Taxillus yadoriki (Siebold) Dancer is a parasitic plant that grows on camellia trees and is common on Jeju Island. The branches of T. yadoriki have long been used to treat various diseases, including hypertension, diabetes mellitus, viral infections, and arthritis. Although recent studies reported that T. yadoriki has anticancer effects in various human cancer cell lines, including lung cancer, the exact molecular mechanisms supporting its anticancer effects are not well understood. This study aims to assess the anticancer effect of the methanol extract of T. yadoriki branches (METY) on mucoepidermoid carcinoma (MEC) cell lines (MC3 cells and YD15 cells) and explore its mechanism of action. Inhibitory activity of MEC cell proliferation was assessed using the CCK-8 assay. The mechanism of the anticancer effect on METY-treated MC3 cells and YD15 cells was evaluated with Hoechst 33342 stain and Western blot. After treating MC3 cells and YD15 cells with METY for 48 hours, the cytotoxicity of MC3 and YD15 cells increased, and nuclear fragmentation increased in both METY-treated MEC cells. Caspase-3 and cleaved PARP activation demonstrated apoptosis of METY-treated MEC cells. Cell proliferation inhibition with METY was alleviated in METY-treated MEC cells pretreated with zVAD-FMK, supporting the cell proliferation inhibition effect by apoptosis. METY-induced apoptosis in MEC cells occurs through MAP kinase pathways such as p38 and pAkt. MEC cell. METY-induced apoptosis of MEC cells occurs via the p38 and pAkt MAPK pathways. Therefore, METY may be a promising anticancer candidate for the MEC therapeutic strategy.
Fluorescent probe were used to evaluate the effects of catechin on the structural parameters (annular lipid fluidity, transbilayer lateral and rotational mobility and protein clustering) of the Porphyromonas gingivalis outer membrane (OPGs). An experimental procedure was used on the basis of selective quenching of 1,6-diphenyl-1,3,5-hexatriene (DPH) and 1,3-di(1-pyrenyl)propane (Py-3-Py) by trinitrophenyl groups and radiationless energy transfer from the tryptophans of membrane proteins to Py-3-Py and DPH. Catechin increased the bulk lateral and rotational mobility, annular lipid fluidity of OPGs lipid bilayers, and had greater fluidizing efficacy on the outer monolayer than the inner monolayer. It also caused membrane proteins to cluster. Based on these effects of catechin on OPGs, the antibacterial and antiviral actions of catechin can be partially explained.
The purpose of this study was to verify the sensitive areas when the AI determines osteoporosis for the entire area of the panoramic radiograph. Panoramic radiographs of a total of 1,156 female patients(average age of 49.0±24.0 years) were used for this study. The panoramic radiographs were diagnosed as osteoporosis and the normal by Oral and Maxillofacial Radiology specialists. The VGG16 deep learning convolutional neural network(CNN) model was used to determine osteoporosis and the normal from testing 72 osteoporosis(average age of 73.7±8.0 years) and 93 normal(average age of 26.4±5.1 years). VGG16 conducted a gradient-weighted class activation mapping(Grad-CAM) visualization to indicate sensitive areas when determining osteoporosis. The accuracy of CNN in determining osteoporosis was 100%. Heatmap image from 72 panoamic radiographs of osteoporosis revealed that CNN was sensitive to the cervical vertebral in 70.8%(51/72), the cortical bone of the lower mandible in 72.2%(52/72), the cranial base area in 30.6%(22/72), the cancellous bone of the mandible in 33.3%(24/72), the cancellous bone of the maxilla in 20.8%(15/72), the zygoma in 8.3%(6/72), and the dental area in 5.6%(4/72). Consideration: it was found that the cervical vertebral area and the cortical bone of the lower mandible were sensitive areas when CNN determines osteoporosis in the entire area of panoramic radiographs.