Ret Signaling Is Required for Tooth Pulp Innervation during Organogenesis.

During organogenesis, the timing and patterning of dental pulp innervation require both chemoattractive and chemorepellent cues for precise spatiotemporal regulation. Our understanding of the signaling mechanisms that regulate tooth innervation during development, as well as the basic biology of these sensory neurons, remains rudimentary. In this study, we analyzed the expression and function of glial cell line-derived neurotrophic factor (GDNF) and its receptor tyrosine kinase, Ret, in the regulation of innervation of the mouse tooth pulp by dental pulpal afferent (DPA) neurons of the trigeminal ganglion (TG). Using reporter mouse models, we demonstrate that Ret is highly expressed by a subpopulation of DPA neurons projecting to the tooth pulp at both postnatal day 7 (P7) and in the adult. In the adult tooth, GDNF is highly expressed by many cell types throughout the dental pulp. Using a ubiquitous tamoxifen (TMX)-inducible Cre ( UBC-Cre/ERT2) line crossed to Ret conditional knockout mice ( Retfx/fx), Ret was deleted immediately prior to tooth innervation, and the neural projections into P7 molars were analyzed. TMX treatment was efficient in ablating >95% of Ret protein. We observed that UBC-Cre/ERT2; Retfx/fx mice had a significant reduction in the total number of neurites present within the pulp at P7, with a significant accumulation of aberrant fibers in the dental follicle and periodontium. In agreement with these findings, inhibition of Ret signaling through in vivo administration of a highly specific pharmacologic inhibitor (1NM-PP1) of Ret also caused a substantial reduction in pulpal innervation. Taken together, these findings indicate that Ret signaling regulates the timing and patterning of tooth innervation by dental primary afferent neurons of the TG during organogenesis and provide a rationale to explore whether alterations in the GDNF-Ret pathway contribute to pathophysiological conditions in the adult dentition.

Parallel computing in biomedical research.

Scalable parallel computer architectures provide the computational performance needed for advanced biomedical computing problems. The National Institutes of Health have developed a number of parallel algorithms and techniques useful in determining biological structure and function. These applications include processing electron micrographs to determine the three-dimensional structure of viruses, calculating the solvent-accessible surface area of proteins to help predict the three-dimensional conformation of these molecules from their primary structures, and searching for homologous DNA or amino acid sequences in large biological databases. Timing results demonstrate substantial performance improvements with parallel implementations compared with conventional sequential systems.