A Novel Emerging Topic Identification and Evolution Discovery Method on Time-Evolving and Heterogeneous Online Social Networks

With the fast development of web 2.0, information generation and propagation among online users become deeply interweaved. How to effectively and immediately discover the new emerging topic and further how to uncover its evolution law are still wide open and urgently needed by both research and practical fields. This paper proposed a novel early emerging topic detection and its evolution law identification framework based on dynamic community detection method on time-evolving and scalable heterogeneous social networks. The framework is composed of three major steps. Firstly, a time-evolving and scalable complex network denoted as KeyGraph is built up by deeply analyzing the text features of all kinds of data crawled from heterogeneous online social network platforms; secondly, a novel dynamic community detection method is proposed by which the new emerging topic is detected on the modeled time-evolving and scalable KeyGraph network; thirdly, a unified directional topic propagation network modeled by a great number of short texts including microblogs and news titles is set up, and the topic evolution law of the previously detected early emerging topic is identified by fully utilizing local network variations and modularity optimization of the “time-evolving” and directional topic propagation network. Our method is proved to yield preferable results on both a huge amount of computer-generated test data and a great amount of real online network data crawled from mainstream heterogeneous social networks.

Four species of bacteria deterministically assemble to form a stable biofilm in a millifluidic channel

Multispecies microbial adherent communities are widespread in nature and organisms, although the principles of their assembly and development remain unclear. Here, we test the possibility of establishing a simplified but relevant model of multispecies biofilm in a non-invasive laboratory setup for the real-time monitoring of community development. We demonstrate that the four chosen species (Bacillus thuringiensis, Pseudomonas fluorescens, Kocuria varians, and Rhodocyclus sp.) form a dynamic community that deterministically reaches its equilibrium after ~30 h of growth. We reveal the emergence of complexity in this simplified community as reported by an increase in spatial heterogeneity and non-monotonic developmental kinetics. Importantly, we find interspecies interactions consisting of competition for resources—particularly oxygen—and both direct and indirect physical interactions. The simplified experimental model opens new avenues to the study of adherent bacterial communities and their behavior in the context of rapid global change.

Mechanisms of microbe-immune system dialogue within the skin

The prevalence and severity of dermatological conditions such as atopic dermatitis have increased dramatically during recent decades. Many of the factors associated with an altered risk of developing inflammatory skin disorders have also been shown to alter the composition and diversity of non-pathogenic microbial communities that inhabit the human host. While the most densely microbial populated organ is the gut, culture and non-culture-based technologies have revealed a dynamic community of bacteria, fungi, viruses and mites that exist on healthy human skin, which change during disease. In this review, we highlight some of the recent findings on the mechanisms through which microbes interact with each other on the skin and the signalling systems that mediate communication between the immune system and skin-associated microbes. In addition, we summarize the ongoing clinical studies that are targeting the microbiome in patients with skin disorders. While significant efforts are still required to decipher the mechanisms underpinning host-microbe communication relevant to skin health, it is likely that disease-related microbial communities, or Dermatypes, will help identify personalized treatments and appropriate microbial reconstitution strategies.