicates that the transmission might occur in the incubation period of COVID-19 case, close attention should be paid to it in future COVID-19 prevention and control.