The production and use of antibiotics are becoming increasingly common worldwide, and the problem of antibiotic resistance is increasing alarmingly. Drug-resistant infections threaten human life and health and impose a heavy burden on the global economy. The origin and molecular basis of bacterial resistance is the presence of antibiotic resistance genes (ARGs). Investigations on ARGs mostly focus on the environments in which antibiotics are frequently used, such as hospitals and farms. This literature review summarizes the current knowledge of the occurrence of antibiotic-resistant bacteria in nonclinical environments, such as air, aircraft wastewater, migratory bird feces, and sea areas in-depth, which have rarely been involved in previous studies.

Intestinal microbiota is considered to play an integral role in maintaining health of host by modulating several physiological functions including nutrition, metabolism and immunity. Accumulated data from human and animal studies indicate that intestinal microbes can affect lipid metabolism in host through various direct and indirect biological mechanisms. These mechanisms include the production of various signalling molecules by the intestinal microbiome, which exert a strong effect on lipid metabolism, bile secretion in the liver, reverse transport of cholesterol and energy expenditure and insulin sensitivity in peripheral tissues. This review discusses the findings of recent studies suggesting an emerging role of intestinal microbiota and its metabolites in regulating lipid metabolism and the association of intestinal microbiota with obesity. Additionally, we discuss the controversies and challenges in this research area. However, intestinal micro-organisms are also affected by some external factors, which in turn influence the regulation of microbial lipid metabolism. Therefore, we also discuss the effects of probiotics, prebiotics, diet structure, exercise and other factors on intestinal microbiological changes and lipid metabolism regulation. K E Y W O R D Sintestinal microbiota, human and animal, lipid metabolism, short-chain fatty acid, exercise and diet, metabolic disorder, obesityThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

No abstract

To investigate the difference of microbial communities among Diannan small-ear (DNSE), Dahe black (DHB) and Yorkshire (YS) pigs, we compared the microbial taxonomic and functional composition using a metagenomic approach. A total of 1,002,362 non-redundant microbial genes were identified, DHB and YS pigs had more similar genetic makeup compared with DNSE pigs. Bacteroidetes, Firmicutes and Spirochetes were the three most abundant phyla for all pig breeds, and DNSE pigs had a higher abundance of Prevotella genus than DHB and YS pigs. The functional profiles varied among the three pig breeds, DNSE pigs had more active carbohydrate metabolism and more abundant antibiotic resistance genes than the other two pig breeds. Moreover, we found that peptide and macrolide resistances genes in DNSE pigs were more abundant than that in DHB pigs (p < 0.05). This study will help to provide a theoretical basis for the development of native pig breeds in Yunnan Province, China.

Due to the impact of the COVID-19 pandemic, many students are unable to attend face-to-face courses, Therefore, in this case, distance education should be promoted to replace face-to-face education. However, because of the imbalance of education in different regions, such as the imbalance of education resources between rural and urban areas, the quality of distance education may not be guaranteed. Therefore, in China and some regions, there have been efforts made to carry out blended synchronous classroom attempts. In hybrid synchronous classroom situations, teachers’ workloads have increased, and it is difficult to fully understand students’ learning efficiency and class participation. We use deep learning to identify the behaviors of teachers and students in a blended synchronous classroom-based situation, aiming to automate the analysis of classroom videos, which can help teachers in classroom reflection and summary in a blended synchronous classroom or face-to-face classroom. In the behavior recognition of students and teachers, we combine the head, hand, and body posture information of teachers and students and add the feature pyramid (FPN) and convolutional block attention module (CBAM) for comparative experiments. Finally, S–T (student–teacher) analysis and engagement analysis were carried out on the identification results.