The model system was further validated by examining the binding of one of the Opa proteins found in Neisseria and known to bind to human CEACAM1. In this example, we chose Opa 52 a Neisseria specific protein which had previously been shown to confer binding to human neutrophils or to Hela cells transfected with human CEACAM1 [8] . Since Neisseria may adhere to and be phagocytosed by neutrophils via a variety of receptors, we chose to demonstrate Opa 52 binding using E. coli expressing this protein. As expected, the Opa 52 positive bacteria were bound in greater numbers by the transgenic neutrophils than the Opa 52 negative bacteria. Thus, the model appears to mimic what is observed with human neutrophils using Opa 52 positive Neisseria. Furthermore, the model should allow investigation into insulin clearance, vasculogenesis, lumen formation, and other functions ascribed to human CEACAM1 in a physiological setting. TUBERCULOUS SARCOIDOSIS: DOES IT EXIST?   DotKnot: pseudoknot prediction using the probability dot plot under a refined energy model RNA pseudoknots are functional structure elements with key roles in viral and cellular processes. Prediction of a pseudoknotted minimum free energy structure is an NP-complete problem. Practical algorithms for RNA structure prediction including restricted classes of pseudoknots suffer from high runtime and poor accuracy for longer sequences. A heuristic approach is to search for promising pseudoknot candidates in a sequence and verify those. Afterwards, the detected pseudoknots can be further analysed using bioinformatics or laboratory techniques. We present a novel pseudoknot detection method called DotKnot that extracts stem regions from the secondary structure probability dot plot and assembles pseudoknot candidates in a constructive fashion. We evaluate pseudoknot free energies using novel parameters, which have recently become available. We show that the conventional probability dot plot makes a wide class of pseudoknots including those with bulged stems manageable in an explicit fashion. The energy parameters now become the limiting factor in pseudoknot prediction. DotKnot is an efficient method for long sequences, which finds pseudoknots with higher accuracy compared to other known prediction algorithms. DotKnot is accessible as a web server at http://dotknot.csse.uwa.edu.au. RNA is a versatile nucleic acid, which is no longer seen as the passive intermediate between DNA and proteins. Numerous functional RNAs with an astonishing variety have been uncovered in the past decade. For example, non-coding RNAs participate in a wide range of cellular processes, are able to regulate gene expression and can act as catalyst (1, 2) . Macromolecule function is closely connected to its 3D folding and structure prediction from the base sequence is thus of great importance. RNA structure formation is understood to be hierarchical and, therefore, secondary structure prediction is the foundation for determining the tertiary folding (3, 4) .