Despite significant public health concerns regarding infectious diseases in air environments, potentially harmful microbiological indicators, such as antibiotic resistance genes (ARGs) in bioaerosols, have not received significant attention. Traditionally, bioaerosol studies have focused on the characterization of microbial communities; however, a more serious problem has recently arisen due to the presence of ARGs in bioaerosols, leading to an increased prevalence of horizontal gene transfer (HGT). This constitutes a process by which bacteria transfer genes to other environmental media and consequently cause infectious disease. Antibiotic resistance in water and soil environments has been extensively investigated in the past few years by applying advanced molecular and biotechnological methods. However, ARGs in bioaerosols have not received much attention. In addition, ARG and HGT profiling in air environments is greatly limited in field studies due to the absence of suitable methodological approaches. Therefore, this study comprehensively describes recent findings from published studies and some of the appropriate molecular and biotechnological methods for monitoring antibiotic resistance in bioaerosols. In addition, this review discusses the main knowledge gaps regarding current methodological issues and future research directions.

Although extensive efforts have been made to investigate the dynamics of the occurrence and abundance of antibiotic resistance genes (ARGs) in wastewater treatment plants (WWTPs), understanding the acquisition of antibiotic resistance based on the WWTP scale and the potential effects on WWTPs is of relatively less interest. In this study, metagenomic analysis was carried out to investigate whether the WWTP scale could be affected by the prevalence and persistence of ARGs and mobile genetic elements (MGEs). As a result, 152 ARG subtypes were identified in small-scale WWTP samples, while 234 ARG subtypes were identified in large-scale WWTP samples. Among the detectable ARGs, multidrug, MLS (macrolide–lincosamide–streptogramin), sulfonamide, and tetracycline resistance genes had the highest abundance, and large and small WWTPs had similar composition characteristics of ARGs. In MGE analysis, plasmids and integrons were 1.5–2.0-fold more abundant in large-scale WWTPs than in small-scale WWTPs. The profile of bacteria at the phylum level showed that Proteobacteria and Actinobacteria were the most dominant bacteria, representing approximately 70% across large- and small-scale WWTPs. Overall, the results of this study elucidate the different abundances and dissemination of ARGs between large- and small-scale WWTPs, which facilitates the development of next-generation engineered wastewater treatment systems.

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Objectives : The objective of this study is to understand digitalization and energy conversion trends and suggest future directions using text-mining-based analysis.Methods : From 2015 to 2021, published domestic research reports and policy briefings related to digitalization and energy from government departments and major media outlets were analyzed using text-mining techniques. Frequency, time-series, and association analyses were conducted to understand current trends and patterns.Results and Discussion : Frequency analysis of reports and articles published for the 2015-2021 period found that the most common keywords were, in descending order, ‘education’, ‘finance’, ‘hydrogen’, and ‘solar power’. This indicates that the core technologies of the fourth industrial revolution have been employed in various fields, with a specific focus on renewable energy for carbon neutrality. Time-series analysis confirmed that the direction of government policy has changed, and it was found that digital and energy conversion was accelerating before and after the outbreak of COVID-19 and the Korean version of the New Deal policies. Association analysis revealed that government policies associated with fourth industrial revolution technologies have been established in various fields and the commercialization of renewable energy has been active.Conclusion Analyzing domestic policy directions using text mining revealed an association between the fourth industrial revolution and carbon neutrality. Text mining techniques can be used to more effectively understanding of domestic policy trends, and it is expected that they will apply a wide variety of fields that can utilize them in the future.