Research on Value Co-Creation New Business Model of Import Cross-Border E-Commerce Platform Ecosystem

Since the outbreak of COVID-19, the cross-border e-commerce platform has been rising rapidly because of its unique advantages. However, with the widespread application of information technologies such as mobile Internet and big data, fundamental changes have taken place in consumer preferences, consumption patterns, and marketing channels in cross-border e-commerce platforms. They also change the logic of value co-creation (VCC). The platform can achieve survive, expansion, and sustainable development by realising the value co-creation of the whole platform ecosystem. Based on the perspective of the platform ecosystem, this paper uses the grounded theory analysis method and NVivo 11.0 software carries out three-level coding on the obtained original data, and finally summarises and extracts four core categories of value co-creation mechanism: connection and interaction of value co-creators, demand mining, resource integration, and system support. The first two categories reflect stakeholders’ internal connection and interaction mechanism, and the last two categories reflect the external support mechanism in value co-creation.

A SARS-CoV-2 nanobody that can bind to the RBD region may be used for treatment in COVID-19 in animals.

Coronavirus disease 2019 (COVID-19) caused by an infectious virus, severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), poses a threat to the world. The suitable treatments must be identified for this disease in animals. Nanobody have therapeutic potential in the COVID-19. In this study, SARS-CoV-2 Spike RBD protein was used to make the nanobody. Nanobodies binding to the SARS-CoV-2 Spike RBD protein was obtained. Interestingly, the nanobody could bind to SARS-CoV-2 Spike S protein and RBD protein at the same time. Nanobodies were validated with a neutralizing antibody detection kit. The use of pseudoviruses confirmed that nanobodies could prevent pseudoviruses from infecting cells. We believe the nanobody are very valuable and could be used in the treatment of COVID-19. SARS-CoV-2 nanobodies can be rapidly mass-produced from microorganisms to block SARS-CoV-2 infection in vitro and in vivo with preventive and therapeutic effects.

Cathepsin B is a potential therapeutic target for coronavirus disease 2019 patients with lung adenocarcinoma.

Coronavirus disease 2019 (COVID-19) was declared a serious global public health emergency. Hospitalization and mortality rates of lung cancer patients diagnosed with COVID-19 are higher than those of patients presenting with other cancers. However, the reasons for the outcomes being disproportionately severe in lung adenocarcinoma (LUAD) patients with COVID-19 remain elusive. The present study aimed to identify the possible causes for disproportionately severe COVID-19 outcomes in LUAD patients and determine a therapeutic target for COVID-19 patients with LUAD. We used publicly available data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and various bioinformatics tools to identify and analyze the genes implicated in SARS-CoV-2 infection in LUAD patients. Upregulation of the SARS-CoV-2 infection-related molecules dipeptidyl peptidase 4, basigin, cathepsin B (CTSB), methylenetetrahydrofolate dehydrogenase, and peptidylprolyl isomerase B rather than angiotensin-converting enzyme 2 may explain the relatively high susceptibility of LUAD patients to SARS-CoV-2 infection. CTSB was highly expressed in the LUAD tissues after SARS-CoV-2 infection, and its expression was positively correlated with immune cell infiltration and proinflammatory cytokine expression. These findings suggest that CTSB plays a vital role in the hyperinflammatory response in COVID-19 patients with LUAD and is a promising target for the development of a novel drug therapy for COVID-19 patients.

Recent advances in vaccine development of severe acute respiratory syndrome coronavirus 2

[Abstract] The outbreak of coronavirus disease 2019 (COVID-19) has become a global pandemic. The pathogen responsible for this disease is a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It belongs to coronavirus family, a pathogen similar to SARS and Middle East respiratory syndrome (MERS), and manifests strong infectivity and pathogenicity to progress into severe pneumonia. Till now, there is no specific therapeutic drug targeting against this virus. With the rapid spread and deterioration of the epidemic situation, vaccination has become an urgent need. This review introduces the immune defense mechanism of human body against coronavirus briefly, set forth the key viral spike protein for coronavirus vaccine development, and then summarize the recent advances/progresses and potential challenges in safety and efficacy of vaccine development for SARS-CoV-2.

Spatiotemporal visualization for the global COVID-19 surveillance by balloon chart.

