ABSTRACT
The prevalence of porcine enteric coronaviruses (PECs), including transmissible gastroenteritis virus (TGEV), swine acute diarrhea syndrome coronavirus (SADS-CoV), porcine delta coronavirus (PDCoV), and porcine epidemic diarrhea virus (PEDV), poses a serious threat to animal and public health. Here, we aimed to further optimize the porcine aminopeptidase N (pAPN) gene editing strategy to explore the balance between individual antiviral properties and the biological functions of pAPN in pigs. Finally, APN-chimeric gene-edited pigs were produced through a CRISPR/Cas9-mediated knock-in strategy. Further reproductive tests indicated that these gene-edited pigs exhibited normal pregnancy rates and viability. Notably, in vitro viral challenge assays further demonstrated that porcine kidney epithelial cells isolated from F1-generation gene-edited pigs could effectively inhibit TGEV infection. This study is the first to report the generation of APN-chimeric pigs, which may provide a natural host animal for characterizing PEC infection with APN and help in the development of better antiviral solutions. © 2022 Elsevier B.V.
ABSTRACT
Small and medium industries facilitate stimulate economic growth by providing employment opportunities to fogeys besides the larger firms. SMEs with their limited ability to hedge risks and bear the costs as a results of the economic stalled are also fighting the difficulties of funds and liquidity, employees, customers, and adapting technology overcoming the pandemic. Problem Statement: As SMEs area unit severely wedged by the Covid-19 scenario, some of them were reduced to the purpose of powerless to service their clientele, pay salary to their staff and be con-summated their commitment with their suppliers. Methodology: The study is determine the Covid-19, economic impacts of e-commerce on small and medium businesses in territorial do-minion. A few methodologies were explored to conduct the analysis including the stage of digital adoption among SMEs, the analysis of causes and barriers for e-commerce adoption including its edges amid the context of COVID-19. Qualitative study with a deep dive interviews conducted to collect primary data. No quota or target was set as there is no known population census knowledge on SMEs with the main focus on e-commerce. Result: Although some of the barriers may well be insurmountable for currently to the purpose that not all industries are ready to adopt e-commerce because of every industries’ structure and business operations. SMEs that had adopted e-commerce is expected to perform better than typical businesses but this can be not enough to mitigated total damages from a broken economy because of the pandemic. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
The global trade of kiwifruit started in New Zealand in the 1950s, and entered a stage of rapid development afterwards. In 2019, the trade volume of kiwifruit reached 3.46 billion U.S. dollars. The major exporters include New Zealand, Italy, Belgium and Chile, and meanwhile, China, Japan, Belgium and Germany are playing important roles in importing. At the beginning of the 2020, the COVID-19 broke out in many countries one after another. What drove the world economy down was not simply virus itself, but a series of regulations came after. The epidemic led governments to issue lockdown order, which resulted in a chain reaction and global trade shrinking, and the kiwifruit market had been hit without exception. Farmers who got used to JIT mode suffered the impact from both the upstream and downstream of the supply chain. So far, the existing literatures in relative area mainly focus on the macro market level, in which they quote official data and make speculations base on facts. In the meanwhile, there is merely no analysis of specific industries nor has the quantitative analysis of trade data been made. As a result, our study aimed to understand the fluctuation of the kiwifruit trade volume due to the COVID- 19 worldwide in an empirical way. A time sequence model was built based on the dataset collected from FAO, UN database and customs website of relevant countries to get the monthly predicted trade value in 2020. We selected several most representative import and export countries for analysis, and the results showed that although the total value of kiwifruit trading witnessed a slight drop, the fluctuation was enormously varied from month to month. The most significant import rise appeared in China in February and March, reaching 2425% and 1380%, respectively. In March, the import value in Japan soared by 446% and the export value in New Zealand raised by 167%. In terms of regions, China experienced the raging virus and ushered in the dawn at the end of February. At the beginning of the epidemic, unprecedented strict lockdown measures made it hard to get commodities from international market, which explained the declining of import in January. In February, China's imports and exports had basically recovered to normal, so the import of kiwifruit surged in the next two months. Japan is another fat part in importing kiwifruit, and a small outbreak scale as well as the lack of domestic stocks explained the rise of importing before May. New Zealand is the largest exporter of kiwifruit in the world. Although it was less affected by the epidemic, the decline of global demand at the beginning of 2020 and the short of available labor in the second quarter may be main stumbling blocks ahead their way to export. All in all, the data from January to August reflected that the greater impact had imposed on Asia and Oceania than that on Europe, except the export value in Belgium. When talking about some of the worst affected nations, U.S. A, India and Brazil are the only three countries whose number of infections have exceeded 5 million. After comparing available trade data in 2020 with previous figures separately, we found that conspicuous ups and downs had reflected in those countries. Especially in June in U.S.A and September in India, the growth rate of import reached 100% and 103%, respectively. The huge fluctuations are considered to have connection with disrupted global supply chain, hindered labor mobility, plunging global demand, the rise of trade protectionism as well as the time lag between the spread of the virus among countries. However, as those problems were prominent in North America and Europe attributed to the increasingly serious epidemic, the kiwifruit trade in those two markets may be severely affected in the future. China is one of the very first countries to emerge from the shadow of the COVID-19, which provides an opportunity for Chinese kiwifruit industry to develop the good fruit quality and seize the global market share. As the world's largest producer and importer of kiwifruit, China owned more than 1 2 thousand hectares kiwifruit orchards and yielded more than 2 million tones fruit in 2019. In the same year, China spent more than $450 million in importing kiwifruit, which made it the biggest kiwifruit buyer in international market. Although China's kiwifruit market has huge throughput, its domestic fruit needs to face problems like uneven product quality, low average profit margin and low unit output. In order to settle current problems, we came up with three suggestions: Firstly, strengthen the integration of industry and academia, and tap into regional dominant varieties;Secondly, increase government support in multiple ways in order to build a thorough export system;Finally, construct closer cooperation in worldwide and conform to international standards. All of them are intended to improve the industry of Chinese kiwifruit better and healthier by not only using the existing advantages but also exploring new ways. © 2021, Office of Journal of the Fruit Science. All right reserved.
