• Journal of Veterinary Science
• /
• v.25 no.2
• /
• pp.20.1-20.15
• /
• 2024

Background: Avian influenza (AI) is a contagious disease that causes illness and death in poultry and humans. High pathogenicity AI (HPAI) H5N6 outbreaks commonly occur in Quang Ninh province bordering China. In June 2021, the first HPAI H5N8 outbreak occurred at a Quang Ninh chicken farm. Objectives: This study examined the risk factors associated with HPAI H5N6 and H5N8 outbreaks in Quang Ninh. Methods: A retrospective case-control study was conducted in Quang Ninh from Nov 2021 to Jan 2022. The cases were households with susceptible poultry with two or more clinical signs and tested positive by real-time reverse transcription polymerase chain reaction. The controls were households in the same village as the cases but did not show clinical symptoms of the disease. Logistic regression models were constructed to assess the risk factors associated with HPAI outbreaks at the household level. Results: There were 38 cases with H5N6 clade 2.3.4.4h viruses (n = 35) and H5N8 clade 2.3.4.4b viruses (n = 3). Compared to the 112 controls, raising poultry in uncovered or partially covered ponds (odds ratio [OR], 7.52; 95% confidence interval [CI], 1.44-39.27), poultry traders visiting the farm (OR, 8.66; 95% CI, 2.7-27.69), farms with 50-2,000 birds (OR, 3.00; 95% CI, 1.06-8-51), and farms with ≥ 2,000 birds (OR, 11.35; 95% CI, 3.07-41.94) were significantly associated with HPAI outbreaks. Conclusions: Combining biosecurity measures, such as restricting visitor entry and vaccination in farms with more than 50 birds, can enhance the control and prevention of HPAI in Quang Ninh and its spread across borders.

• Molecules and Cells
• /
• v.45 no.12
• /
• pp.896-910
• /
• 2022

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible and potentially fatal virus. So far, most comprehensive analyses encompassing clinical and transcriptional manifestation have concentrated on the lungs. Here, we confirmed evident signs of viral infection in the lungs and spleen of SARS-CoV-2-infected K18-hACE2 mice, which replicate the phenotype and infection symptoms in hospitalized humans. Seven days post viral detection in organs, infected mice showed decreased vital signs, leading to death. Bronchopneumonia due to infiltration of leukocytes in the lungs and reduction in the spleen lymphocyte region were observed. Transcriptome profiling implicated the meticulous regulation of distress and recovery from cytokine-mediated immunity by distinct immune cell types in a time-dependent manner. In lungs, the chemokine-driven response to viral invasion was highly elevated at 2 days post infection (dpi). In late infection, diseased lungs, post the innate immune process, showed recovery signs. The spleen established an even more immediate line of defense than the lungs, and the cytokine expression profile dropped at 7 dpi. At 5 dpi, spleen samples diverged into two distinct groups with different transcriptome profile and pathophysiology. Inhibition of consecutive host cell viral entry and massive immunoglobulin production and proteolysis inhibition seemed that one group endeavored to survive, while the other group struggled with developmental regeneration against consistent viral intrusion through the replication cycle. Our results may contribute to improved understanding of the longitudinal response to viral infection and development of potential therapeutics for hospitalized patients affected by SARS-CoV-2.

• Journal of the Korean Society for information Management
• /
• v.39 no.1
• /
• pp.331-350
• /
• 2022

This study aims to understand topics of incivility related to COVID-19 from analyzing Twitter posts including COVID-19-related hate speech. To achieve the goal, a total of 63,802 tweets that were created between December 1st, 2019, and August 31st, 2021, covering three targets of hate speech including region and public facilities, groups of people, and religion were analyzed. Frequency analysis, dynamic topic modeling, and keyword co-occurrence network analysis were used to explore topics and keywords. 1) Results of frequency analysis revealed that hate against regions and public facilities showed a relatively increasing trend while hate against specific groups of people and religion showed a relatively decreasing trend. 2) Results of dynamic topic modeling analysis showed keywords of each of the three targets of hate speech. Keywords of the region and public facilities included "Daegu, Gyeongbuk local hate", "interregional hate", and "public facility hate"; groups of people included "China hate", "virus spreaders", and "outdoor activity sanctions"; and religion included "Shincheonji", "Christianity", "religious infection", "refusal of quarantine", and "places visited by confirmed cases". 3) Similarly, results of keyword co-occurrence network analysis revealed keywords of three targets: region and public facilities (Corona, Daegu, confirmed cases, Shincheonji, Gyeongbuk, region); specific groups of people (Coronavirus, Wuhan pneumonia, Wuhan, China, Chinese, People, Entry, Banned); and religion (Corona, Church, Daegu, confirmed cases, infection). This study attempted to grasp the public's anti-citizenship public opinion related to COVID-19 by identifying domestic COVID-19 hate targets and keywords using social media. In particular, it is meaningful to grasp public opinion on incivility topics and hate emotions expressed on social media using data mining techniques for hate-related to COVID-19, which has not been attempted in previous studies. In addition, the results of this study suggest practical implications in that they can be based on basic data for contributing to the establishment of systems and policies for cultural communication measures in preparation for the post-COVID-19 era.