We present a selective review of statistical modeling of dynamic networks. We focus on models with latent variables, specifically, the latent space models and the latent class models (or stochastic blockmodels), which investigate both the observed features and the unobserved structure of networks. We begin with an overview of the static models, and then we introduce the dynamic extensions. For each dynamic model, we also discuss its applications that have been studied in the literature, with the data source listed in Appendix. Based on the review, we summarize a list of open problems and challenges in dynamic network modeling with latent variables.

No abstract

Young-Do nam 1,5* the gut microbiome is related to various host health conditions through metabolites produced by microbiota. Investigating their relationships involves association analysis of the population-level microbiome and metabolome data, which requires the appropriate collection, handling, and storage of specimens. Simplification of the specimen handling processes will facilitate such investigations. As a pilot study for population-level studies, we collected the fecal samples from three volunteers and tested whether a single sample collection procedure, particularly using OMNIgene-GUT, can be used to reliably obtain both microbiome and metabolome data. We collected fecal samples from three young and healthy Korean adults, stored them at room temperature with and without OMNIgene-GUT solution up to three weeks, and analyzed their microbiome and metabolite profiles. We found that the microbiome profiles were stably maintained in OMNIgene-GUT solution for 21 days, and the abundance relationships among metabolites were well preserved, although their absolute abundances slightly varied over time. Our results show that a single sampling procedure suffices to obtain a fecal sample for collecting gut microbiome and gut metabolome data of an individual. We expect that the health effects of gut microbiome via fecal metabolites can be further understood by increasing the sampling size to the population level.

The increased usage of digital communication technologies has transformed online engagement into a key aspect of the modern customer experience in the hospitality industry. The flow theory is especially important for understanding customer engagement in the online environment. The purpose of this study is to examine the antecedents of flow and to investigate its influence on the positive attitudes and continuance intentions among the users of social media. The study’s results show that challenge, information quality, and system quality all play significant roles in flow; and flow leads to positive attitudes and continuance intentions, which indicates the importance of creating flow to increase customer engagement. Academically, this study contributes to the limited body of literature on the flow experience and customer engagement in the hospitality context. Additionally, it provides practical insights how to gain competitive advantages by strategically managing customer engagement with social media marketing through flow.

To address the drug-resistance of bacterial pathogens without imposing a selective survival pressure, virulence and biofilms are highly attractive targets. Here, we show that terrein, which was isolated from Aspergillus terreus, reduced virulence factors (elastase, pyocyanin, and rhamnolipid) and biofilm formation via antagonizing quorum sensing (QS) receptors without affecting Pseudomonas aeruginosa cell growth. Additionally, the effects of terrein on the production of QS signaling molecules and expression of QS-related genes were verified. Interestingly, terrein also reduced intracellular 3,5-cyclic diguanylic acid (c-di-GMP) levels by decreasing the activity of a diguanylate cyclase (DGC). Importantly, the inhibition of c-di-GMP levels by terrein was reversed by exogenous QS ligands, suggesting a regulation of c-di-GMP levels by QS; this regulation was confirmed using P. aeruginosa QS mutants. This is the first report to demonstrate a connection between QS signaling and c-di-GMP metabolism in P. aeruginosa, and terrein was identified as the first dual inhibitor of QS and c-di-GMP signaling.