BACKGROUND: Considering the widespread of coronavirus disease 2019 (COVID-19) pandemic in the world, it is important to understand the spatiotemporal development of the pandemic. In this study, we aimed to visualize time-associated alterations of COVID-19 in the context of continents and countries. METHODS: Using COVID-19 case and death data from February to December 2020 offered by Johns Hopkins University, we generated time-associated balloon charts with multiple epidemiological indicators including crude case fatality rate (CFR), morbidity, mortality and the total number of cases, to compare the progression of the pandemic within a specific period across regions and countries, integrating seven related dimensions together. The area chart is used to supplement the display of the balloon chart in daily new COVID-19 case changes in UN geographic regions over time. Javascript and Vega-Lite were chosen for programming and mapping COVID-19 data in browsers for visualization. RESULTS: From February 1st to December 20th 2020, the COVID-19 pandemic spread across UN subregions in the chronological order. It was first reported in East Asia, and then became noticeable in Europe (South, West and North), North America, East Europe and West Asia, Central and South America, Southern Africa, Caribbean, South Asia, North Africa, Southeast Asia and Oceania, causing several waves of epidemics in different regions. Since October, the balloons of Europe, North America and West Asia have been rising rapidly, reaching a dramatically high morbidity level ranging from 200 to 500/10 000 by December, suggesting an emerging winter wave of COVID-19 which was much bigger than the previous ones. By late December 2020, some European and American countries displayed a leading mortality as high as or over 100/100 000, represented by Belgium, Czechia, Spain, France, Italy, UK, Hungary, Bulgaria, Peru, USA, Argentina, Brazil, Chile and Mexico. The mortality of Iran was the highest in Asia (over 60/100 000), and that of South Africa topped in Africa (40/100 000). In the last 15 days, the CFRs of most countries were at low levels of less than 5%, while Mexico had exceptional high CFR close to 10%. CONCLUSIONS: We creatively used visualization integrating 7-dimensional epidemiologic and spatiotemporal indicators to assess the progression of COVID-19 pandemic in terms of transmissibility and severity. Such methodology allows public health workers and policy makers to understand the epidemics comparatively and flexibly.

Epidemiological and clinical characteristics of 47 corona virus disease 2019 non-survivors in Huoshenshan Hospital

Objective To provide a basis for further optimizing the diagnosis and treatment strategies of severe and critical corona virus disease 2019 (COVID-19) by investigating and analyzing the epidemiological and clinical characteristics of the death cases. Methods The epidemiological and clinical characteristics of 47 death cases obtained from Huoshenshan Hospital in Whuhan, Hubei Province were retrospectively analyzed. Results All the patients developed initial symptoms in Wuhan. The time from onset to admission was (12.60±5.60) days. Most of them were male (68.09%) with non-nosocomial infection (91.49%), advanced age (>60 years, 89.36%). Over half of the cases (51.06%) reported a history of contact with suspected or confirmed patients, and comorbidity of chronic diseases (70.21%). Multiple organ dysfunction syndrome (MODS) occurred in 29 cases (61.70%) with heart failure (51.06%) and renal failure (36.17%). The main clinical symptoms included fever, fatigue, dyspnea and cough. At admission,most cases were severe (55.32%) or critical (42.55%), and the in-hospital survival was longer for the severe than for the critical (P=0.02). 76.59% of the patients received invasive mechanical ventilation, and they had a longer in-hospital survival than those with non-invasive mechanical ventilation (P<0.05). Conclusions This group of cases occurred during the peak of the COVID-19 outbreak in China, characterized by male, elder and history of chronic diseases. Acute respiratory distress syndrome (ARDS) caused by COVID-19 was responsible for patients' death, and MODS manifestated by heart and kidney failure also implicated in the process. Disease severity and invasive mechanical ventilation were related to in-hospital survival.

Automated detection and quantification of COVID-19 pneumonia: CT imaging analysis by a deep learning-based software.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) is an emerging worldwide threat to public health. While chest computed tomography (CT) plays an indispensable role in its diagnosis, the quantification and localization of lesions cannot be accurately assessed manually. We employed deep learning-based software to aid in detection, localization and quantification of COVID-19 pneumonia. METHODS: A total of 2460 RT-PCR tested SARS-CoV-2-positive patients (1250 men and 1210 women; mean age, 57.7 ± 14.0 years (age range, 11-93 years) were retrospectively identified from Huoshenshan Hospital in Wuhan from February 11 to March 16, 2020. Basic clinical characteristics were reviewed. The uAI Intelligent Assistant Analysis System was used to assess the CT scans. RESULTS: CT scans of 2215 patients (90%) showed multiple lesions of which 36 (1%) and 50 patients (2%) had left and right lung infections, respectively (> 50% of each affected lung's volume), while 27 (1%) had total lung infection (> 50% of the total volume of both lungs). Overall, 298 (12%), 778 (32%) and 1300 (53%) patients exhibited pure ground glass opacities (GGOs), GGOs with sub-solid lesions and GGOs with both sub-solid and solid lesions, respectively. Moreover, 2305 (94%) and 71 (3%) patients presented primarily with GGOs and sub-solid lesions, respectively. Elderly patients (≥ 60 years) were more likely to exhibit sub-solid lesions. The generalized linear mixed model showed that the dorsal segment of the right lower lobe was the favoured site of COVID-19 pneumonia. CONCLUSION: Chest CT combined with analysis by the uAI Intelligent Assistant Analysis System can accurately evaluate pneumonia in COVID-19 patients.