Materials and Methods: In order to conduct this review, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Studies published from 2015 to 2021 under the keywords (deep convolutional neural network) AND (caries), (deep learning caries) AND (convolutional neural network) AND (caries) were systematically reviewed.
Results: When dental caries is improperly diagnosed, the lesion may eventually invade the enamel, dentin, and pulp tissue, leading to loss of tooth function. Rapid and precise detection and diagnosis are vital for implementing appropriate prevention and treatment of dental caries. Radiography and intraoral images are considered to play a vital role in detecting dental caries; nevertheless, studies have shown that 20% of suspicious areas are mistakenly diagnosed as dental caries using this technique; hence, diagnosis via radiography alone without an objective assessment is inaccurate. Identifying caries with a deep convolutional neural network-based detector enables the operator to distinguish changes in the location and morphological features of dental caries lesions. Deep learning algorithms have broader and more profound layers and are continually being developed, remarkably enhancing their precision in detecting and segmenting objects.
Conclusion: Clinical applications of deep learning convolutional neural networks in the dental field have shown significant accuracy in detecting and diagnosing dental caries, and these models hold promise in supporting dental practitioners to improve patient outcomes.
METHODS: The RCSs, namely GuttaFlow Bioseal, MTA Fillapex, CeraSeal Bioceramic, and iRoot SP, were mixed according to the manufacturer's guidelines. The extract solution was prepared by immersing the set RCS into 1X dilution of E3 solution. Then, the extract solution was delivered into a Petri dish where zebrafish embryos were allowed to develop. Cytotoxicity was evaluated 24, 48, 72, and 96 hours after fertilization.
RESULTS: The Kruskal-Wallis test showed that except for GuttaFlow Bioseal, the mortality, survival, and hatching of zebrafish embryos for the remaining three bioceramic RCSs were significantly different from the negative controls (P<0.05). Significant differences were also evident in the mortality, survival, and hatching of zebrafish embryos between GuttaFlow Bioseal and three other RCSs (P<0.05).
CONCLUSION: GuttaFlow Bioseal was less cytotoxic than other bioceramics RCSs; MTA Fillapex, CeraSeal Bioceramic root canal sealer, and iRoot SP root canal sealer exhibited comparable cytotoxicity.
METHODS: The antioxidant properties were analysed using 2,2'-diphenyl-1 picrylhydrazyl (DPPH), ferric reducing antioxidant potential (FRAP) and 2,2'-azinodi 3-ethylbenthiazolinesulfonate (ABTS) assays. Cytotoxicity was assayed using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) test and the induction of apoptosis was observed via caspase-3/7 activity assay. The identification of phenolic compounds was done via ultra-high-performance-liquid chromatography coupled to mass spectrometer (UHPLC-MS/MS).
RESULTS: The antioxidant analysis exhibited: the half inhibitory concentration (IC50) of DPPH inhibition, 54.10 (SD = 4.51) μg/mL; the FRAP value, 30.07 (SD = 0.93) mM TEQ/100 g; and the ABTS value, 131.79 (SD = 8.73) mg TEQ/100 g. Cinnamic acid was the most abundant phenolic compound, followed by maleic acid and salicylic acid. The IC50 for ORL115 and ORL188 were 35.51 mg/mL and 43.54 mg/mL, respectively. The cells became rounded and dissymmetrical which reduced in number and size. The apoptotic cell death in ORL115 and ORL188 was deduced as caspase-3/7 activities that significantly increased (P < 0.05).
CONCLUSION: The study evidenced that the antioxidant activity of MTJ could influence the induction of apoptosis in ORL115 and ORL188 in future investigations and verifications.