Ameloblasts produce enamel matrix proteins such as amelogenin, ameloblastin, and amelotin during tooth development. The molecular mechanisms of ameloblast differentiation (amelogenesis) are currently not well understood. SP6 is a transcription factor of the Sp/KLF family that was recently found to regulate cell proliferation in a cell-type-specific manner. Sp6-deficient mice demonstrate characteristic tooth anomalies such as delayed eruption of the incisors and supernumerary teeth with disorganized amelogenesis. However, it remains unclear how Sp6 controls amelogenesis. In this study, we used SP6 high producer cells to identify SP6 target genes. Based on the observations that long-term culture of SP6 high producer cells reduced SP6 protein expression but not Sp6 mRNA expression, we found that SP6 is short lived and specifically degraded through a proteasome pathway. We established an in vitro inducible SP6 expression system coupled with siRNA knockdown and found a possible linkage between SP6 and amelogenesis through the regulation of amelotin and Rock1 gene expression by microarray analysis. Our findings suggest that the regulation of SP6 protein stability is one of the crucial steps in amelogenesis.

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ARE cell clones can provide a useful in vitro model to study the mechanism of SP6-mediated amelogenesis imperfecta.

Ionizing radiation (IR) presents a risk to human health via DNA damage even when administered at low doses, such as those used in panoramic radiography. Objectives: This study used the comet assay to assess DNA damage in buccal mucosa cells consequent to X-ray radiation from panoramic radiography. Methods: Twenty participants were recruited from among patients who underwent panoramic examinations at Prof. Soedomo Dental Hospital, Universitas Gadjah Mada, and divided into two groups of 10. Buccal mucosa cells were collected from all participants before exposure to IR and at 30 min or 24 h after exposure in groups 1 and 2, respectively, and subjected to a comet assay to assess DNA damage. Assay output images were analyzed using OpenComet software. Double-strand breaks (DSBs) were assessed by comparing the percentages of tail DNA in output images obtained before and after X-ray exposure. Results: A statistically significant (p=0.014) increase in the percentage of tail DNA was observed at 30 min after exposure, but not at 24 h (p=0.29). Conclusion: Panoramic X-ray radiation may induce DSBs in human buccal mucosal cells within 30 min after exposure.

Aim: Dental imaging has been widely used for diagnosis in dentistry. However, dental X-ray may induce cytotoxicity leading to apoptosis in oral mucosa cells. The present study aimed to observe the maturation pattern of buccal and gingival cells after exposure to X-ray radiation from analog/digital panoramic scanning and cone beam computed tomography (CBCT). Methods: The research samples were 40 subjects who fulfilled the inclusion and exclusion criteria. The subjects were divided into the exposed (patients who received analog/digital panoramic radiography or CBCT) and controlled (patients who had no radiography examinations) groups, with 10 subjects in each group. Exfoliative cytology smears were obtained from buccal mucosa and gingiva before exposure (or on day 0 for the control group) and 10 days later. The cells were stained with the Papanicolaou method. Then, the superficial, intermediate, and parabasal cells were counted in each glass slide. Results: No significant differences (p > 0.05) were observed among all cell types between day 0 and 10 in the control group. Meanwhile, after exposure to three kinds of radiography examinations, the frequency of intermediate cells in buccal mucosa and gingiva increased (p < 0.05), but that of superficial cells decreased (p < 0.05) significantly. No significant difference was found in the parabasal cells (p > 0.05). The frequency differences between intermediate and superficial cells showed no significant difference between the buccal mucosa and gingiva. Conclusion: Analog/digital panoramic radiography and CBCT exposure can induce cytotoxicity by altering the maturation pattern of buccal mucosa cells and gingiva, so it is strongly recommended to only perform these procedures if necessary and avoid repeated exposure to the same patient.

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Comet assay is a simple and precise method to analyze DNA damage. Nowadays, many research studies have demonstrated the effectiveness of buccal mucosa cells usage in comet assays. However, several software tools do not perform well for detecting and classifying comets from a comet assay image of buccal mucosa cells because the cell has a lot more noise. Therefore, a specific software tool is required for fully automated comet detection and classification from buccal mucosa cell swabs. This research proposes a deep learning-based fully automated framework using Faster R-CNN to detect and classify comets in a comet assay image taken from buccal mucosa swab. To train the Faster R-CNN model, buccal mucosa samples were collected from 24 patients in Indonesia. We acquired 275 comet assay images containing 519 comets. Furthermore, two strategies were used to overcome the lack of dataset problems during the model training, namely transfer learning and data augmentation. We implemented the proposed Faster R-CNN model as a web-based tool, GamaComet, that can be accessed freely for academic purposes. To test the GamaComet, buccal mucosa samples were collected from seven patients in Indonesia. We acquired 43 comet assay images containing 73 comets. GamaComet can give an accuracy of 81.34% for the detection task and an accuracy of 66.67% for the classification task. Furthermore, we also compared the performance of GamaComet with an existing free software tool for comet detection, OpenComet. The experiment results showed that GamaComet performed significantly better than OpenComet that could only give an accuracy of 11.5% for the comet detection task. Downstream analysis can be well conducted based on the detection and classification results from GamaComet. The analysis showed that patients owning comet assay images containing comets with class 3 and class 4 had a smoking habit, meaning they had more cells with a high level of DNA damage. Although GamaComet had a good performance, the performance for the classification task could still be improved. Therefore, it will be one of the future works for the research development of GamaComet.