ABSTRACT
Autophagy is an intracellular degradation and recycling process that can also remove pathogenic intracellular bacteria and viruses from within cells (referred to as xenophagy) and activate the adaptive immune responses. But autophagy-especially Atg proteins including Atg8 family members-can also have proviral and probacterial effects. In this review, we summarize known interactions of bacterial, parasitic, and viral proteins with Atg8 family proteins and the outcome of these interactions on pathogen replication, autophagy, or mitophagy. We discuss the value of prediction software and the research methodology in the study of pathogen protein-Atg8 family protein interactions, with selected examples of potential LC3-interacting region motif-containing SARS-CoV-2 proteins.
Subject(s)
Bacterial Proteins/metabolism , Fungal Proteins/metabolism , Microtubule-Associated Proteins/metabolism , SARS-CoV-2/metabolism , Viral Proteins/metabolism , Autophagy , Autophagy-Related Protein 8 Family/metabolism , Humans , Mitophagy , Protein Interaction Maps , SoftwareABSTRACT
The rapid emergence of automation brings new opportunities for airport development. Airports strive to maximize passenger satisfaction as well as optimize their operation. However, the lack of knowledge of consumer preferences might be an important barrier to achieve these objectives. Therefore, our study aims to unveil the potential of service development alternatives based on artificial intelligence (AI). For this, a systematic literature review (SLR) and a quantitative analysis of a survey have been conducted. The results of the empirical research are based on 593 responses;most of the subjects belong to generation Z (digital natives) and Y (millennials). The analysis revealed attitudes towards different AI-based transport solutions and AI robots that provide information at the airports. Based on the perceived attractiveness of such services, the environmentally conscious behaviour of consumers, and sociodemographic data, subjects were classified into three different clusters (Negligents, AV Enthusiasts, and Robot Fanatics). Results proved the attractiveness of AI-based transport services that can be used in the air-side zone. Among the millennials, the idea of self-driving buses running between airport terminals is the most appealing. Greater interest in AI-based communication solutions can be perceived among generation Z. For both generations, environmentally conscious consumption is also of paramount importance. The attractiveness of AI-based solutions has been analyzed in a tourist environment, which might be a good starting point for further research into the technology acceptance of AI-based services.