Teaching and assessment of implant dentistry in undergraduate and postgraduate education: a European consensus

This paper constitutes a summary of the consensus documents agreed at the First European Workshop on Implant Dentistry University Education held in Prague on 19-22 June 2008. Implant dentistry is becoming increasingly important treatment alternative for the restoration of missing teeth, as patients expectations and demands increase. Furthermore, implant related complications such as peri-implantitis are presenting more frequently in the dental surgery. This consensus paper recommends that implant dentistry should be an integral part of the undergraduate curriculum. Whilst few schools will achieve student competence in the surgical placement of implants this should not preclude the inclusion of the fundamental principles of implant dentistry in the undergraduate curriculum such as the evidence base for their use, indications and contraindications and treatment of the complications that may arise. The consensus paper sets out the rationale for the introduction of implant dentistry in the dental curriculum and the knowledge base for an undergraduate programme in the subject. It lists the competencies that might be sought without expectations of surgical placement of implants at this stage and the assessment methods that might be employed. The paper also addresses the competencies and educational pathways for postgraduate education in implant dentistry.

Realistic Single Cell Modeling – from Experiment to Simulation

This tutorial gives a step by step explanation of how one uses experimental data to construct a biologically realistic multicompartmental model. Special emphasis is given on the many ways that this process can be imprecise. The tutorial is intended for both experimentalists who want to get into computer modeling and for computer scientists who use abstract neural network models but are curious about biological realistic modeling. The tutorial is not dependent on the use of a specific simulation engine, but rather covers the kind of data needed for constructing a model, how they are used, and potential pitfalls in the process.