Alveolar bone loss and mineralization in the pig with experimental periodontal disease

Periodontal disease as a model to study chronic inflammation in aging

Periodontal disease is a chronic inflammatory condition that results in the destruction of the teeth supporting tissues, eventually leading to the loss of teeth and reduced quality of life. In severe cases, periodontal disease can limit proper nutritional intake, cause acute pain and infection, and cause a withdrawal from social situations due to esthetic and phonetic concerns. Similar to other chronic inflammatory conditions, periodontal disease increases in prevalence with age. Research into what drives periodontal disease pathogenesis in older adults is contributing to our general understanding of age-related chronic inflammation. This review will present periodontal disease as an age-related chronic inflammatory disease and as an effective geroscience model to study mechanisms of age-related inflammatory dysregulation. The current understanding of the cellular and molecular mechanisms that drive inflammatory dysregulation as a function of age will be discussed with a focus on the major pathogenic immune cells in periodontal disease, which include neutrophils, macrophages, and T cells. Research in the aging biology field has shown that the age-related changes in these immune cells result in the cells becoming less effective in the clearance of microbial pathogens, expansion of pathogenic subpopulations, or an increase in pro-inflammatory cytokine secretions. Such changes can be pathogenic and contribute to inflammatory dysregulation that is associated with a myriad of age-related disease including periodontal disease. An improved understanding is needed to develop better interventions that target the molecules or pathways that are perturbed with age in order to improve treatment of chronic inflammatory conditions, including periodontal disease, in older adult populations.

Characterization of Porcine Gingiva for Drug Absorption

Gingiva or gum is a part of the periodontium that surrounds the tooth. Its main function is to provide an effective barrier to both mechanical trauma and bacterial invasion. Gingiva is the target site for some topical drugs. The most common disease in gingiva is periodontal diseases (gum infections). Understanding the gingiva barrier properties could provide insights into approaches to effective drug delivery for the gingiva. Porcine gingiva was chosen as the model in the present membrane transport study. The permeability coefficients of gingiva were determined using a modified Franz diffusion cell with small diffusional area (0.03 cm2) and 12 model permeants with different physicochemical properties. The influences of edge effect and aqueous boundary layers were not observed in the modified diffusion cell setup for the small pieces of gingiva tissue samples. Lipophilic permeants exhibit higher permeability coefficients than hydrophilic permeants. A correlation was observed between the Log permeability coefficient (Log P) and Log octanol-water distribution coefficient (Log Dow) in the analysis. The permeant molecular weight (MW) was also a factor in the Log P vs. Log Dow relationship. The coefficient of Log Dow in this three-factor relationship (0.42) suggested that the gingiva barrier was less lipophilic than octanol.

An Interpretable Computer-Aided Diagnosis Method for Periodontitis From Panoramic Radiographs

Periodontitis is a prevalent and irreversible chronic inflammatory disease both in developed and developing countries, and affects about 20–50% of the global population. The tool for automatically diagnosing periodontitis is highly demanded to screen at-risk people for periodontitis and its early detection could prevent the onset of tooth loss, especially in local communities and health care settings with limited dental professionals. In the medical field, doctors need to understand and trust the decisions made by computational models and developing interpretable models is crucial for disease diagnosis. Based on these considerations, we propose an interpretable method called Deetal-Perio to predict the severity degree of periodontitis in dental panoramic radiographs. In our method, alveolar bone loss (ABL), the clinical hallmark for periodontitis diagnosis, could be interpreted as the key feature. To calculate ABL, we also propose a method for teeth numbering and segmentation. First, Deetal-Perio segments and indexes the individual tooth via Mask R-CNN combined with a novel calibration method. Next, Deetal-Perio segments the contour of the alveolar bone and calculates a ratio for individual tooth to represent ABL. Finally, Deetal-Perio predicts the severity degree of periodontitis given the ratios of all the teeth. The Macro F1-score and accuracy of the periodontitis prediction task in our method reach 0.894 and 0.896, respectively, on Suzhou data set, and 0.820 and 0.824, respectively on Zhongshan data set. The entire architecture could not only outperform state-of-the-art methods and show robustness on two data sets in both periodontitis prediction, and teeth numbering and segmentation tasks, but also be interpretable for doctors to understand the reason why Deetal-Perio works so well.

Functional tooth mobility in young pigs

Mobility is a fundamental characteristic of mammalian teeth, and has been widely used to determine individual tooth prognosis. However, the direction and extent of tooth movement under functional loads are unknown. This study investigated maxillary molar mobility, alveolar bending, and periodontal space (PDL) fluid pressure during mastication and masseter muscle contraction in young pigs, along with PDL space measurements. Twelve three-month-old farm pigs were instrumented with some or all of the following: (1) ultrasonic crystals, one implanted into the pulp chamber of a deciduous maxillary molar and additional crystals glued onto its buccal and palatal alveolar plates; (2) rosette strain gauges affixed to the buccal and palatal of alveolar ridges; (3) a pressure transducer inserted into palatal alveolar bone facing the PDL. Tooth mobility, alveolar bending, and fluid pressure were simultaneously recorded during unrestrained feeding and subsequent masseter muscle stimulation. The PDL widths were measured using micro-CT. The results indicate that during the power stroke of mastication, (1) the molar displaced buccally and apically (192 ± 95 µm) regardless of the side of chewing; (2) compressive bone strain was greater on the buccal than on the palatal alveolar plate; and (3) PDL pressure increased during the power strok (3.63 ± 0.80 kPa). Masseter contraction produced similar results but with generally lower values. The PDL widths were larger than the range of tooth mobility, and showed no correlation with the mobility. Thus occlusal function causes buccal tipping and intrusion of maxillary molars with concomitant compression of the buccal alveolar plate and raised pressure within the PDL space.