Role of biofilms in the oral health of animals

In humans the importance of biofilms in disease processes is now widely recognised together with the difficulties in treating such infections once established. One of the earliest and certainly most studied biofilm in humans is that of dental plaque which is responsible for two of the most prevalent human infections, namely dental caries and periodontal disease. However, comparable studies of dental plaque in animals are relatively limited, despite the fact that similar infections also occur, and in the case of farm animals there is an associated economic impact. In addition, biofilms in the mouths of animals can also be detrimental to human health when transferred by animal bites. As a result, an understanding of both the microbial composition of animal plaque biofilms together with their role in animal diseases is important. Through the use of modern molecular studies, an insight into the oral microflora of animals is now being obtained and, to date, reveals that despite differences in terms of microbial species and relative proportions occurring between humans and animals, similarities do indeed exist. This information can be exploited in our efforts to both manage and treat infections in animals arising from the presence of an oral biofilm. This Chapter describes our current understanding of the microbial composition of animal plaque, its role in disease and how oral hygiene measures can be implemented to reduce subsequent infection.

Rockburst laboratory tests database - Application of data mining techniques

Rockburst is characterized by a violent explosion of a block causing a sudden rupture in the rock and is quite common in deep tunnels. It is critical to understand the phenomenon of rockburst, focusing on the patterns of occurrence so these events can be avoided and/or managed saving costs and possibly lives. The failure mechanism of rockburst needs to be better understood. Laboratory experiments are undergoing at the Laboratory for Geomechanics and Deep Underground Engineering (SKLGDUE) of Beijing and the system is described. A large number of rockburst tests were performed and their information collected, stored in a database and analyzed. Data Mining (DM) techniques were applied to the database in order to develop predictive models for the rockburst maximum stress (σRB) and rockburst risk index (IRB) that need the results of such tests to be determined. With the developed models it is possible to predict these parameters with high accuracy levels using data from the rock mass and specific project.