LPS-Induced Neuron Cell Apoptosis through TNF-α and Cytochrome c Expression in Dental Pulp.

OBJECTIVES: Inflammation of the dental pulp tissue caused by bacteria, creating an immunology response of death of the dental pulp, is called apoptosis. The Porphyromonas gingivalis that cause apoptosis is lipopolysaccharide (LPS) through toll-like receptor (TLR) via two different mechanisms, intracellular and extracellular pathways. This study analyzed the role of LPS exposure of neuron cells, tumor necrosis factor-α (TNF-α), and cytochrome c (cyt-c) expression in the dental pulp to predict the possible mechanism of apoptosis. MATERIALS AND METHODS: The lower tooth of Sprague Dawley rats was opened and exposed to LPS for 48 hours. Then the neuron cell analyzed histopathology using hematoxylin-eosin, whereas the TNF-α and cyt-c expression with indirect immunohistochemistry using a light microscope. The relationship between neuron cells with TNF-α and cyt-c was analyzed using stepwise regression linear analysis. RESULT: The LPS exposure showed a lower number of neuron cells and had a relationship with TNF-α expression but not with cyt-c, while compared with control, both TNF-α and cyt-c expression were higher in neuron cells. CONCLUSION: LPS exposure in dental pulp is possible to stimulate the apoptosis process through extracellular pathways marked by higher TNF-α expression.

Deep convolutional neural network algorithm for the automatic segmentation of oral potentially malignant disorders and oral cancers.

This study aimed to develop an algorithm to automatically segment the oral potentially malignant diseases (OPMDs) and oral cancers (OCs) of all oral subsites with various deep convolutional neural network applications. A total of 510 intraoral images of OPMDs and OCs were collected over 3 years (2006-2009). All images were confirmed both with patient records and histopathological reports. Following the labeling of the lesions the dataset was arbitrarily split, using random sampling in Python as the study dataset, validation dataset, and test dataset. Pixels were classified as the OPMDs and OCs with the OPMD/OC label and the rest as the background. U-Net architecture was used and the model with the best validation loss was chosen for the testing among the trained 500 epochs. Dice similarity coefficient (DSC) score was noted. The intra-observer ICC was found to be 0.994 while the inter-observer reliability was 0.989. The calculated DSC and validation accuracy across all clinical images were 0.697 and 0.805, respectively. Our algorithm did not maintain an excellent DSC due to multiple reasons for the detection of both OC and OPMDs in oral cavity sites. A better standardization for both 2D and 3D imaging (such as patient positioning) and a bigger dataset are required to improve the quality of such studies. This is the first study which aimed to segment OPMDs and OCs in all subsites of oral cavity which is crucial not only for the early diagnosis but also for higher survival rates.

Evaluation of Root Anatomy and Canal Configuration of Human Permanent Maxillary First Molar Using Cone-Beam Computed Tomography: A Systematic Review.

The aim of this paper is to review the literature on root canal configuration (RCC) and the frequency of occurrence of a second mesiobuccal canal (MB) in human permanent maxillary first molars where cone-beam computed tomography (CBCT) is used. Online electronic databases such as PubMed-Medline, Embase, Scopus and Cochrane Library were searched using appropriate keywords from the earliest available date until 12th June 2022, without restriction on language. In the mesiobuccal root, type I was the most frequent (33.29%), followed by types II and IV (27.18% and 26.36%, respectively). Moreover, 68.2% of maxillary first molars had a second MB canal. For both the distobuccal and palatal roots, type I was the most prevalent, with 99.08% and 97.83% occurrence, respectively. All other types were infrequent. Type I RCC is most frequent in all the roots of the maxillary first molars. Hence, care must be taken during biomechanical preparation of the MB roots.

Apical debris extrusion during instrumentation of oval root canals in primary teeth using manual versus motorized files: an ex vivo study.

This study aimed to assess the apical extrusion of debris during instrumentation of primary canines using three endodontic file types. Forty-five extracted primary canines were randomly assigned to three instrumentation groups (n = 15): Hand K-files; and the motorized Kedo-S files and XP-endo Shaper files. The apically extruded debris produced during the procedure was collected and dried in pre-weighed Eppendorf tubes, and the mass of debris was calculated. The time required for the endodontic procedure was also recorded. Analysis of variance (ANOVA) and Tukey's post hoc test were used with a significance level set at 5%. XP-endo Shaper and Kedo-S files extruded significantly less debris compared with hand K-files with means of 0.84 ± 0.31 and 1.20 ± 0.67 mg respectively, compared to 2.13 ± 0.31 mg (p < 0.0001). No significant difference was found between the two motorized files. Less time was required to complete the procedure with the XP-endo Shaper compared to the hand K-files (p < 0.0001) and Kedo-S files (p < 0.0001). Within the limitations of the present study, it may be concluded that motorized files extruded less debris and required less instrumentation time compared to traditional K-files, which could benefit paediatric patients with root canal treatment needs.