Host-microbiome interactions (HMIs) are critical for the modulation of biological processes and are associated with several diseases, and extensive HMI studies have generated large amounts of data. We propose that the logical representation of the knowledge derived from these data and the standardized representation of experimental variables and processes can foster integration of data and reproducibility of experiments and thereby further HMI knowledge discovery. A community-based Ontology of Host-Microbiome Interactions (OHMI) was developed following the OBO Foundry principles. OHMI leverages established (...) ontologies to create logically structured representations of microbiomes, microbial taxonomy, host species, host anatomical entities, and HMIs under different conditions and associated study protocols and types of data analysis and experimental results. (shrink)

Based on event history analysis, this study examined the survival distribution of the duration of online public opinions related to major health emergencies and its influencing factors. We analyzed the data of such emergencies that took place in China during a period of 10 years. The results of the Kaplan-Meier method and Cox proportional hazards regression analysis showed that the average duration of online public opinions regarding health emergencies is 43 days, and the median is 19 days, which dispels the (...) myth of the “Seven-day Law of Propagation.” Furthermore, the duration of online public opinions can be divided into three stages: the rapid decline stage, the slowdown stage, and the disappearing stage. In addition, the type of event, and the volume of both social media discussion and traditional media coverage all had significant impacts on the duration. Our findings provide practical implications for the carrying out of targeted and stage-based governance of public opinions. (shrink)

Based on Network Agenda Setting Model, this study collected 42,516 media reports from Party Media, commercial media, and We Media of China during the COVID-19 pandemic. We trained LDA models for topic clustering through unsupervised machine learning. Questionnaires and social network analysis methods were then applied to examine the correlation between media network agendas and public network agendas in terms of explicit and implicit topics. The study found that the media reports could be classified into 14 topics by the LDA (...) topic modeling, and the three types of media presented homogeneity in the topics of their reports, yet had their own characteristics; there was a significant correlation between the media network agenda and the public network agenda, and the We Media reports had the most prominent effect on the public network agenda; the correlation between the media agenda and the implicit public agenda was higher than that of the explicit public agenda. Overall, findings showed a significant correlation between network agendas among different media. (shrink)

The deteriorating situation of migrant workers’ health rights protection was once again highlighted in the case of Tseng Hei-tao. This case explicitly and implicitly showed that four conundrums—the Employment Restriction Conundrum, the Occupational Safety and Health (OSH) Legal Conundrum, the Morality Conundrum and the Identity Conundrum—are barriers to migrant workers’ right protection. The health rights of migrant workers could be safeguarded by abolishing the outdated household registration system designed in the planned economy era, improving the rule of law, and strengthening (...) administrative supervisions. This would fundamentally remove these barriers and thus contribute to migrant workers’ health rights protection. (shrink)