Uncovering the unique characteristics of the mandible to improve clinical approaches to mandibular regeneration

Thoughts on the Etiology of Cherubism

Cherubism is nowadays classified as an autoimmune disease and was first described in 1933. Although suspected at that time to be the result of defective tooth development, it was primarily classified as a bone disease caused by a mutation in the SH3BP2 gene. Despite a knock-in mouse model, phenotypic signs in the jaw area were not reproducible in this model. The features of classical cherubism can be attributed to a disturbed formation of the dental placode of the second molar. Since 2019, it has become clear that inhibition of the WNT pathway leads to the accumulation of SH3BP2 via tankyrase inhibition. As the dental placode is triggered via WNT (in epithelia) and MSX1 (in mesenchyme), aplasia of the second and third molars occurs due to a block in the WNT pathway. The mesenchymal part, which occurs prior to the body plan regulation of the WNT/MSX1 pathway, remains unaffected and provides the substrate for the giant cell granuloma. Considering macrophage polarization and the role of the extracellular matrix in general, cherubism is situated in the field of tension between autoimmune diseases and cancer. In this sense, we see the cause of cherubism in a WNT-related dysregulation, which can be proven postnatally in the neural crest-related tooth development of the replacement tooth ridge, both genotypically and phenotypically.

Features and networks of the mandible on computed tomography

The mandible or lower jaw is the largest and hardest bone in the human facial skeleton. Fractures of the mandible are reported to be a common facial trauma in emergency medicine and gaining insights into mandibular morphology in different facial types can be helpful for trauma treatment. Furthermore, features of the mandible play an important role in forensics and anthropology for identifying gender and individuals. Thus, discovering hidden information of the mandible can benefit interdisciplinary research. Here, for the first time, a method of artificial intelligence-based nonlinear dynamics and network analysis are used for discovering dissimilar and similar radiographic features of mandibles between male and female subjects. Using a public dataset of 10 computed tomography scans of mandibles, the results suggest a difference in the distribution of spatial autocorrelation between genders, uniqueness in network topologies among individuals and shared values in recurrence quantification.