ABSTRACT
Objective: To explore the factors affecting the interprovincial transmission and development of coronavirus disease 2019 (COVID-19) in China, with a view to providing recommendations for the formulation of preventive and control measures according to the actual conditions in different regions during the outbreak of the severe infectious disease. Methods: We collected the total number of confirmed cases of COVID-19 in 30 provinces and cities in China by the end of 24:00 February 25, 2020. Then we also collected the distance from each region to Hubei province, the proportion of population moving out from Wuhan city from January 1 to January 23, population density, urban population, traffic passenger volume, passenger turnover volume and other relevant data of each region.The cumulative confirmed cases including the most of imported cases by the end of 24:00 January 29, 2020 were taken as the first-stage cases cluster, and the cumulative newly confirmed cases including the most of secondary cases from 0:00 January 30 to 24:00 February 25, 2020 were taken as the second-stage cases cluster. Pearson bivariate correlation and linear fitting regression method were adopted to analyze the effects of population migration, transportation, economy and other factors on the transmission and development of COVID-19 in different regions. In the linear fitting regression, the multi-factor optimal subset model was used to screen the factors most closely related to COVID-19. Results: The distance from each region to Hubei province was negatively correlated with the first-stage cases cluster with the most of imported cases and the second-stage cases cluster with the most of secondary cases(t=-3.654, t=-3.679, both P<0.05). The proportion of population moving out from Wuhan, GDP, urban population, traffic passenger volume, and passenger turnover volume were positively correlated with the first-stage and second-stage cases cluster (all t>2.760, all P<0.05). GDP and the proportion of population moving out from Wuhan were most closely related to the first-stage cases cluster with the most of imported cases (t=4.173, t=7.851, all P<0.05). The first-stage cases cluster, the proportion of population moving out from Wuhan, and urban population were most closely related to the second-stage cases cluster with the most of secondary cases (t=4.734, t=3.491, t=2.855, all P<0.05). Results: GDP and the proportion of population moving out from Wuhan city had the greatest impact on the stage with the most of imported cases. The imported cases, the proportion of population moving out from Wuhan and the urban population had the greatest impact on the stage with the most of secondary cases. In the early stage of epidemic outbreak with the most of imported cases,we should consider strengthening the prevention and control of the epidemic in areas with high level of GDP and high proportion of population moving out from the epidemic area.The flow of population should be restricted more strictly as soon as possible in order to effectively curb the outbreak of the epidemic.In the later-stage of epidemic with the most of secondary cases, regionalized control policies should be formulated mainly according to the indicators of imported cases, the population proportion fromtheepidemic area, and the urban population. Finally, the contact of population should be restricted reasonably to prevent further development of the epidemic.
ABSTRACT
2019-nCoV has spread rapidly around the world, posing a major threat to global public health systems. This is the third time that a highly pathogenic coronavirus has emerged in the human population during the past 20 years. Researchers have conducted a number of studies since the coronavirus epidemic broke out, but there are no specific drugs or vaccines for coronavirus. Therefore, further systematic research on coronavirus is still needed. This review focused on the structure, life cycle and pathogenesis of coronavirus and summarized the current progress in detection approaches, treatment strategies and vaccines for COVID-19 with a view to provide references for further research.
ABSTRACT
The pandemic of coronavirus disease 2019 (COVID-19) has posed serious challenges. It is vitally important to further clarify the epidemiological characteristics of the COVID-19 outbreak for future study and prevention and control measures. Epidemiological characteristics and spatial-temporal analysis were performed based on COVID-19 cases from 21 January 2020 to 1 March 2020 in Shandong Province, and close contacts were traced to construct transmission chains. A total of 758 laboratory-confirmed cases were reported in Shandong. The sex ratio was 1.27: 1 (M: F) and the median age was 42 (interquartile range: 32-55). The high-risk clusters were identified in the central, eastern and southern regions of Shandong from 25 January 2020 to 10 February 2020. We rebuilt 54 transmission chains involving 209 cases, of which 52.2% were family clusters, and three widespread infection chains were elaborated, occurring in Jining, Zaozhuang and Liaocheng, respectively. The geographical and temporal disparity may alert public health agencies to implement specific measures in regions with different risk, and should attach importance on how to avoid household and community transmission.